short-paper

In Situ Workflows at Exascale: System Software to the Rescue

Authors:

Matthieu Dreher,

Swann Perarnau,

Pete BeckmanAuthors Info & Claims

ISAV'17: Proceedings of the In Situ Infrastructures on Enabling Extreme-Scale Analysis and Visualization

Pages 22 - 26

https://doi.org/10.1145/3144769.3144774

Published: 12 November 2017 Publication History

Abstract

Implementing an in situ workflow involves several challenges related to data placement, task scheduling, efficient communications, scalability, and reliability. Most of the current implementations provide reasonably performant solutions to these issues by focusing on high-performance communications and low-overhead execution models at the cost of reliability and flexibility.

One of the key design choices in such infrastructures is between providing a single-program, integrated environment or a multiple-program, connected environment, both solutions having their own strengths and weaknesses. While these approaches might be appropriate for current production systems, the expected characteristics of exascale machines will shift current priorities.

After a survey of the trade-offs and challenges of integrated and connected in situ workflow solutions available today, we discuss in this paper how exascale systems will impact those designs. In particular, we identify missing features of current system-level software required for the evolution of in situ workflows toward exascale and how system software innovations from the Argo Exascale Computing Project can help address those challenges.

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Cited By

Peterka TBard DBennett JBethel EOldfield RPouchard LSweeney CWolf M(2020)Priority research directions for in situ data managementInternational Journal of High Performance Computing Applications10.1177/109434202091362834:4(409-427)Online publication date: 1-Jul-2020
https://dl.acm.org/doi/10.1177/1094342020913628

Index Terms

In Situ Workflows at Exascale: System Software to the Rescue
1. Computing methodologies
  1. Concurrent computing methodologies
    1. Concurrent programming languages
2. Software and its engineering
  1. Software organization and properties
    1. Extra-functional properties
      1. Software reliability
    2. Software system structures
      1. Software architectures
        Data flow architectures

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cover image ACM Conferences

ISAV'17: Proceedings of the In Situ Infrastructures on Enabling Extreme-Scale Analysis and Visualization

November 2017

53 pages

ISBN:9781450351393

DOI:10.1145/3144769

Copyright © 2017 ACM.

Publication rights licensed to ACM. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of the United States government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 November 2017

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Short-paper
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Refereed limited

Funding Sources

Advanced Scientific Computing Research, Office of Science, U.S. Department of Energy

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SC '17

Sponsor:

SIGHPC

SC '17: The International Conference for High Performance Computing, Networking, Storage and Analysis

November 12 - 17, 2017

CO, Denver, USA

Acceptance Rates

ISAV'17 Paper Acceptance Rate 9 of 28 submissions, 32%;

Overall Acceptance Rate 23 of 63 submissions, 37%

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Cited By

Peterka TBard DBennett JBethel EOldfield RPouchard LSweeney CWolf M(2020)Priority research directions for in situ data managementInternational Journal of High Performance Computing Applications10.1177/109434202091362834:4(409-427)Online publication date: 1-Jul-2020
https://dl.acm.org/doi/10.1177/1094342020913628

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