Central, scheduler-driven, power-performance control (EXPERIMENTAL) Abstract ======== The topic of a single simple power-performance tunable, that is wholly scheduler centric, and has well defined and predictable properties has come up on several occasions in the past [1,2]. With techniques such as a scheduler driven DVFS [3], we now have a good framework for implementing such a tunable. This document describes the overall ideas behind its design and implementation. Table of Contents ================= 1. Motivation 2. Introduction 3. Signal Boosting Strategy 4. OPP selection using boosted CPU utilization 5. Per task group boosting 6. Per-task wakeup-placement-strategy Selection 7. Question and Answers - What about "auto" mode? - What about boosting on a congested system? - How CPUs are boosted when we have tasks with multiple boost values? 8. References 1. Motivation ============= Sched-DVFS [3] was a new event-driven cpufreq governor which allows the scheduler to select the optimal DVFS operating point (OPP) for running a task allocated to a CPU. Later, the cpufreq maintainers introduced a similar governor, schedutil. The introduction of schedutil also enables running workloads at the most energy efficient OPPs. However, sometimes it may be desired to intentionally boost the performance of a workload even if that could imply a reasonable increase in energy consumption. For example, in order to reduce the response time of a task, we may want to run the task at a higher OPP than the one that is actually required by it's CPU bandwidth demand. This last requirement is especially important if we consider that one of the main goals of the utilization-driven governor component is to replace all currently available CPUFreq policies. Since sched-DVFS and schedutil are event based, as opposed to the sampling driven governors we currently have, they are already more responsive at selecting the optimal OPP to run tasks allocated to a CPU. However, just tracking the actual task load demand may not be enough from a performance standpoint. For example, it is not possible to get behaviors similar to those provided by the "performance" and "interactive" CPUFreq governors. This document describes an implementation of a tunable, stacked on top of the utilization-driven governors which extends their functionality to support task performance boosting. By "performance boosting" we mean the reduction of the time required to complete a task activation, i.e. the time elapsed from a task wakeup to its next deactivation (e.g. because it goes back to sleep or it terminates). For example, if we consider a simple periodic task which executes the same workload for 5[s] every 20[s] while running at a certain OPP, a boosted execution of that task must complete each of its activations in less than 5[s]. A previous attempt [5] to introduce such a boosting feature has not been successful mainly because of the complexity of the proposed solution. Previous versions of the approach described in this document exposed a single simple interface to user-space. This single tunable knob allowed the tuning of system wide scheduler behaviours ranging from energy efficiency at one end through to incremental performance boosting at the other end. This first tunable affects all tasks. However, that is not useful for Android products so in this version only a more advanced extension of the concept is provided which uses CGroups to boost the performance of only selected tasks while using the energy efficient default for all others. The rest of this document introduces in more details the proposed solution which has been named SchedTune. 2. Introduction =============== SchedTune exposes a simple user-space interface provided through a new CGroup controller 'stune' which provides two power-performance tunables per group: //schedtune.prefer_idle //schedtune.boost The CGroup implementation permits arbitrary user-space defined task classification to tune the scheduler for different goals depending on the specific nature of the task, e.g. background vs interactive vs low-priority. More details are given in section 5. 2.1 Boosting ============ The boost value is expressed as an integer in the range [-100..0..100]. A value of 0 (default) configures the CFS scheduler for maximum energy efficiency. This means that sched-DVFS runs the tasks at the minimum OPP required to satisfy their workload demand. A value of 100 configures scheduler for maximum performance, which translates to the selection of the maximum OPP on that CPU. A value of -100 configures scheduler for minimum performance, which translates to the selection of the minimum OPP on that CPU. The range between -100, 0 and 100 can be set to satisfy other scenarios suitably. For example to satisfy interactive response or depending on other system events (battery level etc). The overall design of the SchedTune module is built on top of "Per-Entity Load Tracking" (PELT) signals and sched-DVFS by introducing a bias on the Operating Performance Point (OPP) selection. Each time a task is allocated on a CPU, cpufreq is given the opportunity to tune the operating frequency of that CPU to better match the workload demand. The selection of the actual OPP being activated is influenced by the boost value for the task CGroup. This simple biasing approach leverages existing frameworks, which means minimal modifications to the scheduler, and yet it allows to achieve a range of different behaviours all from a single simple tunable knob. In EAS schedulers, we use boosted task and CPU utilization for energy calculation and energy-aware task placement. 