linux-kernelorg-stable/include/linux/energy_model.h

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PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
/* SPDX-License-Identifier: GPL-2.0 */
#ifndef _LINUX_ENERGY_MODEL_H
#define _LINUX_ENERGY_MODEL_H
#include <linux/cpumask.h>
#include <linux/device.h>
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
#include <linux/jump_label.h>
#include <linux/kobject.h>
#include <linux/kref.h>
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
#include <linux/rcupdate.h>
#include <linux/sched/cpufreq.h>
#include <linux/sched/topology.h>
#include <linux/types.h>
/**
* struct em_perf_state - Performance state of a performance domain
* @performance: CPU performance (capacity) at a given frequency
* @frequency: The frequency in KHz, for consistency with CPUFreq
* @power: The power consumed at this level (by 1 CPU or by a registered
* device). It can be a total power: static and dynamic.
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
* @cost: The cost coefficient associated with this level, used during
* energy calculation. Equal to: power * max_frequency / frequency
* @flags: see "em_perf_state flags" description below.
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
*/
struct em_perf_state {
unsigned long performance;
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
unsigned long frequency;
unsigned long power;
unsigned long cost;
unsigned long flags;
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
};
/*
* em_perf_state flags:
*
* EM_PERF_STATE_INEFFICIENT: The performance state is inefficient. There is
* in this em_perf_domain, another performance state with a higher frequency
* but a lower or equal power cost. Such inefficient states are ignored when
* using em_pd_get_efficient_*() functions.
*/
#define EM_PERF_STATE_INEFFICIENT BIT(0)
/**
* struct em_perf_table - Performance states table
* @rcu: RCU used for safe access and destruction
* @kref: Reference counter to track the users
* @state: List of performance states, in ascending order
*/
struct em_perf_table {
struct rcu_head rcu;
struct kref kref;
struct em_perf_state state[];
};
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
/**
* struct em_perf_domain - Performance domain
* @em_table: Pointer to the runtime modifiable em_perf_table
* @nr_perf_states: Number of performance states
* @min_perf_state: Minimum allowed Performance State index
* @max_perf_state: Maximum allowed Performance State index
* @flags: See "em_perf_domain flags"
* @cpus: Cpumask covering the CPUs of the domain. It's here
* for performance reasons to avoid potential cache
* misses during energy calculations in the scheduler
* and simplifies allocating/freeing that memory region.
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
*
* In case of CPU device, a "performance domain" represents a group of CPUs
* whose performance is scaled together. All CPUs of a performance domain
* must have the same micro-architecture. Performance domains often have
* a 1-to-1 mapping with CPUFreq policies. In case of other devices the @cpus
* field is unused.
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
*/
struct em_perf_domain {
struct em_perf_table __rcu *em_table;
int nr_perf_states;
int min_perf_state;
int max_perf_state;
unsigned long flags;
unsigned long cpus[];
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
};
/*
* em_perf_domain flags:
*
PM: EM: convert power field to micro-Watts precision and align drivers The milli-Watts precision causes rounding errors while calculating efficiency cost for each OPP. This is especially visible in the 'simple' Energy Model (EM), where the power for each OPP is provided from OPP framework. This can cause some OPPs to be marked inefficient, while using micro-Watts precision that might not happen. Update all EM users which access 'power' field and assume the value is in milli-Watts. Solve also an issue with potential overflow in calculation of energy estimation on 32bit machine. It's needed now since the power value (thus the 'cost' as well) are higher. Example calculation which shows the rounding error and impact: power = 'dyn-power-coeff' * volt_mV * volt_mV * freq_MHz power_a_uW = (100 * 600mW * 600mW * 500MHz) / 10^6 = 18000 power_a_mW = (100 * 600mW * 600mW * 500MHz) / 10^9 = 18 power_b_uW = (100 * 605mW * 605mW * 600MHz) / 10^6 = 21961 power_b_mW = (100 * 605mW * 605mW * 600MHz) / 10^9 = 21 max_freq = 2000MHz cost_a_mW = 18 * 2000MHz/500MHz = 72 cost_a_uW = 18000 * 2000MHz/500MHz = 72000 cost_b_mW = 21 * 2000MHz/600MHz = 70 // <- artificially better cost_b_uW = 21961 * 2000MHz/600MHz = 73203 The 'cost_b_mW' (which is based on old milli-Watts) is misleadingly better that the 'cost_b_uW' (this patch uses micro-Watts) and such would have impact on the 'inefficient OPPs' information in the Cpufreq framework. This patch set removes the rounding issue. Signed-off-by: Lukasz Luba <lukasz.luba@arm.com> Acked-by: Daniel Lezcano <daniel.lezcano@linaro.org> Acked-by: Viresh Kumar <viresh.kumar@linaro.org> Signed-off-by: Rafael J. Wysocki <rafael.j.wysocki@intel.com>
2022-07-07 07:15:52 +00:00
* EM_PERF_DOMAIN_MICROWATTS: The power values are in micro-Watts or some
* other scale.
*
* EM_PERF_DOMAIN_SKIP_INEFFICIENCIES: Skip inefficient states when estimating
* energy consumption.
