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 12:56:16 +03:00
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/* SPDX-License-Identifier: GPL-2.0 */
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#ifndef _LINUX_ENERGY_MODEL_H
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#define _LINUX_ENERGY_MODEL_H
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#include <linux/cpumask.h>
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#include <linux/jump_label.h>
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#include <linux/kobject.h>
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#include <linux/rcupdate.h>
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#include <linux/sched/cpufreq.h>
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#include <linux/sched/topology.h>
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#include <linux/types.h>
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/**
|
2020-05-27 12:58:47 +03:00
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|
* em_perf_state - Performance state 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 12:56:16 +03:00
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* @frequency: The CPU frequency in KHz, for consistency with CPUFreq
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* @power: The power consumed by 1 CPU at this level, in milli-watts
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* @cost: The cost coefficient associated with this level, used during
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* energy calculation. Equal to: power * max_frequency / frequency
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*/
|
2020-05-27 12:58:47 +03:00
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struct em_perf_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 12:56:16 +03:00
|
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unsigned long frequency;
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unsigned long power;
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unsigned long cost;
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};
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/**
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* em_perf_domain - Performance domain
|
2020-05-27 12:58:47 +03:00
|
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* @table: List of performance states, in ascending order
|
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* @nr_perf_states: Number of performance 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 12:56:16 +03:00
|
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* @cpus: Cpumask covering the CPUs of the domain
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*
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* A "performance domain" represents a group of CPUs whose performance is
|
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* scaled together. All CPUs of a performance domain must have the same
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* micro-architecture. Performance domains often have a 1-to-1 mapping with
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* CPUFreq policies.
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*/
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struct em_perf_domain {
|
2020-05-27 12:58:47 +03:00
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struct em_perf_state *table;
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int nr_perf_states;
|
2020-03-24 01:23:01 +03:00
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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 12:56:16 +03:00
|
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};
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|
2020-05-27 12:58:47 +03:00
|
|
|
#define em_span_cpus(em) (to_cpumask((em)->cpus))
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|
2019-10-30 18:14:49 +03:00
|
|
|
#ifdef CONFIG_ENERGY_MODEL
|
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 12:56:16 +03:00
|
|
|
#define EM_CPU_MAX_POWER 0xFFFF
|
|
|
|
|
|
|
|
struct em_data_callback {
|
|
|
|
/**
|
2020-05-27 12:58:47 +03:00
|
|
|
* active_power() - Provide power at the next performance state of
|
|
|
|
* a CPU
|
|
|
|
* @power : Active power at the performance state in mW
|
|
|
|
* (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 12:56:16 +03:00
|
|
|
* @cpu : CPU for which we do this operation
|
|
|
|
*
|
2020-05-27 12:58:47 +03:00
|
|
|
* active_power() must find the lowest performance state of 'cpu' 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 12:56:16 +03:00
|
|
|
* 'freq' and update 'power' and 'freq' to the matching active power
|
|
|
|
* and frequency.
|
|
|
|
*
|
|
|
|
* The power is the one of a single CPU in the domain, expressed in
|
|
|
|
* milli-watts. It is expected to fit in the [0, EM_CPU_MAX_POWER]
|
|
|
|
* range.
|
|
|
|
*
|
|
|
|
* Return 0 on success.
|
|
|
|
*/
|
|
|
|
int (*active_power)(unsigned long *power, unsigned long *freq, int cpu);
|
|
|
|
};
|
|
|
|
#define EM_DATA_CB(_active_power_cb) { .active_power = &_active_power_cb }
|
|
|
|
|
|
|
|
struct em_perf_domain *em_cpu_get(int cpu);
|
|
|
|
int em_register_perf_domain(cpumask_t *span, unsigned int nr_states,
|
|
|
|
struct em_data_callback *cb);
|
|
|
|
|
|
|
|
/**
|
|
|
|
* em_pd_energy() - Estimates the energy consumed by the CPUs of a perf. domain
|
|
|
|
* @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
|
|
|
|
*
|
|
|
|
* 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_pd_energy(struct em_perf_domain *pd,
|
|
|
|
unsigned long max_util, unsigned long sum_util)
|
|
|
|
{
|
|
|
|
unsigned long freq, scale_cpu;
|
2020-05-27 12:58:47 +03:00
|
|
|
struct em_perf_state *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 12:56:16 +03:00
|
|
|
int i, cpu;
|
|
|
|
|
|
|
|
/*
|
2020-05-27 12:58:47 +03:00
|
|
|
* In order to predict the performance state, map the utilization of
|
|
|
|
* the most utilized CPU of the performance domain to a requested
|
|
|
|
* frequency, like schedutil.
