Performance Study of Monte Carlo Codes on Xeon Phi Coprocessors — Testing MCNP 6.1 and Profiling ARCHER Geometry Module on the FS7ONNi Problem

This paper contains two parts revolving around Monte Carlo transport simulation on Intel Many Integrated Core coprocessors (MIC, also known as Xeon Phi). (1) MCNP 6.1 was recompiled into multithreading (OpenMP) and multiprocessing (MPI) forms respectively without modification to the source code. The...

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Bibliographic Details
Published in:	EPJ Web of Conferences Vol. 153; p. 6022
Main Authors:	Liu, Tianyu, Wolfe, Noah, Lin, Hui, Zieb, Kris, Ji, Wei, Caracappa, Peter, Carothers, Christopher, Xu, X. George
Format:	Journal Article Conference Proceeding
Language:	English
Published:	Les Ulis EDP Sciences 01-01-2017
Subjects:	Computer simulation Constructive solid geometry Coprocessors Geometry Monte Carlo simulation Multiprocessing Radiation shielding Random walk
Online Access:	Get full text
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Summary:	This paper contains two parts revolving around Monte Carlo transport simulation on Intel Many Integrated Core coprocessors (MIC, also known as Xeon Phi). (1) MCNP 6.1 was recompiled into multithreading (OpenMP) and multiprocessing (MPI) forms respectively without modification to the source code. The new codes were tested on a 60-core 5110P MIC. The test case was FS7ONNi, a radiation shielding problem used in MCNP’s verification and validation suite. It was observed that both codes became slower on the MIC than on a 6-core X5650 CPU, by a factor of ~4 for the MPI code and, abnormally, ~20 for the OpenMP code, and both exhibited limited capability of strong scaling. (2) We have recently added a Constructive Solid Geometry (CSG) module to our ARCHER code to provide better support for geometry modelling in radiation shielding simulation. The functions of this module are frequently called in the particle random walk process. To identify the performance bottleneck we developed a CSG proxy application and profiled the code using the geometry data from FS7ONNi. The profiling data showed that the code was primarily memory latency bound on the MIC. This study suggests that despite low initial porting e_ort, Monte Carlo codes do not naturally lend themselves to the MIC platform — just like to the GPUs, and that the memory latency problem needs to be addressed in order to achieve decent performance gain.
ISSN:	2100-014X 2101-6275 2100-014X
DOI:	10.1051/epjconf/201715306022