Title :
Language Features for Scalable Distributed-Memory Dataflow Computing
Author :
Wozniak, Justin M. ; Wilde, Michael ; Foster, Ian T.
Author_Institution :
Math. & Comput. Sci. Div., Argonne Nat. Lab., Argonne, IL, USA
Abstract :
Dataflow languages offer a natural means to express concurrency but are not a natural representation of the architectural features of high-performance, distributed-memory computers. When used as the outermost language in a hierarchical programming model, dataflow is very effective at expressing the overall flow of a computation. In this work, we present strategies and techniques used by the Swift dataflow language to obtain good performance on extremely large computing systems. We also present multiple unique language features that offer practical utility and performance enhancements.
Keywords :
concurrency control; data flow computing; distributed memory systems; parallel programming; software architecture; Swift dataflow language; architectural features; concurrency; dataflow languages; distributed-memory computer; hierarchical programming model; high-performance computer; language features; performance enhancements; scalable distributed-memory dataflow computing; Computational modeling; Concurrent computing; Libraries; Programming; Runtime; Syntactics; Turbines;
Conference_Titel :
Data-Flow Execution Models for Extreme Scale Computing (DFM), 2014 Fourth Workshop on
DOI :
10.1109/DFM.2014.17
