OpenARC: Open Accelerator Research Compiler for directive-based, efficient heterogeneous computing

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54 Scopus citations

Abstract

This paper presents Open Accelerator Research Compiler (OpenARC): an open-source framework that supports the full feature set of OpenACC V1.0 and performs source-tosource transformations, targeting heterogeneous devices, such as NVIDIA GPUs. Combined with its high-level, extensible Intermediate Representation (IR) and rich semantic annotations, OpenARC serves as a powerful research vehicle for prototyping optimization, source-to-source transformations, and instrumentation for debugging, performance analysis, and autotuning. Infact, OpenARC is equipped with various capabilities for advanced analyses and transformations, as well as built-in performance and debugging tools. We explain the overall design and implementation of OpenARC, and we present key analysis techniques necessary to efficiently port OpenACC applications. Porting various OpenACC applications to CUDA GPUs using OpenARC demonstrates that OpenARC performs similarly to a commercial compiler, while serving as a general research framework.

Original languageEnglish
Title of host publicationHPDC 2014 - Proceedings of the 23rd International Symposium on High-Performance Parallel and Distributed Computing
PublisherAssociation for Computing Machinery
Pages115-119
Number of pages5
ISBN (Print)9781450327480
DOIs
StatePublished - 2014
Event23rd ACM Symposium on High-Performance Parallel and Distributed Computing, HPDC 2014 - Vancouver, BC, Canada
Duration: Jun 23 2014Jun 27 2014

Publication series

NameHPDC 2014 - Proceedings of the 23rd International Symposium on High-Performance Parallel and Distributed Computing

Conference

Conference23rd ACM Symposium on High-Performance Parallel and Distributed Computing, HPDC 2014
Country/TerritoryCanada
CityVancouver, BC
Period06/23/1406/27/14

Keywords

  • CUDA
  • Compiler
  • GPU
  • OpenACC
  • OpenARC
  • Source-to-source translation

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