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authorMorten Rasmussen <morten.rasmussen@arm.com>2015-01-13 13:43:28 +0000
committerRobin Randhawa <robin.randhawa@arm.com>2015-04-09 12:26:13 +0100
commit153e0173891899790b531e9ccc7ec91b69406d79 (patch)
treeab1385f76b2929073d51107631d3ef341c39335a
parentb82e7deb5e67f6c6ede8d05dd688431626e07892 (diff)
downloadkernel-153e0173891899790b531e9ccc7ec91b69406d79.tar.gz
sched: Documentation for scheduler energy cost model
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 <morten.rasmussen@arm.com>
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+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 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().
+
+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.
+
+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.