research-article

Skeletons for distributed topological computation

Authors:

Fouzhan HosseiniAuthors Info & Claims

FHPC 2015: Proceedings of the 4th ACM SIGPLAN Workshop on Functional High-Performance Computing

Pages 35 - 44

https://doi.org/10.1145/2808091.2808095

Published: 30 August 2015 Publication History

Abstract

Parallel implementation of topological algorithms is highly desirable, but the challenges, from reconstructing algorithms around independent threads through to runtime load balancing, have proven to be formidable. This problem, made all the more acute by the diversity of hardware platforms, has led to new kinds of implementation platform for computational science, with sophisticated runtime systems managing and coordinating large threadcounts to keep processing elements heavily utilized. While simpler and more portable than direct management of threads, these approaches still entangle program logic with resource management. Similar kinds of highly parallel runtime system have also been developed for functional languages. Here, however, language support for higher-order functions allows a cleaner separation between the algorithm and `skeletons' that express generic patterns of parallel computation. We report results on using this technique to develop a distributed version of the Joint Contour Net, a generalization of the Contour Tree to multifields. We present performance comparisons against a recent Haskell implementation using shared-memory parallelism, and initial work on a skeleton for distributed memory implementation that utilizes an innovative strategy to reduce inter-process communication overheads.

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Cited By

Xia JYe FZhou FChen YKui X(2019)Visual Identification and Extraction of Intrinsic Axes in High-Dimensional DataIEEE Access10.1109/ACCESS.2019.29229977(79565-79578)Online publication date: 2019
https://doi.org/10.1109/ACCESS.2019.2922997
P. Thomas DBorgo RS. Laramee RJ. Hands S(2018)Topological Visualisation Techniques for Volume Multifield DataComputer Graphics and Imaging [Working Title]10.5772/intechopen.82185Online publication date: 13-Dec-2018
https://doi.org/10.5772/intechopen.82185
Liu SMaljovec DWang BBremer PPascucci V(2017)Visualizing High-Dimensional DataIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2016.264096023:3(1249-1268)Online publication date: 1-Mar-2017
https://dl.acm.org/doi/10.1109/TVCG.2016.2640960

Index Terms

Skeletons for distributed topological computation
1. Software and its engineering
  1. Software notations and tools
    1. General programming languages
      1. Language types
        Functional languages

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cover image ACM Conferences

FHPC 2015: Proceedings of the 4th ACM SIGPLAN Workshop on Functional High-Performance Computing

August 2015

54 pages

ISBN:9781450338073

DOI:10.1145/2808091

Program Chairs:
Tiark Rompf,
Geoffrey Mainland

Copyright © 2015 ACM.

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Published: 30 August 2015

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Engineering and Physical Sciences Research Council

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ICFP'15

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ICFP'15: 20th ACM SIGPLAN International Conference on Functional Programming

September 3, 2015

BC, Vancouver, Canada

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Overall Acceptance Rate 18 of 25 submissions, 72%

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Cited By

Xia JYe FZhou FChen YKui X(2019)Visual Identification and Extraction of Intrinsic Axes in High-Dimensional DataIEEE Access10.1109/ACCESS.2019.29229977(79565-79578)Online publication date: 2019
https://doi.org/10.1109/ACCESS.2019.2922997
P. Thomas DBorgo RS. Laramee RJ. Hands S(2018)Topological Visualisation Techniques for Volume Multifield DataComputer Graphics and Imaging [Working Title]10.5772/intechopen.82185Online publication date: 13-Dec-2018
https://doi.org/10.5772/intechopen.82185
Liu SMaljovec DWang BBremer PPascucci V(2017)Visualizing High-Dimensional DataIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2016.264096023:3(1249-1268)Online publication date: 1-Mar-2017
https://dl.acm.org/doi/10.1109/TVCG.2016.2640960

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