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Intel Developer Proposes A New Linux CPU Load Metric

Intel

Published on 25 April 2014 01:22 AM EDT
Written by Michael Larabel in Intel
1 Comment

A Linux developer at Intel has proposed a new CPU load metric for power-efficient scheduling by the Linux kernel.

The new metric is called CPU ConCurrency. Using this metric for power-efficient scheduling, Intel developers implemented a workload consolidation patch for two mobile Intel platforms. The work contains the load and load balancing to two cores when the aggregated CPU ConCurrency is low while when it's high all four CPU cores are used for scheduling. This change led to increased power-savings while no significant performance regessions were spotted.

Intel Developer Proposes A New Linux CPU Load Metric


Intel's Yuyang Du explained CPU ConCurrency on the kernel mailing list. Here's the full explanation:
The current scheduler’s load balancing is completely work-conserving. In some workload, generally low CPU utilization but immersed with CPU bursts of transient tasks, migrating task to engage all available CPUs for work-conserving can lead to significant overhead: cache locality loss, idle/active HW state transitional latency and power, shallower idle state, etc, which are both power and performance inefficient especially for today’s low power processors in mobile.

This RFC introduces a sense of idleness-conserving into work-conserving (by all means, we really don’t want to be overwhelming in only one way). But to what extent the idleness-conserving should be, bearing in mind that we don’t want to sacrifice performance? We first need a load/idleness indicator to that end.

Thanks to CFS’s "model an ideal, precise multi-tasking CPU", tasks can be seen as concurrently running (the tasks in the runqueue). So it is natural to use task concurrency as load indicator. Having said that, we do two things:

1) Divide continuous time into periods of time, and average task concurrency in period, for tolerating the transient bursts: a = sum(concurrency * time) / period
2) Exponentially decay past periods, and synthesize them all, for hysteresis to load drops or resilience to load rises (let f be decaying factor, and a_x the xth period average since period 0): s = a_n + f^1 * a_n-1 + f^2 * a_n-2 +, …..,+ f^(n-1) * a_1 + f^n * a_0

We name this load indicator as CPU ConCurrency (CC): task concurrency determines how many CPUs are needed to be running concurrently.

To track CC, we intercept the scheduler in 1) enqueue, 2) dequeue, 3) scheduler tick, and 4) enter/exit idle.

By CC, we implemented a Workload Consolidation patch on two Intel mobile platforms (a quad-core composed of two dual-core modules): contain load and load balancing in the first dual-core when aggregated CC low, and if not in the full quad-core. Results show that we got power savings and no substantial performance regression (even gains for some).

About The Author
Michael Larabel is the principal author of Phoronix.com and founded the web-site in 2004 with a focus on enriching the Linux hardware experience and being the largest web-site devoted to Linux hardware reviews, particularly for products relevant to Linux gamers and enthusiasts but also commonly reviewing servers/workstations and embedded Linux devices. Michael has written more than 10,000 articles covering the state of Linux hardware support, Linux performance, graphics hardware drivers, and other topics. Michael is also the lead developer of the Phoronix Test Suite, Phoromatic, and OpenBenchmarking.org automated testing software. He can be followed via and or contacted via .
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