linux-brain/kernel/power/energy_model.c

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PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 18:56:16 +09:00
// SPDX-License-Identifier: GPL-2.0
/*
* Energy Model of CPUs
*
* Copyright (c) 2018, Arm ltd.
* Written by: Quentin Perret, Arm ltd.
*/
#define pr_fmt(fmt) "energy_model: " fmt
#include <linux/cpu.h>
#include <linux/cpumask.h>
PM / EM: Expose the Energy Model in debugfs The recently introduced Energy Model (EM) framework manages power cost tables of CPUs. These tables are currently only visible from kernel space. However, in order to debug the behaviour of subsystems that use the EM (EAS for example), it is often required to know what the power costs are from userspace. For this reason, introduce under /sys/kernel/debug/energy_model a set of directories representing the performance domains of the system. Each performance domain contains a set of sub-directories representing the different capacity states (cs) and their attributes, as well as a file exposing the related CPUs. The resulting hierarchy is as follows on Arm juno r0 for example: /sys/kernel/debug/energy_model ├── pd0 │   ├── cpus │   ├── cs:450000 │   │   ├── cost │   │   ├── frequency │   │   └── power │   ├── cs:575000 │   │   ├── cost │   │   ├── frequency │   │   └── power │   ├── cs:700000 │   │   ├── cost │   │   ├── frequency │   │   └── power │   ├── cs:775000 │   │   ├── cost │   │   ├── frequency │   │   └── power │   └── cs:850000 │   ├── cost │   ├── frequency │   └── power └── pd1 ├── cpus ├── cs:1100000 │   ├── cost │   ├── frequency │   └── power ├── cs:450000 │   ├── cost │   ├── frequency │   └── power ├── cs:625000 │   ├── cost │   ├── frequency │   └── power ├── cs:800000 │   ├── cost │   ├── frequency │   └── power └── cs:950000 ├── cost ├── frequency └── power Signed-off-by: Quentin Perret <quentin.perret@arm.com> Reviewed-by: Greg Kroah-Hartman <gregkh@linuxfoundation.org> Signed-off-by: Rafael J. Wysocki <rafael.j.wysocki@intel.com>
2019-01-23 01:42:47 +09:00
#include <linux/debugfs.h>
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 18:56:16 +09:00
#include <linux/energy_model.h>
#include <linux/sched/topology.h>
#include <linux/slab.h>
/* Mapping of each CPU to the performance domain to which it belongs. */
static DEFINE_PER_CPU(struct em_perf_domain *, em_data);
/*
* Mutex serializing the registrations of performance domains and letting
* callbacks defined by drivers sleep.
*/
static DEFINE_MUTEX(em_pd_mutex);
PM / EM: Expose the Energy Model in debugfs The recently introduced Energy Model (EM) framework manages power cost tables of CPUs. These tables are currently only visible from kernel space. However, in order to debug the behaviour of subsystems that use the EM (EAS for example), it is often required to know what the power costs are from userspace. For this reason, introduce under /sys/kernel/debug/energy_model a set of directories representing the performance domains of the system. Each performance domain contains a set of sub-directories representing the different capacity states (cs) and their attributes, as well as a file exposing the related CPUs. The resulting hierarchy is as follows on Arm juno r0 for example: /sys/kernel/debug/energy_model ├── pd0 │   ├── cpus │   ├── cs:450000 │   │   ├── cost │   │   ├── frequency │   │   └── power │   ├── cs:575000 │   │   ├── cost │   │   ├── frequency │   │   └── power │   ├── cs:700000 │   │   ├── cost │   │   ├── frequency │   │   └── power │   ├── cs:775000 │   │   ├── cost │   │   ├── frequency │   │   └── power │   └── cs:850000 │   ├── cost │   ├── frequency │   └── power └── pd1 ├── cpus ├── cs:1100000 │   ├── cost │   ├── frequency │   └── power ├── cs:450000 │   ├── cost │   ├── frequency │   └── power ├── cs:625000 │   ├── cost │   ├── frequency │   └── power ├── cs:800000 │   ├── cost │   ├── frequency │   └── power └── cs:950000 ├── cost ├── frequency └── power Signed-off-by: Quentin Perret <quentin.perret@arm.com> Reviewed-by: Greg Kroah-Hartman <gregkh@linuxfoundation.org> Signed-off-by: Rafael J. Wysocki <rafael.j.wysocki@intel.com>
