From mboxrd@z Thu Jan 1 00:00:00 1970 Return-Path: Received: (majordomo@vger.kernel.org) by vger.kernel.org via listexpand id S934138AbbELTor (ORCPT ); Tue, 12 May 2015 15:44:47 -0400 Received: from foss.arm.com ([217.140.101.70]:33852 "EHLO foss.arm.com" rhost-flags-OK-OK-OK-OK) by vger.kernel.org with ESMTP id S933830AbbELTiU (ORCPT ); Tue, 12 May 2015 15:38:20 -0400 From: Morten Rasmussen To: peterz@infradead.org, mingo@redhat.com Cc: vincent.guittot@linaro.org, Dietmar Eggemann , yuyang.du@intel.com, preeti@linux.vnet.ibm.com, mturquette@linaro.org, rjw@rjwysocki.net, Juri Lelli , sgurrappadi@nvidia.com, pang.xunlei@zte.com.cn, linux-kernel@vger.kernel.org, linux-pm@vger.kernel.org, morten.rasmussen@arm.com Subject: [RFCv4 PATCH 13/34] sched: Documentation for scheduler energy cost model Date: Tue, 12 May 2015 20:38:48 +0100 Message-Id: <1431459549-18343-14-git-send-email-morten.rasmussen@arm.com> X-Mailer: git-send-email 1.9.1 In-Reply-To: <1431459549-18343-1-git-send-email-morten.rasmussen@arm.com> References: <1431459549-18343-1-git-send-email-morten.rasmussen@arm.com> Sender: linux-kernel-owner@vger.kernel.org List-ID: X-Mailing-List: linux-kernel@vger.kernel.org This documentation patch provides an overview of the experimental scheduler energy costing model, associated data structures, and a reference recipe on how platforms can be characterized to derive energy models. Signed-off-by: Morten Rasmussen --- Documentation/scheduler/sched-energy.txt | 363 +++++++++++++++++++++++++++++++ 1 file changed, 363 insertions(+) create mode 100644 Documentation/scheduler/sched-energy.txt diff --git a/Documentation/scheduler/sched-energy.txt b/Documentation/scheduler/sched-energy.txt new file mode 100644 index 0000000..f2a4c19 --- /dev/null +++ b/Documentation/scheduler/sched-energy.txt @@ -0,0 +1,363 @@ +Energy cost model for energy-aware scheduling (EXPERIMENTAL) + +Introduction +============= + +The basic energy model uses platform energy data stored in sched_group_energy +data structures attached to the sched_groups in the sched_domain hierarchy. The +energy cost model offers two functions that can be used to guide scheduling +decisions: + +1. static unsigned int sched_group_energy(struct energy_env *eenv) +2. static int energy_diff(struct energy_env *eenv) + +sched_group_energy() estimates the energy consumed by all cpus in a specific +sched_group including any shared resources owned exclusively by this group of +cpus. Resources shared with other cpus are excluded (e.g. later level caches). + +energy_diff() estimates the total energy impact of a utilization change. That +is, adding, removing, or migrating utilization (tasks). + +Both functions use a struct energy_env to specify the scenario to be evaluated: + + struct energy_env { + struct sched_group *sg_top; + struct sched_group *sg_cap; + int cap_idx; + int usage_delta; + int src_cpu; + int dst_cpu; + int energy; + }; + +sg_top: sched_group to be evaluated. Not used by energy_diff(). + +sg_cap: sched_group covering the cpus in the same frequency domain. Set by +sched_group_energy(). + +cap_idx: Capacity state to be used for energy calculations. Set by +find_new_capacity(). + +usage_delta: Amount of utilization to be added, removed, or migrated. + +src_cpu: Source cpu from where 'usage_delta' utilization is removed. Should be +-1 if no source (e.g. task wake-up). + +dst_cpu: Destination cpu where 'usage_delta' utilization is added. Should be -1 +if utilization is removed (e.g. terminating tasks). + +energy: Result of sched_group_energy(). + +The metric used to represent utilization is the actual per-entity running time +averaged over time using a geometric series. Very similar to the existing +per-entity load-tracking, but _not_ scaled by task priority and capped by the +capacity of the cpu. The latter property does mean that utilization may +underestimate the compute requirements for task on fully/over utilized cpus. +The greatest potential for energy savings without affecting performance too much +is scenarios where the system isn't fully utilized. If the system is deemed +fully utilized load-balancing should be done with task load (includes task +priority) instead in the interest of fairness and performance. + + +Background and Terminology +=========================== + +To make it clear from the start: + +energy = [joule] (resource like a battery on powered devices) +power = energy/time = [joule/second] = [watt] + +The goal of energy-aware scheduling is to minimize energy, while still getting +the job done. That is, we want to maximize: + + performance [inst/s] + -------------------- + power [W] + +which is equivalent to minimizing: + + energy [J] + ----------- + instruction + +while still getting 'good' performance. It is essentially an alternative +optimization objective to the current performance-only objective for the +scheduler. This alternative considers two objectives: energy-efficiency and +performance. Hence, there needs to be a user controllable knob to switch the +objective. Since it is early days, this is currently a sched_feature +(ENERGY_AWARE). + +The idea behind introducing an energy cost model is to allow the scheduler to +evaluate the implications of its decisions rather than applying energy-saving +techniques blindly that may only have positive effects on some platforms. At +the same time, the energy cost model must be as simple as possible to minimize +the scheduler latency impact. + +Platform topology +------------------ + +The system topology (cpus, caches, and NUMA information, not peripherals) is +represented in the scheduler by the sched_domain hierarchy which has +sched_groups attached at each level that covers one or more cpus (see +sched-domains.txt for more details). To add energy awareness to the scheduler +we need to consider power and frequency domains. + +Power