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Accelerating x-ray tracing for exascale systems using Kokkos

Journal Article · · Concurrency and Computation. Practice and Experience
DOI:https://doi.org/10.1002/cpe.7944· OSTI ID:2500817
 [1];  [2];  [2];  [2];  [2];  [2];  [3];  [4];  [1];  [1]
  1. Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC)
  2. Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
  3. Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
  4. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
+ Show Author Affiliations

The upcoming exascale computing systems Frontier and Aurora will draw much of their computing power from GPU accelerators. The hardware for these systems will be provided by AMD and Intel, respectively, each supporting their own GPU programming model. The challenge for applications that harness one of these exascale systems will be to avoid lock-in and to preserve performance portability. We report here on our results of using Kokkos to accelerate a real-world application on NERSC's Perlmutter Phase 1 (using NVIDIA A100 accelerators) and Crusher, the testbed system for OLCF's Frontier (using AMD MI250X). By porting to Kokkos, we successfully ran the same X-ray tracing code on both systems and achieved speed-ups between 13 % and 66 % compared to the original CUDA code. Finally, these results are a highly encouraging demonstration of using Kokkos to accelerate production science code.

Research Organization:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Basic Energy Sciences (BES). Scientific User Facilities (SUF); USDOE National Nuclear Security Administration (NNSA)
Grant/Contract Number:
NA0003525; AC02-05CH11231; AC05-00OR22725
OSTI ID:
2500817
Journal Information:
Concurrency and Computation. Practice and Experience, Journal Name: Concurrency and Computation. Practice and Experience Journal Issue: 5 Vol. 36; ISSN 1532-0626
Publisher:
WileyCopyright Statement
Country of Publication:
United States
Language:
English

References (5)

The Computational Crystallography Toolbox : crystallographic algorithms in a reusable software framework journal January 2002
New Python-based methods for data processing journal June 2013
Towards the spatial resolution of metalloprotein charge states by detailed modeling of XFEL crystallographic diffraction journal February 2020
Kokkos 3: Programming Model Extensions for the Exascale Era journal January 2021
Experiences with Cross-Facility Real-Time Light Source Data Analysis Workflows conference November 2021

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Related Subjects

97 MATHEMATICS AND COMPUTING
AMD GPU
Kokkos
Nvidia GPU
code optimization
cross compilation