Return-Path: Received: (majordomo@vger.kernel.org) by vger.kernel.org via listexpand id S1759213AbaGCQ0M (ORCPT ); Thu, 3 Jul 2014 12:26:12 -0400 Received: from service87.mimecast.com ([91.220.42.44]:44785 "EHLO service87.mimecast.com" rhost-flags-OK-OK-OK-OK) by vger.kernel.org with ESMTP id S1755667AbaGCQ0I convert rfc822-to-8bit (ORCPT ); Thu, 3 Jul 2014 12:26:08 -0400 From: Morten Rasmussen To: linux-kernel@vger.kernel.org, linux-pm@vger.kernel.org, peterz@infradead.org, mingo@kernel.org Cc: rjw@rjwysocki.net, vincent.guittot@linaro.org, daniel.lezcano@linaro.org, preeti@linux.vnet.ibm.com, Dietmar.Eggemann@arm.com, pjt@google.com Subject: [RFCv2 PATCH 00/23] sched: Energy cost model for energy-aware scheduling Date: Thu, 3 Jul 2014 17:25:47 +0100 Message-Id: <1404404770-323-1-git-send-email-morten.rasmussen@arm.com> X-Mailer: git-send-email 1.7.9.5 MIME-Version: 1.0 X-OriginalArrivalTime: 03 Jul 2014 16:26:05.0772 (UTC) FILETIME=[7D1758C0:01CF96DB] X-MC-Unique: 114070317260606601 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8BIT Sender: linux-kernel-owner@vger.kernel.org List-ID: X-Mailing-List: linux-kernel@vger.kernel.org This is RFC v2 of this proposal (changelog at the end). Several techniques for saving energy through various scheduler modifications have been proposed in the past, however most of the techniques have not been universally beneficial for all use-cases and platforms. For example, consolidating tasks on fewer cpus is an effective way to save energy on some platforms, while it might make things worse on others. This proposal, which is inspired by the Ksummit workshop discussions last year [1], takes a different approach by using a (relatively) simple platform energy cost model to guide scheduling decisions. By providing the model with platform specific costing data the model can provide a estimate of the energy implications of scheduling decisions. So instead of blindly applying scheduling techniques that may or may not work for the current use-case, the scheduler can make informed energy-aware decisions. We believe this approach provides a methodology that can be adapted to any platform, including heterogeneous systems such as ARM big.LITTLE. The model considers cpus only. Model data includes power consumption at each P-state, C-state power consumption, and wake-up energy costs. However, the energy model could potentially be extended to be used to guide performance/energy decisions in other subsystems. For example, the scheduler can use energy_diff_task(cpu, task) to estimate the cost of placing a task on a specific cpu and compare energy costs of different cpus. This is an RFC and there are some loose ends that have not been addressed here or in the code yet. The model and its infrastructure is in place in the scheduler and it is being used for load-balancing decisions. It is used for the select_task_rq_fair() path for fork/exec/wake balancing and to guide the selection of the source cpu for periodic or idle balance. The latter is still very early days. There are quite a few dirty hacks in there to tie things together. To mention a few current limitations: 1. Due to the lack of scale invariant cpu and task utilization, it doesn't work properly with frequency scaling or heterogeneous systems (big.LITTLE). 2. Platform data for the test platform (ARM TC2) has been hardcoded in arch/arm/ code. 3. Most likely idle-state is currently hardcoded to be the shallowest one. cpuidle integration missing. However, the main ideas and the primary focus of this RFC: The energy model and energy_diff_{load, task, cpu}() are there. Due to limitation 1, the ARM TC2 platform (2xA15+3xA7) was setup to disable frequency scaling and set frequencies to eliminate the big.LITTLE performance difference. That basically turns TC2 into an SMP platform where a subset of the cpus are less energy-efficient. Tests using a synthetic workload with seven short running periodic tasks of different size and period, and the sysbench cpu benchmark with five threads gave the following results: cpu energy* short tasks sysbench Mainline 100 100 EA 49 99 * Note that these energy savings are _not_ representative of what can be achieved on a true SMP platform where all cpus are equally energy-efficient. There should be benefit for SMP platforms as well, however, it will be smaller. The energy model led to consolidation of the short tasks on the A7 cluster (more energy-efficient), while sysbench made use of all cpus as the A7s didn't have sufficient compute capacity to handle the five tasks. To see how scheduling would happen if all cpus would have been A7s the same tests were done with the