TY - GEN

T1 - VEXS, an open platform for the study of continuous-energy cross-section lookup algorithms on GPU’s

AU - Shriver, Forrest

AU - Lee, Seyong

AU - Hamilton, Steven

AU - Watson, Justin

AU - Vetter, Jeffrey

PY - 2019/1/1

Y1 - 2019/1/1

N2 - A significant bottleneck in continuous-energy neutron transport simulations is the cross-section lookup problem, especially in the case of those occurring in depleted fuel regions. Several algorithms have been developed over the years to solve this problem on more traditional CPU-based platforms, however new computational architectures such as GPUs may not benefit as significantly from these algorithms. As there is increasing interest in using these new computational architectures as a core part of large simulations, the relative efficacy of these algorithms compared to one another is an interesting area of research. Additionally, implementations of these algorithms are sometimes inaccessible to interested scientists outside of the nuclear engineering field given the export-controlled nature of the codes they are implemented in. In this paper, we describe our work to extend an existing open-source platform for cross-section lookup simulation, XSBench, to GPUs. We also describe our adaptation of the original codebase to handle more realistic datasets, and our efforts to accommodate different in-memory data layouts in order to more closely approximate those implementations used in production codes. Finally, we compare our results with those obtained from Shift, a GPU-enabled Monte Carlo transport solver developed for large neutron transport simulations.

AB - A significant bottleneck in continuous-energy neutron transport simulations is the cross-section lookup problem, especially in the case of those occurring in depleted fuel regions. Several algorithms have been developed over the years to solve this problem on more traditional CPU-based platforms, however new computational architectures such as GPUs may not benefit as significantly from these algorithms. As there is increasing interest in using these new computational architectures as a core part of large simulations, the relative efficacy of these algorithms compared to one another is an interesting area of research. Additionally, implementations of these algorithms are sometimes inaccessible to interested scientists outside of the nuclear engineering field given the export-controlled nature of the codes they are implemented in. In this paper, we describe our work to extend an existing open-source platform for cross-section lookup simulation, XSBench, to GPUs. We also describe our adaptation of the original codebase to handle more realistic datasets, and our efforts to accommodate different in-memory data layouts in order to more closely approximate those implementations used in production codes. Finally, we compare our results with those obtained from Shift, a GPU-enabled Monte Carlo transport solver developed for large neutron transport simulations.

UR - http://www.scopus.com/inward/record.url?scp=85075385651&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85075385651&partnerID=8YFLogxK

M3 - Conference contribution

T3 - International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering, M and C 2019

SP - 2575

EP - 2584

BT - International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering, M and C 2019

PB - American Nuclear Society

T2 - 2019 International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering, M and C 2019

Y2 - 25 August 2019 through 29 August 2019

ER -