A high-productivity task-based programming model for clusters

SUMMARY Programming for large‐scale, multicore‐based architectures requires adequate tools that offer ease of programming and do not hinder application performance. StarSs is a family of parallel programming models based on automatic function‐level parallelism that targets productivity. StarSs deplo...

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Bibliographic Details
Published in:Concurrency and computation Vol. 24; no. 18; pp. 2421 - 2448
Main Authors: Tejedor, Enric, Farreras, Montse, Grove, David, Badia, Rosa M., Almasi, Gheorghe, Labarta, Jesus
Format: Journal Article Publication
Language:English
Published: Chichester, UK John Wiley & Sons, Ltd 25-12-2012
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Summary:SUMMARY Programming for large‐scale, multicore‐based architectures requires adequate tools that offer ease of programming and do not hinder application performance. StarSs is a family of parallel programming models based on automatic function‐level parallelism that targets productivity. StarSs deploys a data‐flow model: it analyzes dependencies between tasks and manages their execution, exploiting their concurrency as much as possible. This paper introduces Cluster Superscalar (ClusterSs), a new StarSs member designed to execute on clusters of SMPs (Symmetric Multiprocessors). ClusterSs tasks are asynchronously created and assigned to the available resources with the support of the IBM APGAS runtime, which provides an efficient and portable communication layer based on one‐sided communication. We present the design of ClusterSs on top of APGAS, as well as the programming model and execution runtime for Java applications. Finally, we evaluate the productivity of ClusterSs, both in terms of programmability and performance and compare it to that of the IBM X10 language. Copyright © 2012 John Wiley & Sons, Ltd.
Bibliography:Spanish Ministry of Science and Innovation - No. TIN2007-60625; No. CSD2007-00050
European Commission in the context of the HiPEAC Network of Excellence - No. IST-004408
HPC-Europa2 Research Infrastructure - No. 222398
ark:/67375/WNG-03W5QCDP-9
ArticleID:CPE2831
istex:9D8737CA31B683BB53A89BEE22222B8485C3E0BE
ISSN:1532-0626
1532-0634
DOI:10.1002/cpe.2831