2019-01-23 01:42:47 +09:00
#ifdef CONFIG_DEBUG_FS
static struct dentry *rootdir;
static void em_debug_create_cs(struct em_cap_state *cs, struct dentry *pd)
{
struct dentry *d;
char name[24];
snprintf(name, sizeof(name), "cs:%lu", cs->frequency);
/* Create per-cs directory */
d = debugfs_create_dir(name, pd);
debugfs_create_ulong("frequency", 0444, d, &cs->frequency);
debugfs_create_ulong("power", 0444, d, &cs->power);
debugfs_create_ulong("cost", 0444, d, &cs->cost);
}
static int em_debug_cpus_show(struct seq_file *s, void *unused)
{
seq_printf(s, "%*pbl\n", cpumask_pr_args(to_cpumask(s->private)));
return 0;
}
DEFINE_SHOW_ATTRIBUTE(em_debug_cpus);
static void em_debug_create_pd(struct em_perf_domain *pd, int cpu)
{
struct dentry *d;
char name[8];
int i;
snprintf(name, sizeof(name), "pd%d", cpu);
/* Create the directory of the performance domain */
d = debugfs_create_dir(name, rootdir);
debugfs_create_file("cpus", 0444, d, pd->cpus, &em_debug_cpus_fops);
/* Create a sub-directory for each capacity state */
for (i = 0; i < pd->nr_cap_states; i++)
em_debug_create_cs(&pd->table[i], d);
}
static int __init em_debug_init(void)
{
/* Create /sys/kernel/debug/energy_model directory */
rootdir = debugfs_create_dir("energy_model", NULL);
return 0;
}
fs_initcall(em_debug_init);
PM / EM: Expose the Energy Model in debugfs The recently introduced Energy Model (EM) framework manages power cost tables of CPUs. These tables are currently only visible from kernel space. However, in order to debug the behaviour of subsystems that use the EM (EAS for example), it is often required to know what the power costs are from userspace. For this reason, introduce under /sys/kernel/debug/energy_model a set of directories representing the performance domains of the system. Each performance domain contains a set of sub-directories representing the different capacity states (cs) and their attributes, as well as a file exposing the related CPUs. The resulting hierarchy is as follows on Arm juno r0 for example: /sys/kernel/debug/energy_model ├── pd0 │   ├── cpus │   ├── cs:450000 │   │   ├── cost │   │   ├── frequency │   │   └── power │   ├── cs:575000 │   │   ├── cost │   │   ├── frequency │   │   └── power │   ├── cs:700000 │   │   ├── cost │   │   ├── frequency │   │   └── power │   ├── cs:775000 │   │   ├── cost │   │   ├── frequency │   │   └── power │   └── cs:850000 │   ├── cost │   ├── frequency │   └── power └── pd1 ├── cpus ├── cs:1100000 │   ├── cost │   ├── frequency │   └── power ├── cs:450000 │   ├── cost │   ├── frequency │   └── power ├── cs:625000 │   ├── cost │   ├── frequency │   └── power ├── cs:800000 │   ├── cost │   ├── frequency │   └── power └── cs:950000 ├── cost ├── frequency └── power Signed-off-by: Quentin Perret <quentin.perret@arm.com> Reviewed-by: Greg Kroah-Hartman <gregkh@linuxfoundation.org> Signed-off-by: Rafael J. Wysocki <rafael.j.wysocki@intel.com>
2019-01-23 01:42:47 +09:00
#else /* CONFIG_DEBUG_FS */
static void em_debug_create_pd(struct em_perf_domain *pd, int cpu) {}
#endif
