Abstract
Heterogeneous architectures with both conventional CPUs and coprocessors become popular in the design of High Performance Computing systems. The programming problems on such architectures are frequently studied. OpenACC standard is proposed to tackle the problem by employing directive-based high-level programming for coprocessors. In this paper, we take advantage of OpenACC to program on the newly Intel MIC coprocessor. We achieve this by automatically translating the OpenACC source code to Intel Offload code. Two optimizations including communication and SIMD optimization are employed. Two kernels i.e. the matrix multiplication and JACOBI, are studied on the MIC-based platform (one knight Corner card) and the GPU-based platform (one NVIDIA Tesla k20c card). Performance evaluation shows that both kernels delivers a speedup of approximately 3 on one knight Corner card than on one Intel Xeon E5-2670 octal-core CPU. Moreover, the two kernels gain better performance on MIC-based platform than on the GPU-based one.
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Chen, C., Yang, C., Tang, T., Wu, Q., Zhang, P. (2013). OpenACC to Intel Offload: Automatic Translation and Optimization. In: Xu, W., Xiao, L., Zhang, C., Li, J., Yu, L. (eds) Computer Engineering and Technology. NCCET 2013. Communications in Computer and Information Science, vol 396. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41635-4_12
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DOI: https://doi.org/10.1007/978-3-642-41635-4_12
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