2.2 prefer_idle =============== This is a flag which indicates to the scheduler that userspace would like the scheduler to focus on energy or to focus on performance. A value of 0 (default) signals to the CFS scheduler that tasks in this group can be placed according to the energy-aware wakeup strategy. A value of 1 signals to the CFS scheduler that tasks in this group should be placed to minimise wakeup latency. The value is combined with the boost value - task placement will not be boost aware however CPU OPP selection is still boost aware. Android platforms typically use this flag for application tasks which the user is currently interacting with. 3. Signal Boosting Strategy =========================== The whole PELT machinery works based on the value of a few load tracking signals which basically track the CPU bandwidth requirements for tasks and the capacity of CPUs. The basic idea behind the SchedTune knob is to artificially inflate some of these load tracking signals to make a task or RQ appears more demanding that it actually is. Which signals have to be inflated depends on the specific "consumer". However, independently from the specific (signal, consumer) pair, it is important to define a simple and possibly consistent strategy for the concept of boosting a signal. A boosting strategy defines how the "abstract" user-space defined sched_cfs_boost value is translated into an internal "margin" value to be added to a signal to get its inflated value: margin := boosting_strategy(sched_cfs_boost, signal) boosted_signal := signal + margin Different boosting strategies were identified and analyzed before selecting the one found to be most effective. Signal Proportional Compensation (SPC) -------------------------------------- In this boosting strategy the sched_cfs_boost value is used to compute a margin which is proportional to the complement of the original signal. When a signal has a maximum possible value, its complement is defined as the delta from the actual value and its possible maximum. Since the tunable implementation uses signals which have SCHED_LOAD_SCALE as the maximum possible value, the margin becomes: margin := sched_cfs_boost * (SCHED_LOAD_SCALE - signal) Using this boosting strategy: - a 100% sched_cfs_boost means that the signal is scaled to the maximum value - each value in the range of sched_cfs_boost effectively inflates the signal in question by a quantity which is proportional to the maximum value. For example, by applying the SPC boosting strategy to the selection of the OPP to run a task it is possible to achieve these behaviors: - 0% boosting: run the task at the minimum OPP required by its workload - 100% boosting: run the task at the maximum OPP available for the CPU - 50% boosting: run at the half-way OPP between minimum and maximum Which means that, at 50% boosting, a task will be scheduled to run at half of the maximum theoretically achievable performance on the specific target platform. A graphical representation of an SPC boosted signal is represented in the following figure where: a) "-" represents the original signal b) "b" represents a 50% boosted signal c) "p" represents a 100% boosted signal ^ | SCHED_LOAD_SCALE +-----------------------------------------------------------------+ |pppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppppp | | boosted_signal | bbbbbbbbbbbbbbbbbbbbbbbb | | original signal | bbbbbbbbbbbbbbbbbbbbbbbb+----------------------+ | | |bbbbbbbbbbbbbbbbbb | | | | | | | | +-----------------------+ | | | | | | |------------------+ | | +-----------------------------------------------------------------------> The plot above shows a ramped load signal (titled 'original_signal') and it's boosted equivalent. For each step of the original signal the boosted signal corresponding to a 50% boost is midway from the original signal and the upper bound. Boosting by 100% generates a boosted signal which is always saturated to the upper bound. 4. OPP selection using boosted CPU utilization ============================================== It is worth calling out that the implementation does not introduce any new load signals. Instead, it provides an API to tune existing signals. This tuning is done on demand and only in scheduler code paths where it is sensible to do so. The new API calls are defined to return either the default signal or a boosted one, depending on the value of sched_cfs_boost. This is a clean an non invasive modification of the existing existing code paths. The signal representing a CPU's utilization is boosted according to the previously described SPC boosting strategy. To sched-DVFS, this allows a CPU (ie CFS run-queue) to appear more used then it actually is. Thus, with the sched_cfs_boost enabled we have the following main functions to get the current utilization of a CPU: cpu_util() boosted_cpu_util() The new boosted_cpu_util() is similar to the first but returns a boosted utilization signal which is a function of the sched_cfs_boost value. This function is used in the CFS scheduler code paths where sched-DVFS needs to decide the OPP to run a CPU at. For example, this allows selecting the highest OPP for a CPU which has the boost value set to 100%. 