domain: + +A power domain is a part of the system that can be powered on/off +independently. Power domains are typically organized in a hierarchy where you +may be able to power down just a cpu or a group of cpus along with any +associated resources (e.g. shared caches). Powering up a cpu means that all +power domains it is a part of in the hierarchy must be powered up. Hence, it is +more expensive to power up the first cpu that belongs to a higher level power +domain than powering up additional cpus in the same high level domain. Two +level power domain hierarchy example: + + Power source + +-------------------------------+----... +per group PD G G + | +----------+ | + +--------+-------| Shared | (other groups) +per-cpu PD G G | resource | + | | +----------+ + +-------+ +-------+ + | CPU 0 | | CPU 1 | + +-------+ +-------+ + +Frequency domain: + +Frequency domains (P-states) typically cover the same group of cpus as one of +the power domain levels. That is, there might be several smaller power domains +sharing the same frequency (P-state) or there might be a power domain spanning +multiple frequency domains. + +From a scheduling point of view there is no need to know the actual frequencies +[Hz]. All the scheduler cares about is the compute capacity available at the +current state (P-state) the cpu is in and any other available states. For that +reason, and to also factor in any cpu micro-architecture differences, compute +capacity scaling states are called 'capacity states' in this document. For SMP +systems this is equivalent to P-states. For mixed micro-architecture systems +(like ARM big.LITTLE) it is P-states scaled according to the micro-architecture +performance relative to the other cpus in the system. + +Energy modelling: +------------------ + +Due to the hierarchical nature of the power domains, the most obvious way to +model energy costs is therefore to associate power and energy costs with +domains (groups of cpus). Energy costs of shared resources are associated with +the group of cpus that share the resources, only the cost of powering the +cpu itself and any private resources (e.g. private L1 caches) is associated +with the per-cpu groups (lowest level). + +For example, for an SMP system with per-cpu power domains and a cluster level +(group of cpus) power domain we get the overall energy costs to be: + + energy = energy_cluster + n * energy_cpu + +where 'n' is the number of cpus powered up and energy_cluster is the cost paid +as soon as any cpu in the cluster is powered up. + +The power and frequency domains can naturally be mapped onto the existing +sched_domain hierarchy and sched_groups by adding the necessary data to the +existing data structures. + +The energy model considers energy consumption from two contributors (shown in +the illustration below): + +1. Busy energy: Energy consumed while a cpu and the higher level groups that it +belongs to are busy running tasks. Busy energy is associated with the state of +the cpu, not an event. The time the cpu spends in this state varies. Thus, the +most obvious platform parameter for this contribution is busy power +(energy/time). + +2. Idle energy: Energy consumed while a cpu and higher level groups that it +belongs to are idle (in a C-state). Like busy energy, idle energy is associated +with the state of the cpu. Thus, the platform parameter for this contribution +is idle power (energy/time). + +Energy consumed during transitions from an idle-state (C-state) to a busy state +(P-staet) or going the other way is ignored by the model to simplify the energy +model calculations. + + + Power + ^ + | busy->idle idle->busy + | transition transition + | + | _ __ + | / \ / \__________________ + |______________/ \ / + | \ / + | Busy \ Idle / Busy + | low P-state \____________/ high P-state + | + +------------------------------------------------------------> time + +Busy |--------------| |-----------------| + +Wakeup |------| |------| + +Idle |------------| + + +The basic algorithm +==================== + +The basic idea is to determine the total energy impact when utilization is +added or removed by estimating the impact at each level in the sched_domain +hierarchy starting from the bottom (sched_group contains just a single cpu). +The energy cost comes from busy time (sched_group is awake because one or more +cpus are busy) and idle time (in an idle-state). Energy model numbers account +for energy costs associated with all cpus in the sched_group as a group. + + for_each_domain(cpu, sd) { + sg = sched_group_of(cpu) + energy_before = curr_util(sg) * busy_power(sg) + + (1-curr_util(sg)) * idle_power(sg) + energy_after = new_util(sg) * busy_power(sg) + + (1-new_util(sg)) * idle_power(sg) + energy_diff += energy_before - energy_after + + } + + return energy_diff + +{curr, new}_util: The cpu utilization at the lowest level and the overall +non-idle time for the entire group for higher levels. Utilization is in the +range 0.0 to 1.0 in the pseudo-code. + +busy_power: The power consumption of the sched_group. + +idle_power: The power consumption of the sched_group when idle. + +Note: It is a fundamental assumption that the utilization is (roughly) scale +invariant. Task utilization tracking factors in any frequency scaling and +performance scaling differences due to difference cpu microarchitectures such +that task utilization can be used across the entire system. + + +Platform energy data +===================== + +struct sched_group_energy can be attached to sched_groups in the sched_domain +hierarchy and has the following members: + +cap_states: + List of struct capacity_state representing the supported capacity states + (P-states). struct capacity_state has two members: cap and power, which + represents the compute capacity and the busy_power of the state. The + list must be ordered by capacity