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Optimizing Linpack Benchmark on GPU-Accelerated Petascale Supercomputer

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Abstract

In this paper we present the programming of the Linpack benchmark on TianHe-1 system, the first petascale supercomputer system of China, and the largest GPU-accelerated heterogeneous system ever attempted before. A hybrid programming model consisting of MPI, OpenMP and streaming computing is described to explore the task parallel, thread parallel and data parallel of the Linpack. We explain how we optimized the load distribution across the CPUs and GPUs using the two-level adaptive method and describe the implementation in details. To overcome the low-bandwidth between the CPU and GPU communication, we present a software pipelining technique to hide the communication overhead. Combined with other traditional optimizations, the Linpack we developed achieved 196:7 GFLOPS on a single compute element of TianHe-1. This result is 70:1% of the peak compute capability, 3:3 times faster than the result by using the vendor's library. On the full configuration of TianHe-1 our optimizations resulted in a Linpack performance of 0:563 PFLOPS, which made TianHe-1 the 5th fastest supercomputer on the Top500 list in November, 2009.

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Authors and Affiliations

  1. School of Computer Science, National University of Defense Technology, Changsha, 410073, China

    Feng Wang (Member, CCF, ACM), Can-Qun Yang, Yun-Fei Du, Juan Chen, Hui-Zhan Yi & Wei-Xia Xu

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  1. Feng Wang
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  2. Can-Qun Yang
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  3. Yun-Fei Du
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  4. Juan Chen
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  5. Hui-Zhan Yi
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  6. Wei-Xia Xu
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Corresponding author

Correspondence to Feng Wang.

Additional information

Supported by the National High Technology Research and Development 863 Program of China under Grant No. 2009AA01A128, the Major Science and Technology Project of China under Grant No. 2009ZX01036-001-003-001, the National Natural Science Foundation of China under Grant Nos. 61003087, 60903044, 60903059, 60970033, and 60673150.

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Wang, F., Yang, CQ., Du, YF. et al. Optimizing Linpack Benchmark on GPU-Accelerated Petascale Supercomputer. J. Comput. Sci. Technol. 26, 854–865 (2011). https://doi.org/10.1007/s11390-011-0184-1

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