research-article

OpenMP to GPGPU: a compiler framework for automatic translation and optimization

Authors:

Rudolf EigenmannAuthors Info & Claims

ACM SIGPLAN Notices, Volume 44, Issue 4

Pages 101 - 110

https://doi.org/10.1145/1594835.1504194

Published: 14 February 2009 Publication History

Abstract

GPGPUs have recently emerged as powerful vehicles for general-purpose high-performance computing. Although a new Compute Unified Device Architecture (CUDA) programming model from NVIDIA offers improved programmability for general computing, programming GPGPUs is still complex and error-prone. This paper presents a compiler framework for automatic source-to-source translation of standard OpenMP applications into CUDA-based GPGPU applications. The goal of this translation is to further improve programmability and make existing OpenMP applications amenable to execution on GPGPUs. In this paper, we have identified several key transformation techniques, which enable efficient GPU global memory access, to achieve high performance. Experimental results from two important kernels (JACOBI and SPMUL) and two NAS OpenMP Parallel Benchmarks (EP and CG) show that the described translator and compile-time optimizations work well on both regular and irregular applications, leading to performance improvements of up to 50X over the unoptimized translation (up to 328X over serial).

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Mustafa DAlkhasawneh RObeidat FShatnawi A(2024)MIMD Programs Execution Support on SIMD Machines: A Holistic SurveyIEEE Access10.1109/ACCESS.2024.337299012(34354-34377)Online publication date: 2024
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Gazda AKoska O(2024)A pragma based C++ framework for hybrid quantum/classical computationScience of Computer Programming10.1016/j.scico.2024.103119236(103119)Online publication date: Sep-2024
https://doi.org/10.1016/j.scico.2024.103119
Krishnakumar AOgras UMarculescu RKishinevsky MMudge T(2023)Domain-Specific Architectures: Research Problems and Promising ApproachesACM Transactions on Embedded Computing Systems10.1145/356394622:2(1-26)Online publication date: 24-Jan-2023
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Index Terms

OpenMP to GPGPU: a compiler framework for automatic translation and optimization
1. Software and its engineering
  1. Software notations and tools
    1. Compilers
      1. Source code generation

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Published In

cover image ACM SIGPLAN Notices

ACM SIGPLAN Notices Volume 44, Issue 4

PPoPP '09

April 2009

294 pages

ISSN:0362-1340

EISSN:1558-1160

DOI:10.1145/1594835

Issue’s Table of Contents

PPoPP '09: Proceedings of the 14th ACM SIGPLAN symposium on Principles and practice of parallel programming
February 2009
322 pages
ISBN:9781605583976
DOI:10.1145/1504176
General Chair:
Daniel Reed
Microsoft Research, USA
,
Program Chair:
Vivek Sarkar
Rice University, USA

Copyright © 2009 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Publication History

Published: 14 February 2009

Published in SIGPLAN Volume 44, Issue 4

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Gazda AKoska O(2024)A pragma based C++ framework for hybrid quantum/classical computationScience of Computer Programming10.1016/j.scico.2024.103119236(103119)Online publication date: Sep-2024
https://doi.org/10.1016/j.scico.2024.103119
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https://dl.acm.org/doi/10.1145/3563946
Tinnerholm JPop ASjölund M(2022)A Modular, Extensible, and Modelica-Standard-Compliant OpenModelica Compiler Framework in Julia Supporting Structural VariabilityElectronics10.3390/electronics1111177211:11(1772)Online publication date: 2-Jun-2022
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Bhosale ABarakhshan PRosas MEigenmann R(2022)Automatic and Interactive Program Parallelization Using the Cetus Source to Source Compiler Infrastructure v2.0Electronics10.3390/electronics1105080911:5(809)Online publication date: 4-Mar-2022
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