*
* EM_PERF_DOMAIN_ARTIFICIAL: The power values are artificial and might be
* created by platform missing real power information
*/
PM: EM: convert power field to micro-Watts precision and align drivers The milli-Watts precision causes rounding errors while calculating efficiency cost for each OPP. This is especially visible in the 'simple' Energy Model (EM), where the power for each OPP is provided from OPP framework. This can cause some OPPs to be marked inefficient, while using micro-Watts precision that might not happen. Update all EM users which access 'power' field and assume the value is in milli-Watts. Solve also an issue with potential overflow in calculation of energy estimation on 32bit machine. It's needed now since the power value (thus the 'cost' as well) are higher. Example calculation which shows the rounding error and impact: power = 'dyn-power-coeff' * volt_mV * volt_mV * freq_MHz power_a_uW = (100 * 600mW * 600mW * 500MHz) / 10^6 = 18000 power_a_mW = (100 * 600mW * 600mW * 500MHz) / 10^9 = 18 power_b_uW = (100 * 605mW * 605mW * 600MHz) / 10^6 = 21961 power_b_mW = (100 * 605mW * 605mW * 600MHz) / 10^9 = 21 max_freq = 2000MHz cost_a_mW = 18 * 2000MHz/500MHz = 72 cost_a_uW = 18000 * 2000MHz/500MHz = 72000 cost_b_mW = 21 * 2000MHz/600MHz = 70 // <- artificially better cost_b_uW = 21961 * 2000MHz/600MHz = 73203 The 'cost_b_mW' (which is based on old milli-Watts) is misleadingly better that the 'cost_b_uW' (this patch uses micro-Watts) and such would have impact on the 'inefficient OPPs' information in the Cpufreq framework. This patch set removes the rounding issue. Signed-off-by: Lukasz Luba <lukasz.luba@arm.com> Acked-by: Daniel Lezcano <daniel.lezcano@linaro.org> Acked-by: Viresh Kumar <viresh.kumar@linaro.org> Signed-off-by: Rafael J. Wysocki <rafael.j.wysocki@intel.com>
2022-07-07 07:15:52 +00:00
#define EM_PERF_DOMAIN_MICROWATTS BIT(0)
#define EM_PERF_DOMAIN_SKIP_INEFFICIENCIES BIT(1)
#define EM_PERF_DOMAIN_ARTIFICIAL BIT(2)
#define em_span_cpus(em) (to_cpumask((em)->cpus))
#define em_is_artificial(em) ((em)->flags & EM_PERF_DOMAIN_ARTIFICIAL)
#ifdef CONFIG_ENERGY_MODEL
PM: EM: convert power field to micro-Watts precision and align drivers The milli-Watts precision causes rounding errors while calculating efficiency cost for each OPP. This is especially visible in the 'simple' Energy Model (EM), where the power for each OPP is provided from OPP framework. This can cause some OPPs to be marked inefficient, while using micro-Watts precision that might not happen. Update all EM users which access 'power' field and assume the value is in milli-Watts. Solve also an issue with potential overflow in calculation of energy estimation on 32bit machine. It's needed now since the power value (thus the 'cost' as well) are higher. Example calculation which shows the rounding error and impact: power = 'dyn-power-coeff' * volt_mV * volt_mV * freq_MHz power_a_uW = (100 * 600mW * 600mW * 500MHz) / 10^6 = 18000 power_a_mW = (100 * 600mW * 600mW * 500MHz) / 10^9 = 18 power_b_uW = (100 * 605mW * 605mW * 600MHz) / 10^6 = 21961 power_b_mW = (100 * 605mW * 605mW * 600MHz) / 10^9 = 21 max_freq = 2000MHz cost_a_mW = 18 * 2000MHz/500MHz = 72 cost_a_uW = 18000 * 2000MHz/500MHz = 72000 cost_b_mW = 21 * 2000MHz/600MHz = 70 // <- artificially better cost_b_uW = 21961 * 2000MHz/600MHz = 73203 The 'cost_b_mW' (which is based on old milli-Watts) is misleadingly better that the 'cost_b_uW' (this patch uses micro-Watts) and such would have impact on the 'inefficient OPPs' information in the Cpufreq framework. This patch set removes the rounding issue. Signed-off-by: Lukasz Luba <lukasz.luba@arm.com> Acked-by: Daniel Lezcano <daniel.lezcano@linaro.org> Acked-by: Viresh Kumar <viresh.kumar@linaro.org> Signed-off-by: Rafael J. Wysocki <rafael.j.wysocki@intel.com>
2022-07-07 07:15:52 +00:00
/*
* The max power value in micro-Watts. The limit of 64 Watts is set as
* a safety net to not overflow multiplications on 32bit platforms. The
* 32bit value limit for total Perf Domain power implies a limit of
* maximum CPUs in such domain to 64.
*/
#define EM_MAX_POWER (64000000) /* 64 Watts */
/*
* To avoid possible energy estimation overflow on 32bit machines add
* limits to number of CPUs in the Perf. Domain.
* We are safe on 64bit machine, thus some big number.
*/
#ifdef CONFIG_64BIT
#define EM_MAX_NUM_CPUS 4096
#else
#define EM_MAX_NUM_CPUS 16
#endif
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
struct em_data_callback {
/**
* active_power() - Provide power at the next performance state of
* a device
* @dev : Device for which we do this operation (can be a CPU)
* @power : Active power at the performance state
* (modified)
* @freq : Frequency at the performance state in kHz
* (modified)
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
*
* active_power() must find the lowest performance state of 'dev' above
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
* 'freq' and update 'power' and 'freq' to the matching active power
* and frequency.
*
* In case of CPUs, the power is the one of a single CPU in the domain,
PM: EM: convert power field to micro-Watts precision and align drivers The milli-Watts precision causes rounding errors while calculating efficiency cost for each OPP. This is especially visible in the 'simple' Energy Model (EM), where the power for each OPP is provided from OPP framework. This can cause some OPPs to be marked inefficient, while using micro-Watts precision that might not happen. Update all EM users which access 'power' field and assume the value is in milli-Watts. Solve also an issue with potential overflow in calculation of energy estimation on 32bit machine. It's needed now since the power value (thus the 'cost' as well) are higher. Example calculation which shows the rounding error and impact: power = 'dyn-power-coeff' * volt_mV * volt_mV * freq_MHz power_a_uW = (100 * 600mW * 600mW * 500MHz) / 10^6 = 18000 power_a_mW = (100 * 600mW * 600mW * 500MHz) / 10^9 = 18 power_b_uW = (100 * 605mW * 605mW * 600MHz) / 10^6 = 21961 power_b_mW = (100 * 605mW * 605mW * 600MHz) / 10^9 = 21 max_freq = 2000MHz cost_a_mW = 18 * 2000MHz/500MHz = 72 cost_a_uW = 18000 * 2000MHz/500MHz = 72000 cost_b_mW = 21 * 2000MHz/600MHz = 70 // <- artificially better cost_b_uW = 21961 * 2000MHz/600MHz = 73203 The 'cost_b_mW' (which is based on old milli-Watts) is misleadingly better that the 'cost_b_uW' (this patch uses micro-Watts) and such would have impact on the 'inefficient OPPs' information in the Cpufreq framework. This patch set removes the rounding issue. Signed-off-by: Lukasz Luba <lukasz.luba@arm.com> Acked-by: Daniel Lezcano <daniel.lezcano@linaro.org> Acked-by: Viresh Kumar <viresh.kumar@linaro.org> Signed-off-by: Rafael J. Wysocki <rafael.j.wysocki@intel.com>
2022-07-07 07:15:52 +00:00
* expressed in micro-Watts or an abstract scale. It is expected to
* fit in the [0, EM_MAX_POWER] range.
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
*
* Return 0 on success.
