NDLI: Performance analysis with a memory-bound Monte Carlo simulation on Xeon Phi

Content Provider	IEEE Xplore Digital Library
Author	Schweitzer, P. Mazel, C. Hill, D.R.C. Carloganu, C.
Copyright Year	2015
Description	Author affiliation: LPC, Univ. Blaise Pascal, Clermont-Ferrand, France (Carloganu, C.) \|\| LIMOS, Univ. Blaise Pascal, Aubière, France (Schweitzer, P.; Mazel, C.; Hill, D.R.C.)
Abstract	Physics simulations are known to be great resources exhausters (CPU, memory). Hardware acceleration can help reduce the need for CPU time and increase the available memory bandwidth. In this paper, we present the performance gain when running a memory-bound muon Monte Carlo simulation on an Intel Xeon Phi and an Intel Xeon CPU. We show how to increase performance on the Xeon Phi without modifying the Physics software frameworks we are using for our application. We investigate distributed simulations on multicore and manycore systems and also the impact of hyper-threading on performance. We extend this to a hybrid computing model, balancing the computing burden between both the manycore and multicore processors of a computing node. Finally, we improved memory usage on the Xeon Phi by sharing Kernel Memory pages using KSM, and we show that, using this approach, we can run 16% more simulation instances.
Starting Page	444
Ending Page	452
File Size	971542
Page Count	9
File Format	PDF
ISBN	9781467378123
e-ISBN	9781467378130
DOI	10.1109/HPCSim.2015.7237074
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-07-20
Publisher Place	Netherlands
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Multicore processing Computational modeling Instruction sets Kernel memory sharing Memory-bound Simulation distribution Geant4 Monte Carlo methods High Energy Physics Hybrid computing Monte Carlo Xeon Phi Hardware Load modeling
Content Type	Text
Resource Type	Article

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