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Analyzing the Impact of CPU Pinning and Partial CPU Loads on Performance and Energy Efficiency
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BibTeX
@MISC{Podzimek_analyzingthe,
author = {Andrej Podzimek and Lubomír Bulej and Lydia Y. Chen and Walter Binder and Petr Tůma},
title = {Analyzing the Impact of CPU Pinning and Partial CPU Loads on Performance and Energy Efficiency},
year = {}
}
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Abstract
Abstract—While workload colocation is a necessity to increase energy efficiency of contemporary multi-core hardware, it also increases the risk of performance anomalies due to workload interference. Pinning certain workloads to a subset of CPUs is a simple approach to increasing workload isolation, but its effect depends on workload type and system architecture. Apart from common sense guidelines, the effect of pinning has not been extensively studied so far. In this paper we study the impact of CPU pinning on performance interference and energy efficiency for pairs of colocated workloads. Besides various combinations of workloads, virtualiza-tion and resource isolation, we explore the effects of pinning depending on the level of background load. The presented results are based on more than 1000 exper-iments carried out on an Intel-based NUMA system, with all power management features enabled to reflect real-world settings. We find that less common CPU pinning configurations improve energy efficiency at par-tial background loads, indicating that systems hosting colocated workloads could benefit from dynamic CPU pinning based on CPU load and workload type. I.
Keyphrases
energy efficiency partial cpu load cpu pinning workload type colocated workload cpu load resource isolation power management feature certain workload presented result performance interference workload isolation intel-based numa system background load performance anomaly par-tial background load dynamic cpu pinning common sense guideline workload colocation various combination system architecture common cpu pinning configuration contemporary multi-core hardware real-world setting simple approach