*/
int (*active_power)(struct device *dev, unsigned long *power,
unsigned long *freq);
PM: EM: Add .get_cost() callback The Energy Model (EM) supports devices which report abstract power scale, not only real Watts. The primary goal for EM is to enable the Energy Aware Scheduler (EAS) for a given platform. Some of the platforms might not be able to deliver proper power values. The only information that they might have is the relative efficiency between CPU types. Thus, it makes sense to remove some restrictions in the EM framework and introduce a mechanism which would support those platforms. What is crucial for EAS to operate is the 'cost' field in the EM. The 'cost' is calculated internally in EM framework based on knowledge from 'power' values. The 'cost' values must be strictly increasing. The existing API with its 'power' value size restrictions cannot guarantee that the 'cost' will meet this requirement. Since the platform is missing this detailed information, but has only efficiency details, introduce a new custom callback in the EM framework. The new callback would allow to provide the 'cost' values which reflect efficiency of the CPUs. This would allow to provide EAS information which has different relation than what would be forced by the EM internal formulas calculating 'cost' values. Thanks to this new callback it is possible to create a system view for EAS which has no overlapping performance states across many Performance Domains. Signed-off-by: Lukasz Luba <lukasz.luba@arm.com> Reviewed-by: Ionela Voinescu <ionela.voinescu@arm.com> Signed-off-by: Rafael J. Wysocki <rafael.j.wysocki@intel.com>
2022-03-21 09:57:22 +00:00
/**
* get_cost() - Provide the cost at the given performance state of
* a device
* @dev : Device for which we do this operation (can be a CPU)
* @freq : Frequency at the performance state in kHz
* @cost : The cost value for the performance state
* (modified)
*
* In case of CPUs, the cost is the one of a single CPU in the domain.
* It is expected to fit in the [0, EM_MAX_POWER] range due to internal
* usage in EAS calculation.
*
* Return 0 on success, or appropriate error value in case of failure.
*/
int (*get_cost)(struct device *dev, unsigned long freq,
unsigned long *cost);
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
};
#define EM_SET_ACTIVE_POWER_CB(em_cb, cb) ((em_cb).active_power = cb)
PM: EM: Add .get_cost() callback The Energy Model (EM) supports devices which report abstract power scale, not only real Watts. The primary goal for EM is to enable the Energy Aware Scheduler (EAS) for a given platform. Some of the platforms might not be able to deliver proper power values. The only information that they might have is the relative efficiency between CPU types. Thus, it makes sense to remove some restrictions in the EM framework and introduce a mechanism which would support those platforms. What is crucial for EAS to operate is the 'cost' field in the EM. The 'cost' is calculated internally in EM framework based on knowledge from 'power' values. The 'cost' values must be strictly increasing. The existing API with its 'power' value size restrictions cannot guarantee that the 'cost' will meet this requirement. Since the platform is missing this detailed information, but has only efficiency details, introduce a new custom callback in the EM framework. The new callback would allow to provide the 'cost' values which reflect efficiency of the CPUs. This would allow to provide EAS information which has different relation than what would be forced by the EM internal formulas calculating 'cost' values. Thanks to this new callback it is possible to create a system view for EAS which has no overlapping performance states across many Performance Domains. Signed-off-by: Lukasz Luba <lukasz.luba@arm.com> Reviewed-by: Ionela Voinescu <ionela.voinescu@arm.com> Signed-off-by: Rafael J. Wysocki <rafael.j.wysocki@intel.com>
2022-03-21 09:57:22 +00:00
#define EM_ADV_DATA_CB(_active_power_cb, _cost_cb) \
{ .active_power = _active_power_cb, \
.get_cost = _cost_cb }
#define EM_DATA_CB(_active_power_cb) \
EM_ADV_DATA_CB(_active_power_cb, NULL)
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
struct em_perf_domain *em_cpu_get(int cpu);
struct em_perf_domain *em_pd_get(struct device *dev);
int em_dev_update_perf_domain(struct device *dev,
PM: EM: Address RCU-related sparse warnings The usage of __rcu in the Energy Model code is quite inconsistent which causes the following sparse warnings to trigger: kernel/power/energy_model.c:169:15: warning: incorrect type in assignment (different address spaces) kernel/power/energy_model.c:169:15: expected struct em_perf_table [noderef] __rcu *table kernel/power/energy_model.c:169:15: got struct em_perf_table * kernel/power/energy_model.c:171:9: warning: incorrect type in argument 1 (different address spaces) kernel/power/energy_model.c:171:9: expected struct callback_head *head kernel/power/energy_model.c:171:9: got struct callback_head [noderef] __rcu * kernel/power/energy_model.c:171:9: warning: cast removes address space '__rcu' of expression kernel/power/energy_model.c:182:19: warning: incorrect type in argument 1 (different address spaces) kernel/power/energy_model.c:182:19: expected struct kref *kref kernel/power/energy_model.c:182:19: got struct kref [noderef] __rcu * kernel/power/energy_model.c:200:15: warning: incorrect type in assignment (different address spaces) kernel/power/energy_model.c:200:15: expected struct em_perf_table [noderef] __rcu *table kernel/power/energy_model.c:200:15: got void *[assigned] _res kernel/power/energy_model.c:204:20: warning: incorrect type in argument 1 (different address spaces) kernel/power/energy_model.c:204:20: expected struct kref *kref kernel/power/energy_model.c:204:20: got struct kref [noderef] __rcu * kernel/power/energy_model.c:320:19: warning: incorrect type in argument 1 (different address spaces) kernel/power/energy_model.c:320:19: expected struct kref *kref kernel/power/energy_model.c:320:19: got struct kref [noderef] __rcu * kernel/power/energy_model.c:325:45: warning: incorrect type in argument 2 (different address spaces) kernel/power/energy_model.c:325:45: expected struct em_perf_state *table kernel/power/energy_model.c:325:45: got struct em_perf_state [noderef] __rcu * kernel/power/energy_model.c:425:45: warning: incorrect type in argument 3 (different address spaces) kernel/power/energy_model.c:425:45: expected struct em_perf_state *table kernel/power/energy_model.c:425:45: got struct em_perf_state [noderef] __rcu * kernel/power/energy_model.c:442:15: warning: incorrect type in argument 1 (different address spaces) kernel/power/energy_model.c:442:15: expected void const *objp kernel/power/energy_model.c:442:15: got struct em_perf_table [noderef] __rcu *[assigned] em_table kernel/power/energy_model.c:626:55: warning: incorrect type in argument 2 (different address spaces) kernel/power/energy_model.c:626:55: expected struct em_perf_state *table