DocumentCode :
3076846
Title :
Analyzing the Impact of CPU Pinning and Partial CPU Loads on Performance and Energy Efficiency
Author :
Podzimek, Andrej ; Bulej, Lubomir ; Chen, Lydia Y. ; Binder, Walter ; Tuma, Petr
fYear :
2015
fDate :
4-7 May 2015
Firstpage :
1
Lastpage :
10
Abstract :
While workload collocation 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 collocated workloads. Besides various combinations of workloads, virtualization 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 experiments 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 partial background loads, indicating that systems hosting collocated workloads could benefit from dynamic CPU pinning based on CPU load and workload type.
Keywords :
performance evaluation; power aware computing; CPU pinning; Intel-based NUMA system; energy efficiency; partial CPU loads; performance interference; power management features; Benchmark testing; Hardware; Interference; Linux; Measurement; Servers; Throughput; KVM virtualization; LXC resource containers; feedback load controller; load throughput relation; partial CPU load; performance interference; reproducible load; workload colocation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cluster, Cloud and Grid Computing (CCGrid), 2015 15th IEEE/ACM International Symposium on
Conference_Location :
Shenzhen
Type :
conf
DOI :
10.1109/CCGrid.2015.164
Filename :
7152466
Link To Document :
بازگشت