Issue |
2014
SNA + MC 2013 - Joint International Conference on Supercomputing in Nuclear Applications + Monte Carlo
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|
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Article Number | 04213 | |
Number of page(s) | 8 | |
Section | 4. Advanced Parallelism and HPC Strategies: b. Monte Carlo Methods, Parallelism and HPC | |
DOI | https://doi.org/10.1051/snamc/201404213 | |
Published online | 06 June 2014 |
GEANT4-MT : bringing multi-threading into GEANT4 production
1 KISTI, Yuseong-gu, Daejeon, 305-806, Korea
2 CERN, CH-1211 Geneva, Switzerland
3 SLAC National Accelerator Laboratory, Menlo Park CA 94025, USA
4 College of Computer and Information Science, Northeastern University, Boston MA 02115, USA
5 Fermilab, Batavia IL 60510, USA
GEANT4-MT is the multi-threaded version of the GEANT4 particle transport code.(1, 2) The key goals for the design of GEANT4-MT have been a) the need to reduce the memory footprint of the multi-threaded application compared to the use of separate jobs and processes; b) to create an easy migration of the existing applications; and c) to use efficiently many threads or cores, by scaling up to tens and potentially hundreds of workers. The first public release of a GEANT4-MT prototype was made in 2011. We report on the revision of GEANT4-MT for inclusion in the production-level release scheduled for end of 2013. This has involved significant re-engineering of the prototype in order to incorporate it into the main GEANT4 development line, and the porting of GEANT4-MT threading code to additional platforms. In order to make the porting of applications as simple as possible, refinements addressed the needs of standalone applications. Further adaptations were created to improve the fit with the frameworks of High Energy Physics (HEP) experiments. We report on performances measurements on Intel Xeon™, AMD Opteron™ the first trials of GEANT4-MT on the Intel Many Integrated Cores (MIC) architecture, in the form of the Xeon Phi™ co-processor.(3) These indicate near-linear scaling through about 200 threads on 60 cores, when holding fixed the number of events per thread.
Key words: particle transport simulation / multi-threading / high-performance computing
© Owned by the authors, published by EDP Sciences, 2014