PM: Introduce an Energy Model management framework Several subsystems in the kernel (task scheduler and/or thermal at the time of writing) can benefit from knowing about the energy consumed by CPUs. Yet, this information can come from different sources (DT or firmware for example), in different formats, hence making it hard to exploit without a standard API. As an attempt to address this, introduce a centralized Energy Model (EM) management framework which aggregates the power values provided by drivers into a table for each performance domain in the system. The power cost tables are made available to interested clients (e.g. task scheduler or thermal) via platform-agnostic APIs. The overall design is represented by the diagram below (focused on Arm-related drivers as an example, but applicable to any architecture): +---------------+ +-----------------+ +-------------+ | Thermal (IPA) | | Scheduler (EAS) | | Other | +---------------+ +-----------------+ +-------------+ | | em_pd_energy() | | | em_cpu_get() | +-----------+ | +--------+ | | | v v v +---------------------+ | | | Energy Model | | | | Framework | | | +---------------------+ ^ ^ ^ | | | em_register_perf_domain() +----------+ | +---------+ | | | +---------------+ +---------------+ +--------------+ | cpufreq-dt | | arm_scmi | | Other | +---------------+ +---------------+ +--------------+ ^ ^ ^ | | | +--------------+ +---------------+ +--------------+ | Device Tree | | Firmware | | ? | +--------------+ +---------------+ +--------------+ Drivers (typically, but not limited to, CPUFreq drivers) can register data in the EM framework using the em_register_perf_domain() API. The calling driver must provide a callback function with a standardized signature that will be used by the EM framework to build the power cost tables of the performance domain. This design should offer a lot of flexibility to calling drivers which are free of reading information from any location and to use any technique to compute power costs. Moreover, the capacity states registered by drivers in the EM framework are not required to match real performance states of the target. This is particularly important on targets where the performance states are not known by the OS. The power cost coefficients managed by the EM framework are specified in milli-watts. Although the two potential users of those coefficients (IPA and EAS) only need relative correctness, IPA specifically needs to compare the power of CPUs with the power of other components (GPUs, for example), which are still expressed in absolute terms in their respective subsystems. Hence, specifying the power of CPUs in milli-watts should help transitioning IPA to using the EM framework without introducing new problems by keeping units comparable across sub-systems. On the longer term, the EM of other devices than CPUs could also be managed by the EM framework, which would enable to remove the absolute unit. However, this is not absolutely required as a first step, so this extension of the EM framework is left for later. On the client side, the EM framework offers APIs to access the power cost tables of a CPU (em_cpu_get()), and to estimate the energy consumed by the CPUs of a performance domain (em_pd_energy()). Clients such as the task scheduler can then use these APIs to access the shared data structures holding the Energy Model of CPUs. Signed-off-by: Quentin Perret <quentin.perret@arm.com> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Mike Galbraith <efault@gmx.de> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rafael J. Wysocki <rjw@rjwysocki.net> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: adharmap@codeaurora.org Cc: chris.redpath@arm.com