An On-Line Performance Introspection Framework for Task-Based Runtime Systems

Aguilar X, Jordan H, Heller T, Hirsch A, Fahringer T, Laure E (2019)

Publication Type: Conference contribution

Publication year: 2019

Journal

Lecture Notes in Computer Science Springer Verlag

Publisher: Springer Verlag

Book Volume: 11536 LNCS

Pages Range: 238-252

Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Event location: Faro PT

ISBN: 9783030227333

DOI: 10.1007/978-3-030-22734-0_18

Abstract

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.

Authors with CRIS profile

Thomas Heller Lehrstuhl für Informatik 3 (Rechnerarchitektur)

Involved external institutions

Leopold-Franzens-Universität Innsbruck / University of Innsbruck AT Austria (AT) Royal Institute of Technology / Kungliga Tekniska Högskolan (KTH) SE Sweden (SE)

How to cite

APA:

Aguilar, X., Jordan, H., Heller, T., Hirsch, A., Fahringer, T., & Laure, E. (2019). An On-Line Performance Introspection Framework for Task-Based Runtime Systems. In João M.F. Rodrigues, Pedro J.S. Cardoso, Jânio Monteiro, Roberto Lam, Jack J. Dongarra, Valeria V. Krzhizhanovskaya, Michael H. Lees, Peter M.A. Sloot (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 238-252). Faro, PT: Springer Verlag.

MLA:

Aguilar, Xavier, et al. "An On-Line Performance Introspection Framework for Task-Based Runtime Systems." Proceedings of the 19th International Conference on Computational Science, ICCS 2019, Faro Ed. João M.F. Rodrigues, Pedro J.S. Cardoso, Jânio Monteiro, Roberto Lam, Jack J. Dongarra, Valeria V. Krzhizhanovskaya, Michael H. Lees, Peter M.A. Sloot, Springer Verlag, 2019. 238-252.

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