low->high. + +nr_cap_states: + Number of capacity states in cap_states list. + +idle_states: + List of struct idle_state containing idle_state power cost for each + idle-state support by the sched_group. Note that the energy model + calculations will use this table to determine idle power even if no idle + state is actually entered by cpuidle. That is, if latency constraints + prevents that the group enters a coupled state or no idle-states are + supported. Hence, the first entry of the list must be the idle power + when idle, but no idle state was actually entered ('active idle'). This + state may be left out groups with one cpu if the cpu is guaranteed to + enter the state when idle. + +nr_idle_states: + Number of idle states in idle_states list. + +nr_idle_states_below: + Number of idle-states below current level. Filled by generic code, not + to be provided by the platform. + +There are no unit requirements for the energy cost data. Data can be normalized +with any reference, however, the normalization must be consistent across all +energy cost data. That is, one bogo-joule/watt must be the same quantity for +data, but we don't care what it is. + +A recipe for platform characterization +======================================= + +Obtaining the actual model data for a particular platform requires some way of +measuring power/energy. There isn't a tool to help with this (yet). This +section provides a recipe for use as reference. It covers the steps used to +characterize the ARM TC2 development platform. This sort of measurements is +expected to be done anyway when tuning cpuidle and cpufreq for a given +platform. + +The energy model needs two types of data (struct sched_group_energy holds +these) for each sched_group where energy costs should be taken into account: + +1. Capacity state information + +A list containing the compute capacity and power consumption when fully +utilized attributed to the group as a whole for each available capacity state. +At the lowest level (group contains just a single cpu) this is the power of the +cpu alone without including power consumed by resources shared with other cpus. +It basically needs to fit the basic modelling approach described in "Background +and Terminology" section: + + energy_system = energy_shared + n * energy_cpu + +for a system containing 'n' busy cpus. Only 'energy_cpu' should be included at +the lowest level. 'energy_shared' is included at the next level which +represents the group of cpus among which the resources are shared. + +This model is, of course, a simplification of reality. Thus, power/energy +attributions might not always exactly represent how the hardware is designed. +Also, busy power is likely to depend on the workload. It is therefore +recommended to use a representative mix of workloads when characterizing the +capacity states. + +If the group has no capacity scaling support, the list will contain a single +state where power is the busy power attributed to the group. The capacity +should be set to a default value (1024). + +When frequency domains include multiple power domains, the group representing +the frequency domain and all child groups share capacity states. This must be +indicated by setting the SD_SHARE_CAP_STATES sched_domain flag. All groups at +all levels that share the capacity state must have the list of capacity states +with the power set to the contribution of the individual group. + +2. Idle power information + +Stored in the idle_states list. The power number is the group idle power +consumption in each idle state as well when the group is idle but has not +entered an idle-state ('active idle' as mentioned earlier). Due to the way the +energy model is defined, the idle power of the deepest group idle state can +alternatively be accounted for in the parent group busy power. In that case the +group idle state power values are offset such that the idle power of the +deepest state is zero. It is less intuitive, but it is easier to measure as +idle power consumed by the group and the busy/idle power of the parent group +cannot be distinguished without per group measurement points. + +Measuring capacity states and idle power: + +The capacity states' capacity and power can be estimated by running a benchmark +workload at each available capacity state. By restricting the benchmark to run +on subsets of cpus it is possible to extrapolate the power consumption of +shared resources. + +ARM TC2 has two clusters of two and three cpus respectively. Each cluster has a +shared L2 cache. TC2 has on-chip energy counters per cluster. Running a +benchmark workload on just one cpu in a cluster means that power is consumed in +the cluster (higher level group) and a single cpu (lowest level group). Adding +another benchmark task to another cpu increases the power consumption by the +amount consumed by the additional cpu. Hence, it is possible to extrapolate the +cluster busy power. + +For platforms that don't have energy counters or equivalent instrumentation +built-in, it may be possible to use an external DAQ to acquire similar data. + +If the benchmark includes some performance score (for example sysbench cpu +benchmark), this can be used to record the compute capacity. + +Measuring idle power requires insight into the idle state implementation on the +particular platform. Specifically, if the platform has coupled idle-states (or +package states). To measure non-coupled per-cpu idle-states it is necessary to +keep one cpu busy to keep any shared resources alive to isolate the idle power +of the cpu from idle/busy power of the shared resources. The cpu can be tricked +into different per-cpu idle states by disabling the other states. Based on +various combinations of measurements with specific cpus busy and disabling +idle-states it is possible to extrapolate the idle-state power. -- 1.9.1