NDLI: Performance Evaluation of NAS Parallel Benchmarks on Intel Xeon Phi

Content Provider	IEEE Xplore Digital Library
Author	Ramachandran, A. Vienne, J. Van Der Wijngaart, R. Koesterke, L. Sharapov, I.
Copyright Year	2013
Description	Author affiliation: Intel Corp., Santa Clara, CA, USA (Van Der Wijngaart, R.; Sharapov, I.) \|\| Univ. of Texas at Dallas, Dallas, TX, USA (Ramachandran, A.) \|\| Texas Adv. Comput. Center, Univ. of Texas at Austin, Austin, TX, USA (Vienne, J.; Koesterke, L.)
Abstract	NAS parallel benchmarks (NPB) are a set of applications commonly used to evaluate parallel systems. We use the NPB-OpenMP version to examine the performance of the Intel's new Xeon Phi co-processor and focus in particular on the many core aspect of the Xeon Phi architecture. A first analysis studies the scalability up to 244 threads on 61 cores and the impact of affinity settings on scaling. It also compares performance characteristics of Xeon Phi and traditional Xeon CPUs. The application of several well-established optimization techniques allows us to identify common bottlenecks that can specifically impede performance on the Xeon Phi but are not as severe on multi-core CPUs. We also find that many of the OpenMP-parallel loops are too short (in terms of the number of loop iterations) for a balanced execution by 244 threads. New or redesigned benchmarks will be needed to accommodate the greatly increased number of cores and threads. At the end, we summarize our findings in a set recommendations for performance optimization for Xeon Phi.
Starting Page	736
Ending Page	743
File Size	489179
Page Count	8
File Format	PDF
ISBN	9780769551173
ISSN	01903918
DOI	10.1109/ICPP.2013.87
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-10-01
Publisher Place	France
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Benchmark testing Vectors Bridges Instruction sets Hardware Computer architecture Optimization Performance analysis Parallel programming Multicore processing
Content Type	Text
Resource Type	Article

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