%0 Conference Proceedings
%T Mimir+: An Optimized Framework of MapReduce on Heterogeneous High-Performance Computing System
%+ Sun Yat-sen University [Guangzhou] (SYSU)
%A Hu, Nan
%A Chen, Zhiguang
%A Du, Yunfei
%A Lu, Yutong
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B 15th IFIP International Conference on Network and Parallel Computing (NPC)
%C Muroran, Japan
%Y Feng Zhang
%Y Jidong Zhai
%Y Marc Snir
%Y Hai Jin
%Y Hironori Kasahara
%Y Mateo Valero
%I Springer International Publishing
%3 Network and Parallel Computing
%V LNCS-11276
%P 164-168
%8 2018-11-29
%D 2018
%R 10.1007/978-3-030-05677-3_18
%K High-performance computing
%K MapReduce
%K Heterogeneous
%Z Computer Science [cs]Conference papers
%X In this paper, we present an optimized data processing framework: Mimir+. Mimir+ is an implementation of MapReduce over MPI. In order to take full advantage of heterogeneous computing system, we propose the concept of Pre-acceleration to reconstruct a heterogeneous workflow and implement the interfaces of GPU so that Mimir+ can facilitate data processing through reasonable tasks and data scheduling between CPU and GPU. We evaluate Mimir+ via two benchmarks (i.e. the WordCount and large-scale matrix multiplication) on the Tianhe-2 supercomputing system. Experimental results demonstrate that Mimir+ achieves excellent acceleration effect compared with original Mimir.
%G English
%Z TC 10
%Z WG 10.3
%2 https://inria.hal.science/hal-02279555/document
%2 https://inria.hal.science/hal-02279555/file/477597_1_En_18_Chapter.pdf
%L hal-02279555
%U https://inria.hal.science/hal-02279555
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-TC
%~ IFIP-TC10
%~ IFIP-NPC
%~ IFIP-WG10-3
%~ IFIP-LNCS-11276