Title:
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A high-productivity task-based programming model for clusters
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Author:
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Tejedor, Enric; Farreras Esclusa, Montserrat; Grove, David; Badia Sala, Rosa Maria; Almási, George; Labarta Mancho, Jesús José
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Other authors:
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Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors; Universitat Politècnica de Catalunya. CAP - Grup de Computació d'Altes Prestacions |
Abstract:
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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 |
Abstract:
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Peer Reviewed |
Subject(s):
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-Àrees temàtiques de la UPC::Informàtica::Arquitectura de computadors::Arquitectures distribuïdes -Computational grids (Computer systems) -asynchronous execution -high performance computing -parallel programming models -productivity -Computació distribuïda |
Rights:
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Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
Document type:
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Article - Published version Article |
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