A15s' energy model being the same as that of the A7s (i.e. lying about the platform to the scheduler energy model). The scheduling pattern for the short tasks changed to being either consolidated on the A7 or the A15 cluster instead of just on the A7, which was expected. Currently, there are no tools available to easily deduce energy for traces using a platform energy model, which could have estimated the energy benefit. Linaro is currently looking into extending the idle-stat tool [3] to do this. Testing with more realistic (mobile) use-cases was done using two previously described Android workloads [2]: Audio playback and Web browsing. In addition the combination of the the two was measured. Reported numbers are averages for 20 runs and have been normalized. Browsing performance score is roughly rendering time (less is better). browsing audio browsing+audio Mainline A15 51.5 17.7 40.5 A7 48.5 82.3 59.5 energy 100.0 100.0 100.0 perf 100.0 100.0 EA A15 16.3 2.2 13.4 A7 60.2 80.7 61.1 energy 76.6 82.9 74.6 perf 108.9 108.9 Diff energy -23.4% -17.1% -25.4% perf -8.9% -8.9% Energy is saved for all three use-cases. The performance loss is due to the TC2 fixed frequency setup. The A15s are not exactly delivering the same performance as the A7s. They have ~10% more compute capacity (guestimate). As with the synthetic tests, these numbers are better than what should be expected for a true SMP platform. The latency overhead induced by the energy model in select_task_rq_fair() for this unoptimized implementation on TC2 is: latency avg (depending on cpu) Mainline 2.3 - 4.9 us EA 13.3 - 15.8 us However, it should be possible to reduce this significantly. Patch 1: Documentation Patch 2-5: Infrastructure to set up energy model data Patch 6: ARM TC2 energy model data Patch 7: Infrastructure Patch 8-13: Unweighted load tracking Patch 14-17: Bits and pieces needed for the energy model Patch 18-23: The energy model and scheduler tweaks This series is based on a fairly recent tip/sched/core. [1] http://etherpad.osuosl.org/energy-aware-scheduling-ks-2013 (search for 'cost') [2] https://lkml.org/lkml/2014/1/7/355 [3] http://git.linaro.org/power/idlestat.git [4] https://lkml.org/lkml/2014/4/11/137 Changes RFC v2: - Extended documentation: - Cover the energy model in greater detail. - Recipe for deriving platform energy model. - Replaced Kconfig with sched feature (jump label). - Add unweighted load tracking. - Use unweighted load as task/cpu utilization. - Support for multiple idle states per sched_group. cpuidle integration still missing. - Changed energy aware functionality in select_idle_sibling(). - Experimental energy aware load-balance support. Dietmar Eggemann (12): sched: Introduce energy data structures sched: Allocate and initialize energy data structures sched: Add energy procfs interface arm: topology: Define TC2 energy and provide it to the scheduler sched: Introduce system-wide sched_energy sched: Aggregate unweighted load contributed by task entities on parenting cfs_rq sched: Maintain the unweighted load contribution of blocked entities sched: Account for blocked unweighted load waking back up sched: Introduce an unweighted cpu_load array sched: Rename weighted_cpuload() to cpu_load() sched: Introduce weighted/unweighted switch in load related functions sched: Use energy model in load balance path Morten Rasmussen (11): sched: Documentation for scheduler energy cost model sched: Make energy awareness a sched feature sched: Introduce SD_SHARE_CAP_STATES sched_domain flag sched, cpufreq: Introduce current cpu compute capacity into scheduler sched, cpufreq: Current compute capacity hack for ARM TC2 sched: Likely idle state statistics placeholder sched: Energy model functions sched: Task wakeup tracking sched: Take task wakeups into account in energy estimates sched: Use energy model in select_idle_sibling sched: Use energy to guide wakeup task placement Documentation/scheduler/sched-energy.txt | 439 ++++++++++++++++++++ arch/arm/kernel/topology.c | 126 +++++- drivers/cpufreq/cpufreq.c | 8 + include/linux/sched.h | 28 ++ kernel/sched/core.c | 178 +++++++- kernel/sched/debug.c | 6 + kernel/sched/fair.c | 646 ++++++++++++++++++++++++++---- kernel/sched/features.h | 6 + kernel/sched/proc.c | 22 +- kernel/sched/sched.h | 44 +- 10 files changed, 1416 insertions(+), 87 deletions(-) create mode 100644 Documentation/scheduler/sched-energy.txt -- 1.7.9.5 -- To unsubscribe from this list: send the line "unsubscribe linux-kernel" in the body of a message to majordomo@vger.kernel.org More majordomo info at http://vger.kernel.org/majordomo-info.html Please read the FAQ at http://www.tux.org/lkml/