Vectorization of Random Number Generation and Reproducibility of Concurrent Particle Transport Simulation

Conference · Mon Mar 11 00:00:00 EDT 2019 · J.Phys.Conf.Ser.

OSTI ID:1565947

Jun, S. Y.  ^[1]; Canal, P. ^[1]; Apostolakis, J. ^[2]; Gheata, A. ^[2]; Moneta, L. ^[2]

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1. Fermilab
2. CERN

Efficient random number generation with high quality statistical properties and exact reproducibility of Monte Carlo simulations are important requirements in many areas of computational science. VecRNG is a package providing pseudo-random number generation (pRNG) in the context of a new library VecMath. This library bundles up several general-purpose mathematical utilities, data structures, and algorithms having both SIMD and SIMT (GPUs) support based on VecCore.~Several state-of-the-art RNG algorithms are implemented as kernels supporting parallel generation of random numbers in scalar, vector, and Cuda workflows. In this report, we will present design considerations, implementation details, and computing performance of parallel pRNG engines on both CPU and GPU. Reproducibility of propagating multiple particles in parallel for HEP event simulation is demonstrated, using GeantV-based examples, for both sequential and fine-grain track-level concurrent simulation wor kflows. Strategies for efficient uses of vectorized pRNG and non-overlapping streams of random number sequences in concurrent computing environments is discussed as well.

• Research Organization: Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States)
• Sponsoring Organization: USDOE Office of Science (SC), High Energy Physics (HEP)
• DOE Contract Number: AC02-07CH11359
• OSTI ID: 1565947
• Report Number(s): FERMILAB-CONF-19-035-CD; oai:inspirehep.net:1754423
• Journal Information: J.Phys.Conf.Ser., Conference: 19th International Workshop on Advanced Computing and Analysis Techniques in Physics Research, Saas-Fee, Switzerland, 03/11-03/15/2019
• Country of Publication: United States
• Language: English