10985

Benchmarking Parallel Performance on Many-Core Processors

Bryant C. Lam, Ajay Barboza, Ravi Agrawal, Alan D. George, Herman Lam
NSF Center for High-Performance Reconfigurable Computing (CHREC), Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL 32611-6200
OpenSHMEM, 2014
@article{lam2013benchmarking,

   title={Benchmarking Parallel Performance on Many-Core Processors},

   author={Lam, Bryant C and Barboza, Ajay and Agrawal, Ravi and George, Alan D and Lam, Herman},

   year={2013}

}

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With the emergence of many-core processor architectures onto the HPC scene, concerns arise regarding the performance and productivity of numerous existing parallel-programming tools, models, and languages. As these devices begin augmenting conventional distributed cluster systems in an evolving age of heterogeneous supercomputing, proper evaluation and profiling of many-core processors must occur in order to understand their performance and architectural strengths with existing parallel-programming environments and HPC applications. This paper presents and evaluates the comparative performance between two many-core processors, the Tilera TILE-Gx8036 and the Intel Xeon Phi 5110P, in the context of their applications performance with the SHMEM and OpenMP parallel-programming environments. Several applications written or provided in SHMEM and OpenMP are evaluated in order to analyze the scalability of existing tools and libraries on these many-core platforms. Our results show that SHMEM and OpenMP parallel applications scale well on the TILE-Gx and Xeon Phi, but heavily depend on optimized libraries and instrumentation.
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