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FastMPJ: a scalable and efficient Java message-passing library

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Abstract

The performance and scalability of communications are key for high performance computing (HPC) applications in the current multi-core era. Despite the significant benefits (e.g., productivity, portability, multithreading) of Java for parallel programming, its poor communications support has hindered its adoption in the HPC community. This paper presents FastMPJ, an efficient message-passing in Java (MPJ) library, boosting Java for HPC by: (1) providing high-performance shared memory communications using Java threads; (2) taking full advantage of high-speed cluster networks (e.g., InfiniBand) to provide low-latency and high bandwidth communications; (3) including a scalable collective library with topology aware primitives, automatically selected at runtime; (4) avoiding Java data buffering overheads through zero-copy protocols; and (5) implementing the most widely extended MPI-like Java bindings for a highly productive development. The comprehensive performance evaluation on representative testbeds (InfiniBand, 10 Gigabit Ethernet, Myrinet, and shared memory systems) has shown that FastMPJ communication primitives rival native MPI implementations, significantly improving the efficiency and scalability of Java HPC parallel applications.

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Acknowledgments

This work has been funded by the Ministry of Education of Spain (FPU Grant AP2010-4348), the Ministry of Economy and Competitiviness (project TIN2010-16735) and the Galician Government (projects CN2012/211 and GRC2013/055), partially supported by FEDER funds. We thankfully acknowledge the computer resources, technical expertise and assistance provided by the Barcelona Supercomputing Center. We also gratefully thank the Advanced School for Computing and Imaging (ASCI) and the Vrije University Amsterdam for providing access to the DAS-4 cluster.

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Correspondence to Roberto R. Expósito.

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Expósito, R.R., Ramos, S., Taboada, G.L. et al. FastMPJ: a scalable and efficient Java message-passing library. Cluster Comput 17, 1031–1050 (2014). https://doi.org/10.1007/s10586-014-0345-4

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