Cc: currojerez@riseup.net Cc: dietmar.eggemann@arm.com Cc: edubezval@gmail.com Cc: gregkh@linuxfoundation.org Cc: javi.merino@kernel.org Cc: joel@joelfernandes.org Cc: juri.lelli@redhat.com Cc: morten.rasmussen@arm.com Cc: patrick.bellasi@arm.com Cc: pkondeti@codeaurora.org Cc: skannan@codeaurora.org Cc: smuckle@google.com Cc: srinivas.pandruvada@linux.intel.com Cc: thara.gopinath@linaro.org Cc: tkjos@google.com Cc: valentin.schneider@arm.com Cc: vincent.guittot@linaro.org Cc: viresh.kumar@linaro.org Link: https://lkml.kernel.org/r/20181203095628.11858-4-quentin.perret@arm.com Signed-off-by: Ingo Molnar <mingo@kernel.org>
2018-12-03 18:56:16 +09:00
static struct em_perf_domain *em_create_pd(cpumask_t *span, int nr_states,
struct em_data_callback *cb)
{
unsigned long opp_eff, prev_opp_eff = ULONG_MAX;
unsigned long power, freq, prev_freq = 0;
int i, ret, cpu = cpumask_first(span);
struct em_cap_state *table;
struct em_perf_domain *pd;
u64 fmax;
if (!cb->active_power)
return NULL;
pd = kzalloc(sizeof(*pd) + cpumask_size(), GFP_KERNEL);
if (!pd)
return NULL;
table = kcalloc(nr_states, sizeof(*table), GFP_KERNEL);
if (!table)
goto free_pd;
/* Build the list of capacity states for this performance domain */
for (i = 0, freq = 0; i < nr_states; i++, freq++) {
/*
* active_power() is a driver callback which ceils 'freq' to
* lowest capacity state of 'cpu' above 'freq' and updates
* 'power' and 'freq' accordingly.
*/
ret = cb->active_power(&power, &freq, cpu);
if (ret) {
pr_err("pd%d: invalid cap. state: %d\n", cpu, ret);
goto free_cs_table;
}
/*
* We expect the driver callback to increase the frequency for
* higher capacity states.
*/
if (freq <= prev_freq) {
pr_err("pd%d: non-increasing freq: %lu\n", cpu, freq);
goto free_cs_table;
}
/*
* The power returned by active_state() is expected to be
* positive, in milli-watts and to fit into 16 bits.
*/
if (!power || power > EM_CPU_MAX_POWER) {
pr_err("pd%d: invalid power: %lu\n", cpu, power);
goto free_cs_table;
}
table[i].power = power;
table[i].frequency = prev_freq = freq;
/*
* The hertz/watts efficiency ratio should decrease as the
* frequency grows on sane platforms. But this isn't always
* true in practice so warn the user if a higher OPP is more
* power efficient than a lower one.
*/
opp_eff = freq / power;
if (opp_eff >= prev_opp_eff)
pr_warn("pd%d: hertz/watts ratio non-monotonically decreasing: em_cap_state %d >= em_cap_state%d\n",
cpu, i, i - 1);
prev_opp_eff = opp_eff;
}
/* Compute the cost of each capacity_state. */
fmax = (u64) table[nr_states - 1].frequency;
for (i = 0; i < nr_states; i++) {
PM: EM: Increase energy calculation precision [ Upstream commit 7fcc17d0cb12938d2b3507973a6f93fc9ed2c7a1 ] The Energy Model (EM) provides useful information about device power in each performance state to other subsystems like: Energy Aware Scheduler (EAS). The energy calculation in EAS does arithmetic operation based on the EM em_cpu_energy(). Current implementation of that function uses em_perf_state::cost as a pre-computed cost coefficient equal to: cost = power * max_frequency / frequency. The 'power' is expressed in milli-Watts (or in abstract scale). There are corner cases when the EAS energy calculation for two Performance Domains (PDs) return the same value. The EAS compares these values to choose smaller one. It might happen that this values are equal due to rounding error. In such scenario, we need better resolution, e.g. 1000 times better. To provide this possibility increase the resolution in the em_perf_state::cost for 64-bit architectures. The cost of increasing resolution on 32-bit is pretty high (64-bit