5. Per task group boosting ========================== On battery powered devices there usually are many background services which are long running and need energy efficient scheduling. On the other hand, some applications are more performance sensitive and require an interactive response and/or maximum performance, regardless of the energy cost. To better service such scenarios, the SchedTune implementation has an extension that provides a more fine grained boosting interface. A new CGroup controller, namely "schedtune", can be enabled which allows to defined and configure task groups with different boosting values. Tasks that require special performance can be put into separate CGroups. The value of the boost associated with the tasks in this group can be specified using a single knob exposed by the CGroup controller: schedtune.boost This knob allows the definition of a boost value that is to be used for SPC boosting of all tasks attached to this group. The current schedtune controller implementation is really simple and has these main characteristics: 1) It is only possible to create 1 level depth hierarchies The root control groups define the system-wide boost value to be applied by default to all tasks. Its direct subgroups are named "boost groups" and they define the boost value for specific set of tasks. Further nested subgroups are not allowed since they do not have a sensible meaning from a user-space standpoint. 2) It is possible to define only a limited number of "boost groups" This number is defined at compile time and by default configured to 16. This is a design decision motivated by two main reasons: a) In a real system we do not expect utilization scenarios with more then few boost groups. For example, a reasonable collection of groups could be just "background", "interactive" and "performance". b) It simplifies the implementation considerably, especially for the code which has to compute the per CPU boosting once there are multiple RUNNABLE tasks with different boost values. Such a simple design should allow servicing the main utilization scenarios identified so far. It provides a simple interface which can be used to manage the power-performance of all tasks or only selected tasks. Moreover, this interface can be easily integrated by user-space run-times (e.g. Android, ChromeOS) to implement a QoS solution for task boosting based on tasks classification, which has been a long standing requirement. Setup and usage --------------- 0. Use a kernel with CONFIG_SCHED_TUNE support enabled 1. Check that the "schedtune" CGroup controller is available: root@linaro-nano:~# cat /proc/cgroups #subsys_name hierarchy num_cgroups enabled cpuset 0 1 1 cpu 0 1 1 schedtune 0 1 1 2. Mount a tmpfs to create the CGroups mount point (Optional) root@linaro-nano:~# sudo mount -t tmpfs cgroups /sys/fs/cgroup 3. Mount the "schedtune" controller root@linaro-nano:~# mkdir /sys/fs/cgroup/stune root@linaro-nano:~# sudo mount -t cgroup -o schedtune stune /sys/fs/cgroup/stune 4. Create task groups and configure their specific boost value (Optional) For example here we create a "performance" boost group configure to boost all its tasks to 100% root@linaro-nano:~# mkdir /sys/fs/cgroup/stune/performance root@linaro-nano:~# echo 100 > /sys/fs/cgroup/stune/performance/schedtune.boost 5. Move tasks into the boost group For example, the following moves the tasks with PID $TASKPID (and all its threads) into the "performance" boost group. root@linaro-nano:~# echo "TASKPID > /sys/fs/cgroup/stune/performance/cgroup.procs This simple configuration allows only the threads of the $TASKPID task to run, when needed, at the highest OPP in the most capable CPU of the system. 6. Per-task wakeup-placement-strategy Selection =============================================== Many devices have a number of CFS tasks in use which require an absolute minimum wakeup latency, and many tasks for which wakeup latency is not important. For touch-driven environments, removing additional wakeup latency can be critical. When you use the Schedtume CGroup controller, you have access to a second parameter which allows a group to be marked such that energy_aware task placement is bypassed for tasks belonging to that group. prefer_idle=0 (default - use energy-aware task placement if available) prefer_idle=1 (never use energy-aware task placement for these tasks) Since the regular wakeup task placement algorithm in CFS is biased for performance, this has the effect of restoring minimum wakeup latency for the desired tasks whilst still allowing energy-aware wakeup placement to save energy for other tasks. 7. Question and Answers ======================= What about "auto" mode? ----------------------- The 'auto' mode as described in [5] can be implemented by interfacing SchedTune with some suitable user-space element. This element could use the exposed system-wide or cgroup based interface. How are multiple groups of tasks with different boost values managed? --------------------------------------------------------------------- The current SchedTune implementation keeps track of the boosted RUNNABLE tasks on a CPU. The CPU utilization seen by the scheduler-driven cpufreq governors (and used to select an appropriate OPP) is boosted with a value which is the maximum of the boost values of the currently RUNNABLE tasks in its RQ. This allows cpufreq to boost a CPU only while there are boosted tasks ready to run and switch back to the energy efficient mode as soon as the last boosted task is dequeued. 8. References ============= [1] http://lwn.net/Articles/552889 [2] http://lkml.org/lkml/2012/5/18/91 [3] http://lkml.org/lkml/2015/6/26/620