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Online Fault Classification in HPC Systems Through Machine Learning Read chapter Read first chapter

2019 | OriginalPaper | Chapter

Dataflow Execution of Hierarchically Tiled Arrays

Authors : Chih-Chieh Yang, Juan C. Pichel, David A. Padua

Published in: Euro-Par 2019: Parallel Processing

Publisher: Springer International Publishing

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Abstract

As the parallelism in high-performance supercomputers continues to grow, new programming models become necessary to maintain programmer productivity at today’s levels. Dataflow is a promising execution model because it can represent parallelism at different granularity levels and to dynamically adapt for efficient execution. The downside is the low-level programming interface inherent to dataflow. We present a strategy to translate programs written in Hierarchically Tiled Arrays (HTA) to the dataflow API of Open Community Runtime (OCR) system. The goal is to enable program development in a convenient notation and at the same time take advantage of the benefits of a dataflow runtime system. Using HTA produces more comprehensive codes than those written using the dataflow runtime programming interface. Moreover, the experiments show that, for applications with high asynchrony and sparse data dependences, our implementation delivers superior performance than OpenMP using parallel for loops.

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Metadata
Title
Dataflow Execution of Hierarchically Tiled Arrays
Authors
Chih-Chieh Yang
Juan C. Pichel
David A. Padua
Copyright Year
2019
Book
Euro-Par 2019: Parallel Processing

Print ISBN: 978-3-030-29399-4

Electronic ISBN: 978-3-030-29400-7

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-030-29400-7_22

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