skip to main content
poster

OpenCL as a unified programming model for heterogeneous CPU/GPU clusters

Authors Info & Claims
Published:25 February 2012Publication History
Skip Abstract Section

Abstract

In this paper, we propose an OpenCL framework for heterogeneous CPU/GPU clusters, and show that the framework achieves both high performance and ease of programming. The framework provides an illusion of a single system for the user. It allows the application to utilize multiple heterogeneous compute devices, such as multicore CPUs and GPUs, in a remote node as if they were in a local node. No communication API, such as the MPI library, is required in the application source. We implement the OpenCL framework and evaluate its performance on a heterogeneous CPU/GPU cluster that consists of one host node and nine compute nodes using eleven OpenCL benchmark applications.

References

  1. AMD Accelerated Parallel Processing (APP) SDK With OpenCL 1.1 Support. AMD, 2011. http://developer.amd.com/sdks/AMDAPPSDK/Pages/default.aspx.Google ScholarGoogle Scholar
  2. C. Bienia, S. Kumar, J. P. Singh, and K. Li. The PARSEC benchmark suite: characterization and architectural implications. In Proceedings of the 17th international conference on Parallel architectures and compilation techniques, PACT '08, pages 72--81, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. The OpenCL Specification Version 1.1. Khronos OpenCL Working Group, 2010. http://www.khronos.org/opencl.Google ScholarGoogle Scholar
  4. C. Lattner and V. Adve. LLVM: A Compilation Framework for Lifelong Program Analysis & Transformation. In Proceedings of the international symposium on Code generation and optimization: feedback-directed and runtime optimization, CGO '04, pages 75--86, 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. J. Lee, J. Kim, S. Seo, S. Kim, J. Park, H. Kim, T. T. Dao, Y. Cho, S. J. Seo, S. H. Lee, S. M. Cho, H. J. Song, S.-B. Suh, and J.-D. Choi. An OpenCL framework for heterogeneous multicores with local memory. In Proceedings of the 19th international conference on Parallel architectures and compilation techniques, PACT '10, pages 193--204, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. NVIDIA. NVIDIA CUDA Toolkit 4.0. http://developer.nvidia.com/cuda-toolkit-40.Google ScholarGoogle Scholar
  7. S. Seo, G. Jo, and J. Lee. Performance Characterization of the NAS Parallel Benchmarks in OpenCL. In Proceedings of the 2011 IEEE International Symposium on Workload Characterization, IISWC '11, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. The IMPACT Research Group. Parboil Benchmark suite. http://impact.crhc.illinois.edu/parboil.php.Google ScholarGoogle Scholar

Index Terms

  1. OpenCL as a unified programming model for heterogeneous CPU/GPU clusters

          Recommendations

          Comments

          Login options

          Check if you have access through your login credentials or your institution to get full access on this article.

          Sign in

          Full Access

          • Published in

            cover image ACM SIGPLAN Notices
            ACM SIGPLAN Notices  Volume 47, Issue 8
            PPOPP '12
            August 2012
            334 pages
            ISSN:0362-1340
            EISSN:1558-1160
            DOI:10.1145/2370036
            Issue’s Table of Contents
            • cover image ACM Conferences
              PPoPP '12: Proceedings of the 17th ACM SIGPLAN symposium on Principles and Practice of Parallel Programming
              February 2012
              352 pages
              ISBN:9781450311601
              DOI:10.1145/2145816

            Copyright © 2012 Authors

            Publisher

            Association for Computing Machinery

            New York, NY, United States

            Publication History

            • Published: 25 February 2012

            Check for updates

            Qualifiers

            • poster

          PDF Format

          View or Download as a PDF file.

          PDF

          eReader

          View online with eReader.

          eReader
          About Cookies On This Site

          We use cookies to ensure that we give you the best experience on our website.

          Learn more

          Got it!