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The Scalable Heterogeneous Computing (SHOC) benchmark suite

Published: 14 March 2010 Publication History
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  • Abstract

    Scalable heterogeneous computing systems, which are composed of a mix of compute devices, such as commodity multicore processors, graphics processors, reconfigurable processors, and others, are gaining attention as one approach to continuing performance improvement while managing the new challenge of energy efficiency. As these systems become more common, it is important to be able to compare and contrast architectural designs and programming systems in a fair and open forum. To this end, we have designed the Scalable HeterOgeneous Computing benchmark suite (SHOC). SHOC's initial focus is on systems containing graphics processing units (GPUs) and multi-core processors, and on the new OpenCL programming standard. SHOC is a spectrum of programs that test the performance and stability of these scalable heterogeneous computing systems. At the lowest level, SHOC uses microbenchmarks to assess architectural features of the system. At higher levels, SHOC uses application kernels to determine system-wide performance including many system features such as intranode and internode communication among devices. SHOC includes benchmark implementations in both OpenCL and CUDA in order to provide a comparison of these programming models.

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        cover image ACM Other conferences
        GPGPU-3: Proceedings of the 3rd Workshop on General-Purpose Computation on Graphics Processing Units
        March 2010
        124 pages
        ISBN:9781605589350
        DOI:10.1145/1735688
        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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        Published: 14 March 2010

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        Author Tags

        1. GPGPU
        2. benchmarking
        3. graphics processors
        4. performance

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        • (2024)Breaking Barriers: Expanding GPU Memory with Sub-Two Digit Nanosecond Latency CXL ControllerProceedings of the 16th ACM Workshop on Hot Topics in Storage and File Systems10.1145/3655038.3665953(108-115)Online publication date: 8-Jul-2024
        • (2024)SYCL-Bench 2020: Benchmarking SYCL 2020 on AMD, Intel, and NVIDIA GPUsProceedings of the 12th International Workshop on OpenCL and SYCL10.1145/3648115.3648120(1-12)Online publication date: 8-Apr-2024
        • (2024)Covert-channels in FPGA-enabled SmartSSDsACM Transactions on Reconfigurable Technology and Systems10.1145/363531217:2(1-23)Online publication date: 30-Apr-2024
        • (2024)Energy-minimizing workload splitting and frequency selection for guaranteed performance over heterogeneous coresProceedings of the 15th ACM International Conference on Future and Sustainable Energy Systems10.1145/3632775.3661968(308-322)Online publication date: 4-Jun-2024
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        • (2024)GRIT: Enhancing Multi-GPU Performance with Fine-Grained Dynamic Page Placement2024 IEEE International Symposium on High-Performance Computer Architecture (HPCA)10.1109/HPCA57654.2024.00085(1080-1094)Online publication date: 2-Mar-2024
        • (2024)Supporting Secure Multi-GPU Computing with Dynamic and Batched Metadata Management2024 IEEE International Symposium on High-Performance Computer Architecture (HPCA)10.1109/HPCA57654.2024.00025(204-217)Online publication date: 2-Mar-2024
        • (2024)Utilizing Machine Learning Techniques for Worst-Case Execution Time Estimation on GPU ArchitecturesIEEE Access10.1109/ACCESS.2024.337901812(41464-41478)Online publication date: 2024
        • (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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