kernel/power/energy_model.c:626:55: got struct em_perf_state [noderef] __rcu * kernel/power/energy_model.c:681:16: warning: incorrect type in assignment (different address spaces) kernel/power/energy_model.c:681:16: expected struct em_perf_state *new_ps kernel/power/energy_model.c:681:16: got struct em_perf_state [noderef] __rcu * kernel/power/energy_model.c:699:37: warning: incorrect type in argument 2 (different address spaces) kernel/power/energy_model.c:699:37: expected struct em_perf_state *table kernel/power/energy_model.c:699:37: got struct em_perf_state [noderef] __rcu * kernel/power/energy_model.c:733:38: warning: incorrect type in argument 3 (different address spaces) kernel/power/energy_model.c:733:38: expected struct em_perf_state *table kernel/power/energy_model.c:733:38: got struct em_perf_state [noderef] __rcu * kernel/power/energy_model.c:855:53: warning: dereference of noderef expression kernel/power/energy_model.c:864:32: warning: dereference of noderef expression This is because the __rcu annotation for sparse is only applicable to pointers that need rcu_dereference() or equivalent for protection, which basically means pointers assigned with rcu_assign_pointer(). Make all of the above sparse warnings go away by cleaning up the usage of __rcu and using rcu_dereference_protected() where applicable. Cc: All applicable <stable@vger.kernel.org> Signed-off-by: Rafael J. Wysocki <rafael.j.wysocki@intel.com> Reviewed-by: Lukasz Luba <lukasz.luba@arm.com> Link: https://patch.msgid.link/5885405.DvuYhMxLoT@rjwysocki.net
2025-03-06 16:49:20 +00:00
struct em_perf_table *new_table);
int em_dev_register_perf_domain(struct device *dev, unsigned int nr_states,
const struct em_data_callback *cb,
const cpumask_t *cpus, bool microwatts);
void em_dev_unregister_perf_domain(struct device *dev);
PM: EM: Address RCU-related sparse warnings The usage of __rcu in the Energy Model code is quite inconsistent which causes the following sparse warnings to trigger: kernel/power/energy_model.c:169:15: warning: incorrect type in assignment (different address spaces) kernel/power/energy_model.c:169:15: expected struct em_perf_table [noderef] __rcu *table kernel/power/energy_model.c:169:15: got struct em_perf_table * kernel/power/energy_model.c:171:9: warning: incorrect type in argument 1 (different address spaces) kernel/power/energy_model.c:171:9: expected struct callback_head *head kernel/power/energy_model.c:171:9: got struct callback_head [noderef] __rcu * kernel/power/energy_model.c:171:9: warning: cast removes address space '__rcu' of expression kernel/power/energy_model.c:182:19: warning: incorrect type in argument 1 (different address spaces) kernel/power/energy_model.c:182:19: expected struct kref *kref kernel/power/energy_model.c:182:19: got struct kref [noderef] __rcu * kernel/power/energy_model.c:200:15: warning: incorrect type in assignment (different address spaces) kernel/power/energy_model.c:200:15: expected struct em_perf_table [noderef] __rcu *table kernel/power/energy_model.c:200:15: got void *[assigned] _res kernel/power/energy_model.c:204:20: warning: incorrect type in argument 1 (different address spaces) kernel/power/energy_model.c:204:20: expected struct kref *kref kernel/power/energy_model.c:204:20: got struct kref [noderef] __rcu * kernel/power/energy_model.c:320:19: warning: incorrect type in argument 1 (different address spaces) kernel/power/energy_model.c:320:19: expected struct kref *kref kernel/power/energy_model.c:320:19: got struct kref [noderef] __rcu * kernel/power/energy_model.c:325:45: warning: incorrect type in argument 2 (different address spaces) kernel/power/energy_model.c:325:45: expected struct em_perf_state *table kernel/power/energy_model.c:325:45: got struct em_perf_state [noderef] __rcu * kernel/power/energy_model.c:425:45: warning: incorrect type in argument 3 (different address spaces) kernel/power/energy_model.c:425:45: expected struct em_perf_state *table kernel/power/energy_model.c:425:45: got struct em_perf_state [noderef] __rcu * kernel/power/energy_model.c:442:15: warning: incorrect type in argument 1 (different address spaces) kernel/power/energy_model.c:442:15: expected void const *objp kernel/power/energy_model.c:442:15: got struct em_perf_table [noderef] __rcu *[assigned] em_table kernel/power/energy_model.c:626:55: warning: incorrect type in argument 2 (different address spaces) kernel/power/energy_model.c:626:55: expected struct em_perf_state *table kernel/power/energy_model.c:626:55: got struct em_perf_state [noderef] __rcu * kernel/power/energy_model.c:681:16: warning: incorrect type in assignment (different address spaces) kernel/power/energy_model.c:681:16: expected struct em_perf_state *new_ps kernel/power/energy_model.c:681:16: got struct em_perf_state [noderef] __rcu * kernel/power/energy_model.c:699:37: warning: incorrect type in argument 2 (different address spaces) kernel/power/energy_model.c:699:37: expected struct em_perf_state *table kernel/power/energy_model.c:699:37: got struct em_perf_state [noderef] __rcu * kernel/power/energy_model.c:733:38: warning: incorrect type in argument 3 (different address spaces) kernel/power/energy_model.c:733:38: expected struct em_perf_state *table kernel/power/energy_model.c:733:38: got struct em_perf_state [noderef] __rcu * kernel/power/energy_model.c:855:53: warning: dereference of noderef expression kernel/power/energy_model.c:864:32: warning: dereference of noderef expression This is because the __rcu annotation for sparse is only applicable to pointers that need rcu_dereference() or equivalent for protection, which basically means pointers assigned with rcu_assign_pointer(). Make all of the above sparse warnings go away by cleaning up the usage of __rcu and using rcu_dereference_protected() where applicable. Cc: All applicable <stable@vger.kernel.org> Signed-off-by: Rafael J. Wysocki <rafael.j.wysocki@intel.com> Reviewed-by: Lukasz Luba <lukasz.luba@arm.com> Link: https://patch.msgid.link/5885405.DvuYhMxLoT@rjwysocki.net
2025-03-06 16:49:20 +00:00
struct em_perf_table *em_table_alloc(struct em_perf_domain *pd);
void em_table_free(struct em_perf_table *table);
int em_dev_compute_costs(struct device *dev, struct em_perf_state *table,
int nr_states);
int em_dev_update_chip_binning(struct device *dev);
int em_update_performance_limits(struct em_perf_domain *pd,
unsigned long freq_min_khz, unsigned long freq_max_khz);
void em_adjust_cpu_capacity(unsigned int cpu);
void em_rebuild_sched_domains(void);
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
/**
* em_pd_get_efficient_state() - Get an efficient performance state from the EM
* @table: List of performance states, in ascending order
* @pd: performance domain for which this must be done
* @max_util: Max utilization to map with the EM
*
* It is called from the scheduler code quite frequently and as a consequence
* doesn't implement any check.
*
* Return: An efficient performance state id, high enough to meet @max_util
* requirement.
