Streaming Applications on Heterogeneous Platforms

Abstract : Using multiple streams can improve the overall system performance by mitigating the data transfer overhead on heterogeneous systems. Currently, very few cases have been streamed to demonstrate the streaming performance impact and a systematic investigation of streaming necessity and how-to over a large number of test cases remains a gap. In this paper, we use a total of 56 benchmarks to build a statistical view of the data transfer overhead, and give an in-depth analysis of the impacting factors. Among the heterogeneous codes, we identify two types of non-streamable codes and three types of streamable codes, for which a streaming approach has been proposed. Our experimental results on the CPU-MIC platform show that, with multiple streams, we can improve the application performance by up 90 %. Our work can serve as a generic flow of using multiple streams on heterogeneous platforms.
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Communication dans un congrès
Guang R. Gao; Depei Qian; Xinbo Gao; Barbara Chapman; Wenguang Chen. 13th IFIP International Conference on Network and Parallel Computing (NPC), Oct 2016, Xi'an, China. Springer International Publishing, Lecture Notes in Computer Science, LNCS-9966, pp.116-129, 2016, Network and Parallel Computing. 〈10.1007/978-3-319-47099-3_10〉
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Zhaokui Li, Jianbin Fang, Tao Tang, Xuhao Chen, Canqun Yang. Streaming Applications on Heterogeneous Platforms. Guang R. Gao; Depei Qian; Xinbo Gao; Barbara Chapman; Wenguang Chen. 13th IFIP International Conference on Network and Parallel Computing (NPC), Oct 2016, Xi'an, China. Springer International Publishing, Lecture Notes in Computer Science, LNCS-9966, pp.116-129, 2016, Network and Parallel Computing. 〈10.1007/978-3-319-47099-3_10〉. 〈hal-01647994〉

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