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MPI Streams for HPC Applications
KTH, School of Electrical Engineering and Computer Science (EECS), Computational Science and Technology (CST).ORCID iD: 0000-0003-4158-3583
KTH, School of Electrical Engineering and Computer Science (EECS), Computational Science and Technology (CST).ORCID iD: 0000-0003-0639-0639
Pacific Northwest Natl Lab, Computat Sci & Math Div, Richland, WA 99352 USA..
Pacific Northwest Natl Lab, Computat Sci & Math Div, Richland, WA 99352 USA..
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2017 (English)In: NEW FRONTIERS IN HIGH PERFORMANCE COMPUTING AND BIG DATA / [ed] Fox, G Getov, V Grandinetti, L Joubert, G Sterling, T, IOS PRESS , 2017, p. 75-92Conference paper, Published paper (Refereed)
Abstract [en]

Data streams are a sequence of data flowing between source and destination processes. Streaming is widely used for signal, image and video processing for its efficiency in pipelining and effectiveness in reducing demand for memory. The goal of this work is to extend the use of data streams to support both conventional scientific applications and emerging data analytics applications running on HPC platforms. We introduce an extension called MPIStream to the de-facto programming standard on HPC, MPI. MPIStream supports data streams either within a single application or among multiple applications. We present three use cases using MPI streams in HPC applications together with their parallel performance. We show the convenience of using MPI streams to support the needs from both traditional HPC and emerging data analytics applications running on supercomputers.

Place, publisher, year, edition, pages
IOS PRESS , 2017. p. 75-92
Series
Advances in Parallel Computing, ISSN 0927-5452 ; 30
Keywords [en]
Streaming Computing, MPI, MapReduce, Particle-in-Cell code, Parallel I/O, LHC
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:kth:diva-239866DOI: 10.3233/978-1-61499-816-7-75ISI: 000450329200004Scopus ID: 2-s2.0-85046361827ISBN: 978-1-61499-816-7 (print)ISBN: 978-1-61499-815-0 (print)OAI: oai:DiVA.org:kth-239866DiVA, id: diva2:1270574
Conference
International Research Workshop on Advanced High Performance Computing Systems, JUL, 2016, Cetraro, ITALY
Note

QC 20181213

Available from: 2018-12-13 Created: 2018-12-13 Last updated: 2018-12-13Bibliographically approved

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Peng, Ivy BoMarkidis, StefanoLaure, Erwin

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