Swift/T: Large-scale application composition via distributed-memory dataflow processing

Justin M. Wozniak, Timothy G. Armstrong, Michael Wilde, Daniel S. Katz, Ewing Lusk, Ian T. Foster

Research output: Contribution to conferencePaperpeer-review


Many scientific applications are conceptually built up from independent component tasks as a parameter study, optimization, or other search. Large batches of these tasks may be executed on high-end computing systems; however, the coordination of the independent processes, their data, and their data dependencies is a significant scalability challenge. Many problems must be addressed, including load balancing, data distribution, notifications, concurrent programming, and linking to existing codes. In this work, we present Swift/T, a programming language and runtime that enables the rapid development of highly concurrent, task-parallel applications. Swift/T is composed of several enabling technologies to address scalability challenges, offers a high-level optimizing compiler for user programming and debugging, and provides tools for binding user code in C/C++/Fortran into a logical script. In this work, we describe the Swift/T solution and present scaling results from the IBM Blue Gene/P and Blue Gene/Q.

Original languageEnglish (US)
Number of pages8
StatePublished - 2013
Externally publishedYes
Event13th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, CCGrid 2013 - Delft, Netherlands
Duration: May 13 2013May 16 2013


Other13th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, CCGrid 2013

ASJC Scopus subject areas

  • Software

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