*/
static inline int
em_pd_get_efficient_state(struct em_perf_state *table,
struct em_perf_domain *pd, unsigned long max_util)
{
unsigned long pd_flags = pd->flags;
int min_ps = pd->min_perf_state;
int max_ps = pd->max_perf_state;
struct em_perf_state *ps;
int i;
for (i = min_ps; i <= max_ps; i++) {
ps = &table[i];
if (ps->performance >= max_util) {
if (pd_flags & EM_PERF_DOMAIN_SKIP_INEFFICIENCIES &&
ps->flags & EM_PERF_STATE_INEFFICIENT)
continue;
return i;
}
}
return max_ps;
}
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
/**
* em_cpu_energy() - Estimates the energy consumed by the CPUs of a
* performance domain
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
* @pd : performance domain for which energy has to be estimated
* @max_util : highest utilization among CPUs of the domain
* @sum_util : sum of the utilization of all CPUs in the domain
sched/cpufreq: Consider reduced CPU capacity in energy calculation Energy Aware Scheduling (EAS) needs to predict the decisions made by SchedUtil. The map_util_freq() exists to do that. There are corner cases where the max allowed frequency might be reduced (due to thermal). SchedUtil as a CPUFreq governor, is aware of that but EAS is not. This patch aims to address it. SchedUtil stores the maximum allowed frequency in 'sugov_policy::next_freq' field. EAS has to predict that value, which is the real used frequency. That value is made after a call to cpufreq_driver_resolve_freq() which clamps to the CPUFreq policy limits. In the existing code EAS is not able to predict that real frequency. This leads to energy estimation errors. To avoid wrong energy estimation in EAS (due to frequency miss prediction) make sure that the step which calculates Performance Domain frequency, is also aware of the allowed CPU capacity. Furthermore, modify map_util_freq() to not extend the frequency value. Instead, use map_util_perf() to extend the util value in both places: SchedUtil and EAS, but for EAS clamp it to max allowed CPU capacity. In the end, we achieve the same desirable behavior for both subsystems and alignment in regards to the real CPU frequency. Signed-off-by: Lukasz Luba <lukasz.luba@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Acked-by: Rafael J. Wysocki <rafael.j.wysocki@intel.com> (For the schedutil part) Link: https://lore.kernel.org/r/20210614191238.23224-1-lukasz.luba@arm.com
2021-06-14 19:12:38 +00:00
* @allowed_cpu_cap : maximum allowed CPU capacity for the @pd, which
* might reflect reduced frequency (due to thermal)
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
*
* This function must be used only for CPU devices. There is no validation,
* i.e. if the EM is a CPU type and has cpumask allocated. It is called from
* the scheduler code quite frequently and that is why there is not checks.
*
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
* Return: the sum of the energy consumed by the CPUs of the domain assuming
* a capacity state satisfying the max utilization of the domain.
*/
static inline unsigned long em_cpu_energy(struct em_perf_domain *pd,
sched/cpufreq: Consider reduced CPU capacity in energy calculation Energy Aware Scheduling (EAS) needs to predict the decisions made by SchedUtil. The map_util_freq() exists to do that. There are corner cases where the max allowed frequency might be reduced (due to thermal). SchedUtil as a CPUFreq governor, is aware of that but EAS is not. This patch aims to address it. SchedUtil stores the maximum allowed frequency in 'sugov_policy::next_freq' field. EAS has to predict that value, which is the real used frequency. That value is made after a call to cpufreq_driver_resolve_freq() which clamps to the CPUFreq policy limits. In the existing code EAS is not able to predict that real frequency. This leads to energy estimation errors. To avoid wrong energy estimation in EAS (due to frequency miss prediction) make sure that the step which calculates Performance Domain frequency, is also aware of the allowed CPU capacity. Furthermore, modify map_util_freq() to not extend the frequency value. Instead, use map_util_perf() to extend the util value in both places: SchedUtil and EAS, but for EAS clamp it to max allowed CPU capacity. In the end, we achieve the same desirable behavior for both subsystems and alignment in regards to the real CPU frequency. Signed-off-by: Lukasz Luba <lukasz.luba@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Acked-by: Rafael J. Wysocki <rafael.j.wysocki@intel.com> (For the schedutil part) Link: https://lore.kernel.org/r/20210614191238.23224-1-lukasz.luba@arm.com
2021-06-14 19:12:38 +00:00
unsigned long max_util, unsigned long sum_util,
unsigned long allowed_cpu_cap)
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
{
struct em_perf_table *em_table;
struct em_perf_state *ps;
int i;
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
WARN_ONCE(!rcu_read_lock_held(), "EM: rcu read lock needed\n");
if (!sum_util)
return 0;
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
/*
* In order to predict the performance state, map the utilization of
* the most utilized CPU of the performance domain to a requested
* performance, like schedutil. Take also into account that the real
* performance might be set lower (due to thermal capping). Thus, clamp
sched/cpufreq: Consider reduced CPU capacity in energy calculation Energy Aware Scheduling (EAS) needs to predict the decisions made by SchedUtil. The map_util_freq() exists to do that. There are corner cases where the max allowed frequency might be reduced (due to thermal). SchedUtil as a CPUFreq governor, is aware of that but EAS is not. This patch aims to address it. SchedUtil stores the maximum allowed frequency in 'sugov_policy::next_freq' field. EAS has to predict that value, which is the real used frequency. That value is made after a call to cpufreq_driver_resolve_freq() which clamps to the CPUFreq policy limits. In the existing code EAS is not able to predict that real frequency. This leads to energy estimation errors. To avoid wrong energy estimation in EAS (due to frequency miss prediction) make sure that the step which calculates Performance Domain frequency, is also aware of the allowed CPU capacity. Furthermore, modify map_util_freq() to not extend the frequency value. Instead, use map_util_perf() to extend the util value in both places: SchedUtil and EAS, but for EAS clamp it to max allowed CPU capacity. In the end, we achieve the same desirable behavior for both subsystems and alignment in regards to the real CPU frequency. Signed-off-by: Lukasz Luba <lukasz.luba@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Acked-by: Rafael J. Wysocki <rafael.j.wysocki@intel.com> (For the schedutil part) Link: https://lore.kernel.org/r/20210614191238.23224-1-lukasz.luba@arm.com
2021-06-14 19:12:38 +00:00
* max utilization to the allowed CPU capacity before calculating
* effective performance.
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
*/
sched/cpufreq: Consider reduced CPU capacity in energy calculation Energy Aware Scheduling (EAS) needs to predict the decisions made by SchedUtil. The map_util_freq() exists to do that. There are corner cases where the max allowed frequency might be reduced (due to thermal). SchedUtil as a CPUFreq governor, is aware of that but EAS is not. This patch aims to address it. SchedUtil stores the maximum allowed frequency in 'sugov_policy::next_freq' field. EAS has to predict that value, which is the real used frequency. That value is made after a call to cpufreq_driver_resolve_freq() which clamps to the CPUFreq policy limits. In the existing code EAS is not able to predict that real frequency. This leads to energy estimation errors. To avoid wrong energy estimation in EAS (due to frequency miss prediction) make sure that the step which calculates Performance Domain frequency, is also aware of the allowed CPU capacity. Furthermore, modify map_util_freq() to not extend the frequency value. Instead, use map_util_perf() to extend the util value in both places: SchedUtil and EAS, but for EAS clamp it to max allowed CPU capacity. In the end, we achieve the same desirable behavior for both subsystems and alignment in regards to the real CPU frequency. Signed-off-by: Lukasz Luba <lukasz.luba@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Acked-by: Rafael J. Wysocki <rafael.j.wysocki@intel.com> (For the schedutil part) Link: https://lore.kernel.org/r/20210614191238.23224-1-lukasz.luba@arm.com
2021-06-14 19:12:38 +00:00
max_util = min(max_util, allowed_cpu_cap);
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
/*
* Find the lowest performance state of the Energy Model above the
* requested performance.
