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An On-Line Performance Introspection Framework for Task-Based Runtime Systems
KTH, Centres, SeRC - Swedish e-Science Research Centre. KTH, School of Electrical Engineering and Computer Science (EECS), Computational Science and Technology (CST).ORCID iD: 0000-0001-9693-6265
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2019 (English)In: 19th International Conference on Computational Science, ICCS 2019, Springer Verlag , 2019, p. 238-252Conference paper, Published paper (Refereed)
Abstract [en]

The expected high levels of parallelism together with the heterogeneity and complexity of new computing systems pose many challenges to current software. New programming approaches and runtime systems that can simplify the development of parallel applications are needed. Task-based runtime systems have emerged as a good solution to cope with high levels of parallelism, while providing software portability, and easing program development. However, these runtime systems require real-time information on the state of the system to properly orchestrate program execution and optimise resource utilisation. In this paper, we present a lightweight monitoring infrastructure developed within the AllScale Runtime System, a task-based runtime system for extreme scale. This monitoring component provides real-time introspection capabilities that help the runtime scheduler in its decision-making process and adaptation, while introducing minimum overhead. In addition, the monitoring component provides several post-mortem reports as well as real-time data visualisation that can be of great help in the task of performance debugging.

Place, publisher, year, edition, pages
Springer Verlag , 2019. p. 238-252
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 11536
Keywords [en]
AllScale, HPX, Performance introspection, Performance monitoring, Real-time visualisation, Runtime system, Computer software portability, Computer systems programming, Data visualization, Decision making, Visualization, Real time, Runtime systems, Real time systems
National Category
Computational Mathematics
Identifiers
URN: urn:nbn:se:kth:diva-262387DOI: 10.1007/978-3-030-22734-0_18Scopus ID: 2-s2.0-85067610766ISBN: 9783030227333 (print)OAI: oai:DiVA.org:kth-262387DiVA, id: diva2:1366042
Conference
19th International Conference on Computational Science, ICCS 2019, Faro, Portugal, 12-14 June 2019
Note

QC 20191028

Available from: 2019-10-28 Created: 2019-10-28 Last updated: 2019-10-28Bibliographically approved

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Aguilar, XavierLaure, Erwin

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CiteExportLink to record
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Citation style
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Output format
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