division) and is not justified since there are no new 32bit big.LITTLE EAS systems expected which would benefit from this higher resolution. This patch allows to avoid the rounding to milli-Watt errors, which might occur in EAS energy estimation for each PD. The rounding error is common for small tasks which have small utilization value. There are two places in the code where it makes a difference: 1. In the find_energy_efficient_cpu() where we are searching for best_delta. We might suffer there when two PDs return the same result, like in the example below. Scenario: Low utilized system e.g. ~200 sum_util for PD0 and ~220 for PD1. There are quite a few small tasks ~10-15 util. These tasks would suffer for the rounding error. These utilization values are typical when running games on Android. One of our partners has reported 5..10mA less battery drain when running with increased resolution. Some details: We have two PDs: PD0 (big) and PD1 (little) Let's compare w/o patch set ('old') and w/ patch set ('new') We are comparing energy w/ task and w/o task placed in the PDs a) 'old' w/o patch set, PD0 task_util = 13 cost = 480 sum_util_w/o_task = 215 sum_util_w_task = 228 scale_cpu = 1024 energy_w/o_task = 480 * 215 / 1024 = 100.78 => 100 energy_w_task = 480 * 228 / 1024 = 106.87 => 106 energy_diff = 106 - 100 = 6 (this is equal to 'old' PD1's energy_diff in 'c)') b) 'new' w/ patch set, PD0 task_util = 13 cost = 480 * 1000 = 480000 sum_util_w/o_task = 215 sum_util_w_task = 228 energy_w/o_task = 480000 * 215 / 1024 = 100781 energy_w_task = 480000 * 228 / 1024 = 106875 energy_diff = 106875 - 100781 = 6094 (this is not equal to 'new' PD1's energy_diff in 'd)') c) 'old' w/o patch set, PD1 task_util = 13 cost = 160 sum_util_w/o_task = 283 sum_util_w_task = 293 scale_cpu = 355 energy_w/o_task = 160 * 283 / 355 = 127.55 => 127 energy_w_task = 160 * 296 / 355 = 133.41 => 133 energy_diff = 133 - 127 = 6 (this is equal to 'old' PD0's energy_diff in 'a)') d) 'new' w/ patch set, PD1 task_util = 13 cost = 160 * 1000 = 160000 sum_util_w/o_task = 283 sum_util_w_task = 293 scale_cpu = 355 energy_w/o_task = 160000 * 283 / 355 = 127549 energy_w_task = 160000 * 296 / 355 = 133408 energy_diff = 133408 - 127549 = 5859 (this is not equal to 'new' PD0's energy_diff in 'b)') 2. Difference in the 6% energy margin filter at the end of find_energy_efficient_cpu(). With this patch the margin comparison also has better resolution, so it's possible to have better task placement thanks to that. Fixes: 27871f7a8a341ef ("PM: Introduce an Energy Model management framework") Reported-by: CCJ Yeh <CCj.Yeh@mediatek.com> Reviewed-by: Dietmar Eggemann <dietmar.eggemann@arm.com> Signed-off-by: Lukasz Luba <lukasz.luba@arm.com> Signed-off-by: Rafael J. Wysocki <rafael.j.wysocki@intel.com> Signed-off-by: Sasha Levin <sashal@kernel.org>
2021-08-03 19:27:43 +09:00
unsigned long power_res = em_scale_power(table[i].power);
table[i].cost = div64_u64(fmax * power_res,
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 18:56:16 +09:00
table[i].frequency);
}
pd->table = table;
pd->nr_cap_states = nr_states;
cpumask_copy(to_cpumask(pd->cpus), span);
