TY - GEN
T1 - Enhancing Monte Carlo proxy applications on GPUs
AU - Shriver, Forrest
AU - Lee, Seyong
AU - Hamilton, Steven
AU - Vetter, Jeffrey
AU - Watson, Justin
N1 - Funding Information:
This research was supported in part by the Exascale Computing Project (17-SC-20-SC), a collaborative effort of the U.S. Department of Energy Office of Science and the National Nuclear Security Administration.
Funding Information:
This research was supported in part by an appointment to the Oak Ridge National Laboratory ASTRO Program, sponsored by the U.S. Department of Energy and administered by the Oak Ridge Institute for Science and Education.
Funding Information:
VIII. ACKNOWLEDGEMENTS This research used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy.
Publisher Copyright:
© 2019 IEEE.
PY - 2019/11
Y1 - 2019/11
N2 - 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.
AB - 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.
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U2 - 10.1109/PMBS49563.2019.00009
DO - 10.1109/PMBS49563.2019.00009
M3 - Conference contribution
AN - SCOPUS:85084068843
T3 - 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
SP - 30
EP - 40
BT - Proceedings of PMBS 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 10th IEEE/ACM Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems, PMBS 2019
Y2 - 18 November 2019
ER -