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From OpenACC to OpenMP5 GPU Offloading: Performance Evaluation on NAS Parallel Benchmarks

  • Yehonatan Fridman
  • , Yosef Goren
  • , Gal Oren
  • Ben-Gurion University of the Negev
  • Technion-Israel Institute of Technology
  • Stanford University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

The NAS Parallel Benchmarks (NPB) are widely used to evaluate parallel programming models, yet lack a native OpenMP offloading implementation for GPUs. This gap is significant given OpenMP’s emergence as a versatile standard for heterogeneous systems, offering broad compatibility with both current and future GPU architectures. Existing solutions, such as those that directly translate OpenACC to a binary executable, are limited by OpenACC’s stagnation and vendor-specific constraints, while not exposing OpenMP, which is used internally as an intermediate representation. This work addresses this limitation by developing a source-level translation of OpenACC-based NPB benchmarks into OpenMP5 offloading code. This translation employs a combination of automated source-to-source tool and manual optimization to ensure efficient execution across various GPU architectures. Performance evaluations indicate that the translated OpenMP versions deliver results comparable to the original OpenACC implementations, validating their reliability for GPU-based computations. Additionally, comparisons between GPU-accelerated OpenMP implementations and traditional CPU-based benchmarks reveal significant performance gains, especially in computationally intensive workloads. These findings highlight OpenMP’s potential as a unified programming model, offering superior portability and optimization capabilities across diverse hardware platforms. The sources of this work are available at our repository.

Original languageEnglish
Title of host publicationProceedings of 2025 4th International Workshop on Extreme Heterogeneity Solutions, ExHET 2025
PublisherAssociation for Computing Machinery, Inc
Pages10-18
Number of pages9
ISBN (Electronic)9798400715365
DOIs
StatePublished - 5 May 2025
Externally publishedYes
Event4th International Workshop on Extreme Heterogeneity Solutions, ExHET 2025 - Hybrid, Las Vegas, United States
Duration: 2 Mar 2025 → …

Publication series

NameProceedings of 2025 4th International Workshop on Extreme Heterogeneity Solutions, ExHET 2025

Conference

Conference4th International Workshop on Extreme Heterogeneity Solutions, ExHET 2025
Country/TerritoryUnited States
CityHybrid, Las Vegas
Period2/03/25 → …

Bibliographical note

Publisher Copyright:
© 2025 Copyright held by the owner/author(s).

Keywords

  • GPU benchmarking
  • NAS Parallel Benchmarks
  • OpenACC
  • OpenMP offloading
  • heterogeneous systems
  • performance optimization

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