PM / EM: Expose the Energy Model in debugfs The recently introduced Energy Model (EM) framework manages power cost tables of CPUs. These tables are currently only visible from kernel space. However, in order to debug the behaviour of subsystems that use the EM (EAS for example), it is often required to know what the power costs are from userspace. For this reason, introduce under /sys/kernel/debug/energy_model a set of directories representing the performance domains of the system. Each performance domain contains a set of sub-directories representing the different capacity states (cs) and their attributes, as well as a file exposing the related CPUs. The resulting hierarchy is as follows on Arm juno r0 for example: /sys/kernel/debug/energy_model ├── pd0 │   ├── cpus │   ├── cs:450000 │   │   ├── cost │   │   ├── frequency │   │   └── power │   ├── cs:575000 │   │   ├── cost │   │   ├── frequency │   │   └── power │   ├── cs:700000 │   │   ├── cost │   │   ├── frequency │   │   └── power │   ├── cs:775000 │   │   ├── cost │   │   ├── frequency │   │   └── power │   └── cs:850000 │   ├── cost │   ├── frequency │   └── power └── pd1 ├── cpus ├── cs:1100000 │   ├── cost │   ├── frequency │   └── power ├── cs:450000 │   ├── cost │   ├── frequency │   └── power ├── cs:625000 │   ├── cost │   ├── frequency │   └── power ├── cs:800000 │   ├── cost │   ├── frequency │   └── power └── cs:950000 ├── cost ├── frequency └── power Signed-off-by: Quentin Perret <quentin.perret@arm.com> Reviewed-by: Greg Kroah-Hartman <gregkh@linuxfoundation.org> Signed-off-by: Rafael J. Wysocki <rafael.j.wysocki@intel.com>
2019-01-23 01:42:47 +09:00
em_debug_create_pd(pd, 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 18:56:16 +09:00
return pd;
free_cs_table:
kfree(table);
free_pd:
kfree(pd);
return NULL;
}
/**
* em_cpu_get() - Return the performance domain for a CPU
* @cpu : CPU to find the performance domain for
*
* Return: the performance domain to which 'cpu' belongs, or NULL if it doesn't
* exist.
*/
struct em_perf_domain *em_cpu_get(int cpu)
{
return READ_ONCE(per_cpu(em_data, cpu));
}
EXPORT_SYMBOL_GPL(em_cpu_get);
/**
* em_register_perf_domain() - Register the Energy Model of a performance domain
* @span : Mask of CPUs in the performance domain
* @nr_states : Number of capacity states to register
* @cb : Callback functions providing the data of the Energy Model
*
* Create Energy Model tables for a performance domain using the callbacks
* defined in cb.
*
* If multiple clients register the same performance domain, all but the first
* registration will be ignored.
*
* Return 0 on success
*/
int em_register_perf_domain(cpumask_t *span, unsigned int nr_states,
struct em_data_callback *cb)
{
unsigned long cap, prev_cap = 0;
struct em_perf_domain *pd;
int cpu, ret = 0;
if (!span || !nr_states || !cb)
return -EINVAL;
/*
* Use a mutex to serialize the registration of performance domains and
* let the driver-defined callback functions sleep.
*/
mutex_lock(&em_pd_mutex);
for_each_cpu(cpu, span) {
/* Make sure we don't register again an existing domain. */
if (READ_ONCE(per_cpu(em_data, cpu))) {
ret = -EEXIST;
goto unlock;
}
/*
* All CPUs of a domain must have the same micro-architecture
* since they all share the same table.
*/
cap = arch_scale_cpu_capacity(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 18:56:16 +09:00
if (prev_cap && prev_cap != cap) {
pr_err("CPUs of %*pbl must have the same capacity\n",
cpumask_pr_args(span));
ret = -EINVAL;
goto unlock;
}
prev_cap = cap;
}
/* Create the performance domain and add it to the Energy Model. */
pd = em_create_pd(span, nr_states, cb);
if (!pd) {
ret = -EINVAL;
goto unlock;
}
for_each_cpu(cpu, span) {
/*
* The per-cpu array can be read concurrently from em_cpu_get().
* The barrier enforces the ordering needed to make sure readers
* can only access well formed em_perf_domain structs.
*/
smp_store_release(per_cpu_ptr(&em_data, cpu), pd);
}
pr_debug("Created perf domain %*pbl\n", cpumask_pr_args(span));
unlock:
mutex_unlock(&em_pd_mutex);
return ret;
}
EXPORT_SYMBOL_GPL(em_register_perf_domain);