|
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 12:56:16 +03:00
|
|
|
*/
|
|
|
|
cpu = cpumask_first(to_cpumask(pd->cpus));
|
2019-06-17 18:00:17 +03:00
|
|
|
scale_cpu = arch_scale_cpu_capacity(cpu);
|
2020-05-27 12:58:47 +03:00
|
|
|
ps = &pd->table[pd->nr_perf_states - 1];
|
|
|
|
freq = map_util_freq(max_util, ps->frequency, 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 12:56:16 +03:00
|
|
|
|
|
|
|
/*
|
2020-05-27 12:58:47 +03:00
|
|
|
* Find the lowest performance state of the Energy Model above 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 12:56:16 +03:00
|
|
|
* requested frequency.
|
|
|
|
*/
|
2020-05-27 12:58:47 +03:00
|
|
|
for (i = 0; i < pd->nr_perf_states; i++) {
|
|
|
|
ps = &pd->table[i];
|
|
|
|
if (ps->frequency >= 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 12:56:16 +03:00
|
|
|
break;
|
|
|
|
}
|
|
|
|
|
|
|
|
/*
|
2020-05-27 12:58:47 +03:00
|
|
|
* The capacity of a CPU in the domain at the performance state (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 12:56:16 +03:00
|
|
|
* can be computed as:
|
|
|
|
*
|
2020-05-27 12:58:47 +03:00
|
|
|
* ps->freq * scale_cpu
|
|
|
|
* ps->cap = -------------------- (1)
|
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 12:56:16 +03:00
|
|
|
* cpu_max_freq
|
|
|
|
*
|
|
|
|
* So, ignoring the costs of idle states (which are not available in
|
2020-05-27 12:58:47 +03:00
|
|
|
* 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 12:56:16 +03:00
|
|
|
*
|
2020-05-27 12:58:47 +03:00
|
|
|
* 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 12:56:16 +03:00
|
|
|
* cpu_nrg = -------------------- (2)
|
2020-05-27 12:58:47 +03:00
|
|
|
* ps->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 12:56:16 +03:00
|
|
|
*
|
2020-05-27 12:58:47 +03:00
|
|
|
* since 'cpu_util / ps->cap' 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 12:56:16 +03:00
|
|
|
*
|
|
|
|
* 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:
|
|
|
|
*
|
2020-05-27 12:58:47 +03:00
|
|
|
* ps->power * cpu_max_freq 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 12:56:16 +03:00
|
|
|
* cpu_nrg = ------------------------ * --------- (3)
|
2020-05-27 12:58:47 +03:00
|
|
|
* 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 12:56:16 +03:00
|
|
|
*
|
2020-05-27 12:58:47 +03:00
|
|
|
* 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 12:56:16 +03:00
|
|
|
*
|
|
|
|
* Since all CPUs of the domain have the same micro-architecture, they
|
2020-05-27 12:58:47 +03:00
|
|
|
* 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 12:56:16 +03:00
|
|
|
* total energy of the domain (which is the simple sum of the energy of
|
|
|
|
* all of its CPUs) can be factorized as:
|
|
|
|
*
|
2020-05-27 12:58:47 +03:00
|
|
|
* ps->cost * \Sum 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 12:56:16 +03:00
|
|
|
* pd_nrg = ------------------------ (4)
|
|
|
|
* scale_cpu
|
|
|
|
*/
|
2020-05-27 12:58:47 +03:00
|
|
|
return ps->cost * sum_util / 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 12:56:16 +03:00
|
|
|
}
|
|
|
|
|
|
|
|
/**
|
2020-05-27 12:58:47 +03:00
|
|
|
* 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 12:56:16 +03:00
|
|
|
* @pd : performance domain for which this must be done
|
|
|
|
*
|
2020-05-27 12:58:47 +03:00
|
|
|
* 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 12:56:16 +03:00
|
|
|
*/
|
2020-05-27 12:58:47 +03:00
|
|
|
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 12:56:16 +03:00
|
|
|
{
|
2020-05-27 12:58:47 +03:00
|
|
|
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 12:56:16 +03:00
|
|
|
}
|
|
|
|
|
|
|
|
#else
|
|
|
|
struct em_data_callback {};
|
|
|
|
#define EM_DATA_CB(_active_power_cb) { }
|
|
|
|
|
|
|
|
static inline int em_register_perf_domain(cpumask_t *span,
|
|
|
|
unsigned int nr_states, struct em_data_callback *cb)
|
|
|
|
{
|
|
|
|
return -EINVAL;
|
|
|
|
}
|
|
|
|
static inline struct em_perf_domain *em_cpu_get(int cpu)
|
|
|
|
{
|
|
|
|
return NULL;
|
|
|
|
}
|
|
|
|
static inline unsigned long em_pd_energy(struct em_perf_domain *pd,
|
|
|
|
unsigned long max_util, unsigned long sum_util)
|
|
|
|
{
|
|
|
|
return 0;
|
|
|
|
}
|
2020-05-27 12:58:47 +03:00
|
|
|
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 12:56:16 +03:00
|
|
|
{
|
|
|
|
return 0;
|
|
|
|
}
|
|
|
|
#endif
|
|
|
|
|
|
|
|
#endif
|