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OpenMP application experiences: Porting to accelerated nodes

Journal Article · · Parallel Computing
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  1. Georgia Inst. of Technology, Atlanta, GA (United States)
  2. Argonne National Lab. (ANL), Argonne, IL (United States)
  3. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
  4. Brookhaven National Lab. (BNL), Upton, NY (United States)
  5. Univ. of Tennessee, Knoxville, TN (United States)
  6. Iowa State Univ., Ames, IA (United States)
  7. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
  8. Stony Brook Univ., NY (United States)
As recent enhancements to the OpenMP specification become available in its implementations, there is a need to share the results of experimentation in order to better understand the OpenMP implementation’s behavior in practice, to identify pitfalls, and to learn how the implementations can be effectively deployed in scientific codes. We report on experiences gained and practices adopted when using OpenMP to port a variety of ECP applications, mini-apps and libraries based on different computational motifs to accelerator-based leadership-class high-performance supercomputer systems at the United States Department of Energy. Additionally, we identify important challenges and open problems related to the deployment of OpenMP. Through our report of experiences, we find that OpenMP implementations are successful on current supercomputing platforms and that OpenMP is a promising programming model to use for applications to be run on emerging and future platforms with accelerated nodes.
Research Organization:
Brookhaven National Laboratory (BNL), Upton, NY (United States)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA); National Science Foundation (NSF)
Grant/Contract Number:
SC0012704; AC05-00OR22725; AC02-06CH11357
OSTI ID:
1829281
Alternate ID(s):
OSTI ID: 1829922
OSTI ID: 1832702
OSTI ID: 1870066
Report Number(s):
BNL--222351-2021-JAAM
Journal Information:
Parallel Computing, Journal Name: Parallel Computing Vol. 109; ISSN 0167-8191
Publisher:
ElsevierCopyright Statement
Country of Publication:
United States
Language:
English

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