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
*/
em_table = rcu_dereference(pd->em_table);
i = em_pd_get_efficient_state(em_table->state, pd, max_util);
ps = &em_table->state[i];
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
/*
* The performance (capacity) of a CPU in the domain at the performance
* state (ps) can be computed as:
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
*
* ps->freq * scale_cpu
* ps->performance = -------------------- (1)
* cpu_max_freq
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
*
* So, ignoring the costs of idle states (which are not available in
* the EM), the energy consumed by this CPU at that performance state
* is estimated as:
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
*
* ps->power * cpu_util
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
* cpu_nrg = -------------------- (2)
* ps->performance
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
*
* since 'cpu_util / ps->performance' represents its percentage of busy
* time.
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
*
* NOTE: Although the result of this computation actually is in
* units of power, it can be manipulated as an energy value
* over a scheduling period, since it is assumed to be
* constant during that interval.
*
* By injecting (1) in (2), 'cpu_nrg' can be re-expressed as a product
* of two terms:
*
* ps->power * cpu_max_freq
* cpu_nrg = ------------------------ * cpu_util (3)
* ps->freq * scale_cpu
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
*
* The first term is static, and is stored in the em_perf_state struct
* as 'ps->cost'.
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
*
* Since all CPUs of the domain have the same micro-architecture, they
* share the same 'ps->cost', and the same CPU capacity. Hence, the
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
* total energy of the domain (which is the simple sum of the energy of
* all of its CPUs) can be factorized as:
*
* pd_nrg = ps->cost * \Sum cpu_util (4)
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
*/
return ps->cost * sum_util;
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
}
/**
* em_pd_nr_perf_states() - Get the number of performance states of a perf.
* domain
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
* @pd : performance domain for which this must be done
*
* Return: the number of performance states in the performance domain table
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
*/
static inline int em_pd_nr_perf_states(struct em_perf_domain *pd)
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
{
return pd->nr_perf_states;
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
}
/**
* em_perf_state_from_pd() - Get the performance states table of perf.
* domain
* @pd : performance domain for which this must be done
*
* To use this function the rcu_read_lock() should be hold. After the usage
* of the performance states table is finished, the rcu_read_unlock() should
* be called.
*
* Return: the pointer to performance states table of the performance domain
*/
static inline
struct em_perf_state *em_perf_state_from_pd(struct em_perf_domain *pd)
{
return rcu_dereference(pd->em_table)->state;
}
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
#else
struct em_data_callback {};
PM: EM: Add .get_cost() callback The Energy Model (EM) supports devices which report abstract power scale, not only real Watts. The primary goal for EM is to enable the Energy Aware Scheduler (EAS) for a given platform. Some of the platforms might not be able to deliver proper power values. The only information that they might have is the relative efficiency between CPU types. Thus, it makes sense to remove some restrictions in the EM framework and introduce a mechanism which would support those platforms. What is crucial for EAS to operate is the 'cost' field in the EM. The 'cost' is calculated internally in EM framework based on knowledge from 'power' values. The 'cost' values must be strictly increasing. The existing API with its 'power' value size restrictions cannot guarantee that the 'cost' will meet this requirement. Since the platform is missing this detailed information, but has only efficiency details, introduce a new custom callback in the EM framework. The new callback would allow to provide the 'cost' values which reflect efficiency of the CPUs. This would allow to provide EAS information which has different relation than what would be forced by the EM internal formulas calculating 'cost' values. Thanks to this new callback it is possible to create a system view for EAS which has no overlapping performance states across many Performance Domains. Signed-off-by: Lukasz Luba <lukasz.luba@arm.com> Reviewed-by: Ionela Voinescu <ionela.voinescu@arm.com> Signed-off-by: Rafael J. Wysocki <rafael.j.wysocki@intel.com>
2022-03-21 09:57:22 +00:00
#define EM_ADV_DATA_CB(_active_power_cb, _cost_cb) { }
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
#define EM_DATA_CB(_active_power_cb) { }
#define EM_SET_ACTIVE_POWER_CB(em_cb, cb) do { } while (0)
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
static inline
int em_dev_register_perf_domain(struct device *dev, unsigned int nr_states,
const struct em_data_callback *cb,
const cpumask_t *cpus, bool microwatts)
{
return -EINVAL;
}
static inline void em_dev_unregister_perf_domain(struct device *dev)
{
}
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
static inline struct em_perf_domain *em_cpu_get(int cpu)
{
return NULL;
}
static inline struct em_perf_domain *em_pd_get(struct device *dev)
{
return NULL;
}
static inline unsigned long em_cpu_energy(struct em_perf_domain *pd,
sched/cpufreq: Consider reduced CPU capacity in energy calculation Energy Aware Scheduling (EAS) needs to predict the decisions made by SchedUtil. The map_util_freq() exists to do that. There are corner cases where the max allowed frequency might be reduced (due to thermal). SchedUtil as a CPUFreq governor, is aware of that but EAS is not. This patch aims to address it. SchedUtil stores the maximum allowed frequency in 'sugov_policy::next_freq' field. EAS has to predict that value, which is the real used frequency. That value is made after a call to cpufreq_driver_resolve_freq() which clamps to the CPUFreq policy limits. In the existing code EAS is not able to predict that real frequency. This leads to energy estimation errors. To avoid wrong energy estimation in EAS (due to frequency miss prediction) make sure that the step which calculates Performance Domain frequency, is also aware of the allowed CPU capacity. Furthermore, modify map_util_freq() to not extend the frequency value. Instead, use map_util_perf() to extend the util value in both places: SchedUtil and EAS, but for EAS clamp it to max allowed CPU capacity. In the end, we achieve the same desirable behavior for both subsystems and alignment in regards to the real CPU frequency. Signed-off-by: Lukasz Luba <lukasz.luba@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Acked-by: Rafael J. Wysocki <rafael.j.wysocki@intel.com> (For the schedutil part) Link: https://lore.kernel.org/r/20210614191238.23224-1-lukasz.luba@arm.com
