Evaluation of Portable Programming Models to Accelerate LArTPC Detector Simulations
The Liquid Argon Time Projection Chamber (LArTPC) technology is widely used in high energy physics experiments, including the upcoming Deep Underground Neutrino Experiment (DUNE). Accurately simulating LArTPC detector responses is essential for analysis algorithm development and physics model interp...
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Published in | Journal of physics. Conference series Vol. 2438; no. 1; pp. 12036 - 12042 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
Bristol
IOP Publishing
01.02.2023
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Subjects | |
Online Access | Get full text |
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Summary: | The Liquid Argon Time Projection Chamber (LArTPC) technology is widely used in high energy physics experiments, including the upcoming Deep Underground Neutrino Experiment (DUNE). Accurately simulating LArTPC detector responses is essential for analysis algorithm development and physics model interpretations. Accurate LArTPC detector response simulations are computationally demanding, and can become a bottleneck in the analysis workflow. Compute devices such as General-Purpose Graphics Processing Units (GPGPUs) have the potential to substantially accelerate simulations compared to traditional CPU-only processing. The software development for these compute accelerators often carries the cost of specialized code refactorization and porting to match the target hardware architecture. With the rapid evolution and increased diversity of the computer architecture landscape, it is highly desirable to have a portable solution that also maintains reasonable performance. We report our ongoing effort in evaluating Kokkos as a basis for this portable programming model using LArTPC simulations in the context of the Wire-Cell Toolkit, a C++ library for LArTPC simulations, data analysis, reconstruction and visualization. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) USDOE Office of Science (SC), Basic Energy Sciences (BES). Scientific User Facilities (SUF) SC0012704; AC02-05CH11231; KA2401045 USDOE Office of Science (SC), High Energy Physics (HEP) BNL-223617-2022-JAAM |
ISSN: | 1742-6588 1742-6596 |
DOI: | 10.1088/1742-6596/2438/1/012036 |