Heterogeneous streaming

Chris J. Newburn, Gaurav Bansal, Michael Wood, Luis Crivelli, Judit Planas, Alejandro Duran, Paulo Souza, Leonardo Borges, Piotr Luszczek, Stanimire Tomov, Jack Dongarra, Hartwig Anzt, Mark Gates, Azzam Haidar, Yulu Jia, Khairul Kabir, Ichitaro Yamazaki, Jesus Labarta

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

15 Scopus citations

Abstract

This paper introduces a new heterogeneous streaminglibrary called hetero Streams (hStreams). We show how asimple FIFO streaming model can be applied to heterogeneoussystems that include manycore coprocessors and multicore CPUs. This model supports concurrency across nodes, among taskswithin a node, and between data transfers and computation. Wegive examples for different approaches, show how the implementation can be layered, analyze overheads among layers, and apply those models to parallelize applications using simple, intuitive interfaces. We compare the features and versatility of hStreams, OpenMP, CUDA Streams and OmpSs. We show how the use of hStreams makes it easier for scientists to identify tasks and easily expose concurrency among them, and how it enables tuning experts and runtime systems to tailor execution for differentheterogeneous targets. Practical application examples are takenfrom the field of numerical linear algebra, commercial structuralsimulation software, and a seismic processing application.

Original languageEnglish
Title of host publicationProceedings - 2016 IEEE 30th International Parallel and Distributed Processing Symposium, IPDPS 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages611-620
Number of pages10
ISBN (Electronic)9781509021406
DOIs
StatePublished - Jul 18 2016
Event30th IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2016 - Chicago, United States
Duration: May 23 2016May 27 2016

Publication series

NameProceedings - 2016 IEEE 30th International Parallel and Distributed Processing Symposium, IPDPS 2016

Conference

Conference30th IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2016
Country/TerritoryUnited States
CityChicago
Period05/23/1605/27/16

Keywords

  • Concurrency
  • Heterogeneous
  • Offload
  • Streaming
  • Task parallelism

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