2021-06-14 19:12:38 +00:00
unsigned long max_util, unsigned long sum_util,
unsigned long allowed_cpu_cap)
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
{
return 0;
}
static inline int em_pd_nr_perf_states(struct em_perf_domain *pd)
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
{
return 0;
}
static inline
PM: EM: Address RCU-related sparse warnings The usage of __rcu in the Energy Model code is quite inconsistent which causes the following sparse warnings to trigger: kernel/power/energy_model.c:169:15: warning: incorrect type in assignment (different address spaces) kernel/power/energy_model.c:169:15: expected struct em_perf_table [noderef] __rcu *table kernel/power/energy_model.c:169:15: got struct em_perf_table * kernel/power/energy_model.c:171:9: warning: incorrect type in argument 1 (different address spaces) kernel/power/energy_model.c:171:9: expected struct callback_head *head kernel/power/energy_model.c:171:9: got struct callback_head [noderef] __rcu * kernel/power/energy_model.c:171:9: warning: cast removes address space '__rcu' of expression kernel/power/energy_model.c:182:19: warning: incorrect type in argument 1 (different address spaces) kernel/power/energy_model.c:182:19: expected struct kref *kref kernel/power/energy_model.c:182:19: got struct kref [noderef] __rcu * kernel/power/energy_model.c:200:15: warning: incorrect type in assignment (different address spaces) kernel/power/energy_model.c:200:15: expected struct em_perf_table [noderef] __rcu *table kernel/power/energy_model.c:200:15: got void *[assigned] _res kernel/power/energy_model.c:204:20: warning: incorrect type in argument 1 (different address spaces) kernel/power/energy_model.c:204:20: expected struct kref *kref kernel/power/energy_model.c:204:20: got struct kref [noderef] __rcu * kernel/power/energy_model.c:320:19: warning: incorrect type in argument 1 (different address spaces) kernel/power/energy_model.c:320:19: expected struct kref *kref kernel/power/energy_model.c:320:19: got struct kref [noderef] __rcu * kernel/power/energy_model.c:325:45: warning: incorrect type in argument 2 (different address spaces) kernel/power/energy_model.c:325:45: expected struct em_perf_state *table kernel/power/energy_model.c:325:45: got struct em_perf_state [noderef] __rcu * kernel/power/energy_model.c:425:45: warning: incorrect type in argument 3 (different address spaces) kernel/power/energy_model.c:425:45: expected struct em_perf_state *table kernel/power/energy_model.c:425:45: got struct em_perf_state [noderef] __rcu * kernel/power/energy_model.c:442:15: warning: incorrect type in argument 1 (different address spaces) kernel/power/energy_model.c:442:15: expected void const *objp kernel/power/energy_model.c:442:15: got struct em_perf_table [noderef] __rcu *[assigned] em_table kernel/power/energy_model.c:626:55: warning: incorrect type in argument 2 (different address spaces) kernel/power/energy_model.c:626:55: expected struct em_perf_state *table kernel/power/energy_model.c:626:55: got struct em_perf_state [noderef] __rcu * kernel/power/energy_model.c:681:16: warning: incorrect type in assignment (different address spaces) kernel/power/energy_model.c:681:16: expected struct em_perf_state *new_ps kernel/power/energy_model.c:681:16: got struct em_perf_state [noderef] __rcu * kernel/power/energy_model.c:699:37: warning: incorrect type in argument 2 (different address spaces) kernel/power/energy_model.c:699:37: expected struct em_perf_state *table kernel/power/energy_model.c:699:37: got struct em_perf_state [noderef] __rcu * kernel/power/energy_model.c:733:38: warning: incorrect type in argument 3 (different address spaces) kernel/power/energy_model.c:733:38: expected struct em_perf_state *table kernel/power/energy_model.c:733:38: got struct em_perf_state [noderef] __rcu * kernel/power/energy_model.c:855:53: warning: dereference of noderef expression kernel/power/energy_model.c:864:32: warning: dereference of noderef expression This is because the __rcu annotation for sparse is only applicable to pointers that need rcu_dereference() or equivalent for protection, which basically means pointers assigned with rcu_assign_pointer(). Make all of the above sparse warnings go away by cleaning up the usage of __rcu and using rcu_dereference_protected() where applicable. Cc: All applicable <stable@vger.kernel.org> Signed-off-by: Rafael J. Wysocki <rafael.j.wysocki@intel.com> Reviewed-by: Lukasz Luba <lukasz.luba@arm.com> Link: https://patch.msgid.link/5885405.DvuYhMxLoT@rjwysocki.net
2025-03-06 16:49:20 +00:00
struct em_perf_table *em_table_alloc(struct em_perf_domain *pd)
{
return NULL;
}
PM: EM: Address RCU-related sparse warnings The usage of __rcu in the Energy Model code is quite inconsistent which causes the following sparse warnings to trigger: kernel/power/energy_model.c:169:15: warning: incorrect type in assignment (different address spaces) kernel/power/energy_model.c:169:15: expected struct em_perf_table [noderef] __rcu *table kernel/power/energy_model.c:169:15: got struct em_perf_table * kernel/power/energy_model.c:171:9: warning: incorrect type in argument 1 (different address spaces) kernel/power/energy_model.c:171:9: expected struct callback_head *head kernel/power/energy_model.c:171:9: got struct callback_head [noderef] __rcu * kernel/power/energy_model.c:171:9: warning: cast removes address space '__rcu' of expression kernel/power/energy_model.c:182:19: warning: incorrect type in argument 1 (different address spaces) kernel/power/energy_model.c:182:19: expected struct kref *kref kernel/power/energy_model.c:182:19: got struct kref [noderef] __rcu * kernel/power/energy_model.c:200:15: warning: incorrect type in assignment (different address spaces) kernel/power/energy_model.c:200:15: expected struct em_perf_table [noderef] __rcu *table kernel/power/energy_model.c:200:15: got void *[assigned] _res kernel/power/energy_model.c:204:20: warning: incorrect type in argument 1 (different address spaces) kernel/power/energy_model.c:204:20: expected struct kref *kref kernel/power/energy_model.c:204:20: got struct kref [noderef] __rcu * kernel/power/energy_model.c:320:19: warning: incorrect type in argument 1 (different address spaces) kernel/power/energy_model.c:320:19: expected struct kref *kref kernel/power/energy_model.c:320:19: got struct kref [noderef] __rcu * kernel/power/energy_model.c:325:45: warning: incorrect type in argument 2 (different address spaces) kernel/power/energy_model.c:325:45: expected struct em_perf_state *table kernel/power/energy_model.c:325:45: got struct em_perf_state [noderef] __rcu * kernel/power/energy_model.c:425:45: warning: incorrect type in argument 3 (different address spaces) kernel/power/energy_model.c:425:45: expected struct em_perf_state *table kernel/power/energy_model.c:425:45: got struct em_perf_state [noderef] __rcu * kernel/power/energy_model.c:442:15: warning: