Enhancing Monte Carlo proxy applications on GPUs

Forrest Shriver, Seyong Lee, Steven Hamilton, Jeffrey Vetter, Justin Watson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In Monte Carlo neutron transport simulations, a computational routine commonly known as the 'cross-section lookup' has been identified as being the most computationally expensive part of these applications. A tool which is commonly used as a proxy application for these routines, named 'XSBench', was created to simulate popular algorithms used in these routines on CPUs. Currently, however, as GPU-based HPC resources have become more widely available, there has been significant interest and efforts invested in moving these traditionally CPU-based simulations to GPUs. Unfortunately, the algorithms commonly used in the cross-section lookup routine were originally devised and developed for CPU-based platforms, and have seen limited study on GPUs to date. Additionally, platforms such as XSBench implement approximations which may have a negligible effect on CPUs, but may be quite impactful to performance on GPUs given the more resource-limited nature of the latter. As a result, we have created VEXS, a new tool for modeling the cross-section lookup routine which removes or at least reduces the approximations made by XSBench in order to provide a more realistic prediction of algorithm performance on GPUs. In this paper, we detail our efforts to remove and reduce these approximations, show the resulting improvement in performance prediction in comparison to a reference production code, Shift, and provide some basic profiling analysis of the resulting application.

Original languageEnglish (US)
Title of host publicationProceedings of PMBS 2019
Subtitle of host publicationPerformance Modeling, Benchmarking and Simulation of High Performance Computer Systems - Held in conjunction with SC 2019: The International Conference for High Performance Computing, Networking, Storage and Analysis
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages30-40
Number of pages11
ISBN (Electronic)9781728159775
DOIs
StatePublished - Nov 2019
Event10th IEEE/ACM Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems, PMBS 2019 - Denver, United States
Duration: Nov 18 2019 → …

Publication series

NameProceedings of PMBS 2019: Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems - Held in conjunction with SC 2019: The International Conference for High Performance Computing, Networking, Storage and Analysis

Conference

Conference10th IEEE/ACM Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems, PMBS 2019
CountryUnited States
CityDenver
Period11/18/19 → …

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Safety, Risk, Reliability and Quality
  • Modeling and Simulation

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  • Cite this

    Shriver, F., Lee, S., Hamilton, S., Vetter, J., & Watson, J. (2019). Enhancing Monte Carlo proxy applications on GPUs. In Proceedings of PMBS 2019: Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems - Held in conjunction with SC 2019: The International Conference for High Performance Computing, Networking, Storage and Analysis (pp. 30-40). [9059270] (Proceedings of PMBS 2019: Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems - Held in conjunction with SC 2019: The International Conference for High Performance Computing, Networking, Storage and Analysis). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/PMBS49563.2019.00009