Dynamic Task Discovery in PaRSEC- A data-flow task-based Runtime

TitleDynamic Task Discovery in PaRSEC- A data-flow task-based Runtime
Publication TypeConference Proceedings
Year of Publication2017
AuthorsHoque, R., T. Herault, G. Bosilca, and J. Dongarra
Conference NameScalA17
Date Published09-2017
PublisherACM
Conference LocationDenver
ISBN Number978-1-4503-5125-6
Keywordsdata-flow, dynamic task-graph, parsec, task-based runtime
Abstract

Successfully exploiting distributed collections of heterogeneous many-cores architectures with complex memory hierarchy through a portable programming model is a challenge for application developers. The literature is not short of proposals addressing this problem, including many evolutionary solutions that seek to extend the capabilities of current message passing paradigms with intranode features (MPI+X). A different, more revolutionary, solution explores data-flow task-based runtime systems as a substitute to both local and distributed data dependencies management. The solution explored in this paper, PaRSEC, is based on such a programming paradigm, supported by a highly efficient task-based runtime. This paper compares two programming paradigms present in PaRSEC, Parameterized Task Graph (PTG) and Dynamic Task Discovery (DTD) in terms of capabilities, overhead and potential benefits.

URLhttps://dl.acm.org/citation.cfm?doid=3148226.3148233
DOI10.1145/3148226.3148233
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