incorrect type in argument 1 (different address spaces) kernel/power/energy_model.c:442:15: expected void const *objp kernel/power/energy_model.c:442:15: got struct em_perf_table [noderef] __rcu *[assigned] em_table kernel/power/energy_model.c:626:55: warning: incorrect type in argument 2 (different address spaces) kernel/power/energy_model.c:626:55: expected struct em_perf_state *table kernel/power/energy_model.c:626:55: got struct em_perf_state [noderef] __rcu * kernel/power/energy_model.c:681:16: warning: incorrect type in assignment (different address spaces) kernel/power/energy_model.c:681:16: expected struct em_perf_state *new_ps kernel/power/energy_model.c:681:16: got struct em_perf_state [noderef] __rcu * kernel/power/energy_model.c:699:37: warning: incorrect type in argument 2 (different address spaces) kernel/power/energy_model.c:699:37: expected struct em_perf_state *table kernel/power/energy_model.c:699:37: got struct em_perf_state [noderef] __rcu * kernel/power/energy_model.c:733:38: warning: incorrect type in argument 3 (different address spaces) kernel/power/energy_model.c:733:38: expected struct em_perf_state *table kernel/power/energy_model.c:733:38: got struct em_perf_state [noderef] __rcu * kernel/power/energy_model.c:855:53: warning: dereference of noderef expression kernel/power/energy_model.c:864:32: warning: dereference of noderef expression This is because the __rcu annotation for sparse is only applicable to pointers that need rcu_dereference() or equivalent for protection, which basically means pointers assigned with rcu_assign_pointer(). Make all of the above sparse warnings go away by cleaning up the usage of __rcu and using rcu_dereference_protected() where applicable. Cc: All applicable <stable@vger.kernel.org> Signed-off-by: Rafael J. Wysocki <rafael.j.wysocki@intel.com> Reviewed-by: Lukasz Luba <lukasz.luba@arm.com> Link: https://patch.msgid.link/5885405.DvuYhMxLoT@rjwysocki.net
2025-03-06 16:49:20 +00:00
static inline void em_table_free(struct em_perf_table *table) {}
static inline
int em_dev_update_perf_domain(struct device *dev,
PM: EM: Address RCU-related sparse warnings The usage of __rcu in the Energy Model code is quite inconsistent which causes the following sparse warnings to trigger: kernel/power/energy_model.c:169:15: warning: incorrect type in assignment (different address spaces) kernel/power/energy_model.c:169:15: expected struct em_perf_table [noderef] __rcu *table kernel/power/energy_model.c:169:15: got struct em_perf_table * kernel/power/energy_model.c:171:9: warning: incorrect type in argument 1 (different address spaces) kernel/power/energy_model.c:171:9: expected struct callback_head *head kernel/power/energy_model.c:171:9: got struct callback_head [noderef] __rcu * kernel/power/energy_model.c:171:9: warning: cast removes address space '__rcu' of expression kernel/power/energy_model.c:182:19: warning: incorrect type in argument 1 (different address spaces) kernel/power/energy_model.c:182:19: expected struct kref *kref kernel/power/energy_model.c:182:19: got struct kref [noderef] __rcu * kernel/power/energy_model.c:200:15: warning: incorrect type in assignment (different address spaces) kernel/power/energy_model.c:200:15: expected struct em_perf_table [noderef] __rcu *table kernel/power/energy_model.c:200:15: got void *[assigned] _res kernel/power/energy_model.c:204:20: warning: incorrect type in argument 1 (different address spaces) kernel/power/energy_model.c:204:20: expected struct kref *kref kernel/power/energy_model.c:204:20: got struct kref [noderef] __rcu * kernel/power/energy_model.c:320:19: warning: incorrect type in argument 1 (different address spaces) kernel/power/energy_model.c:320:19: expected struct kref *kref kernel/power/energy_model.c:320:19: got struct kref [noderef] __rcu * kernel/power/energy_model.c:325:45: warning: incorrect type in argument 2 (different address spaces) kernel/power/energy_model.c:325:45: expected struct em_perf_state *table kernel/power/energy_model.c:325:45: got struct em_perf_state [noderef] __rcu * kernel/power/energy_model.c:425:45: warning: incorrect type in argument 3 (different address spaces) kernel/power/energy_model.c:425:45: expected struct em_perf_state *table kernel/power/energy_model.c:425:45: got struct em_perf_state [noderef] __rcu * kernel/power/energy_model.c:442:15: warning: incorrect type in argument 1 (different address spaces) kernel/power/energy_model.c:442:15: expected void const *objp kernel/power/energy_model.c:442:15: got struct em_perf_table [noderef] __rcu *[assigned] em_table kernel/power/energy_model.c:626:55: warning: incorrect type in argument 2 (different address spaces) kernel/power/energy_model.c:626:55: expected struct em_perf_state *table kernel/power/energy_model.c:626:55: got struct em_perf_state [noderef] __rcu * kernel/power/energy_model.c:681:16: warning: incorrect type in assignment (different address spaces) kernel/power/energy_model.c:681:16: expected struct em_perf_state *new_ps kernel/power/energy_model.c:681:16: got struct em_perf_state [noderef] __rcu * kernel/power/energy_model.c:699:37: warning: incorrect type in argument 2 (different address spaces) kernel/power/energy_model.c:699:37: expected struct em_perf_state *table kernel/power/energy_model.c:699:37: got struct em_perf_state [noderef] __rcu * kernel/power/energy_model.c:733:38: warning: incorrect type in argument 3 (different address spaces) kernel/power/energy_model.c:733:38: expected struct em_perf_state *table kernel/power/energy_model.c:733:38: got struct em_perf_state [noderef] __rcu * kernel/power/energy_model.c:855:53: warning: dereference of noderef expression kernel/power/energy_model.c:864:32: warning: dereference of noderef expression This is because the __rcu annotation for sparse is only applicable to pointers that need rcu_dereference() or equivalent for protection, which basically means pointers assigned with rcu_assign_pointer(). Make all of the above sparse warnings go away by cleaning up the usage of __rcu and using rcu_dereference_protected() where applicable. Cc: All applicable <stable@vger.kernel.org> Signed-off-by: Rafael J. Wysocki <rafael.j.wysocki@intel.com> Reviewed-by: Lukasz Luba <lukasz.luba@arm.com> Link: https://patch.msgid.link/5885405.DvuYhMxLoT@rjwysocki.net
2025-03-06 16:49:20 +00:00
struct em_perf_table *new_table)
{
return -EINVAL;
}
static inline
struct em_perf_state *em_perf_state_from_pd(struct em_perf_domain *pd)
{
return NULL;
}
static inline
int em_dev_compute_costs(struct device *dev, struct em_perf_state *table,
int nr_states)
{
return -EINVAL;
}
static inline int em_dev_update_chip_binning(struct device *dev)
{
return -EINVAL;
}
static inline
int em_update_performance_limits(struct em_perf_domain *pd,
unsigned long freq_min_khz, unsigned long freq_max_khz)
{
return -EINVAL;
}
static inline void em_adjust_cpu_capacity(unsigned int cpu) {}
static inline void em_rebuild_sched_domains(void) {}
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 09:56:16 +00:00
#endif
#endif