A real-time scheduling service for parallel tasks

David Ferry; Jing Li; Mahesh Mahadevan; Kunal Agrawal; Christopher Gill; Chenyang Lu

doi:10.1109/RTAS.2013.6531098

A real-time scheduling service for parallel tasks

David Ferry, Jing Li, Mahesh Mahadevan, Kunal Agrawal, Christopher Gill, Chenyang Lu

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

51 Scopus citations

Abstract

The multi-core revolution presents both opportunities and challenges for real-time systems. Parallel computing can yield significant speedup for individual tasks (enabling shorter deadlines, or more computation within the same deadline), but unless managed carefully may add complexity and overhead that could potentially wreck real-time performance. There is little experience to date with the design and implementation of realtime systems that allow parallel tasks, yet the state of the art cannot progress without the construction of such systems. In this work we describe the design and implementation of a scheduler and runtime dispatcher for a new concurrency platform, RT-OpenMP, whose goal is the execution of real-time workloads with intra-task parallelism.

Original language	English (US)
Title of host publication	2013 IEEE 19th Real-Time and Embedded Technology and Applications Symposium, RTAS 2013
Pages	261-272
Number of pages	12
DOIs	https://doi.org/10.1109/RTAS.2013.6531098
State	Published - 2013
Externally published	Yes
Event	2013 IEEE 19th Real-Time and Embedded Technology and Applications Symposium, RTAS 2013 - Philadelphia, PA, United States Duration: Apr 9 2013 → Apr 11 2013

Publication series

Name	Real-Time Technology and Applications - Proceedings
ISSN (Print)	1080-1812

Other

Other	2013 IEEE 19th Real-Time and Embedded Technology and Applications Symposium, RTAS 2013
Country/Territory	United States
City	Philadelphia, PA
Period	4/9/13 → 4/11/13

All Science Journal Classification (ASJC) codes

Computer Networks and Communications
Hardware and Architecture
Software

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10.1109/RTAS.2013.6531098

Cite this

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title = "A real-time scheduling service for parallel tasks",

abstract = "The multi-core revolution presents both opportunities and challenges for real-time systems. Parallel computing can yield significant speedup for individual tasks (enabling shorter deadlines, or more computation within the same deadline), but unless managed carefully may add complexity and overhead that could potentially wreck real-time performance. There is little experience to date with the design and implementation of realtime systems that allow parallel tasks, yet the state of the art cannot progress without the construction of such systems. In this work we describe the design and implementation of a scheduler and runtime dispatcher for a new concurrency platform, RT-OpenMP, whose goal is the execution of real-time workloads with intra-task parallelism.",

author = "David Ferry and Jing Li and Mahesh Mahadevan and Kunal Agrawal and Christopher Gill and Chenyang Lu",

note = "Copyright: Copyright 2013 Elsevier B.V., All rights reserved.; 2013 IEEE 19th Real-Time and Embedded Technology and Applications Symposium, RTAS 2013 ; Conference date: 09-04-2013 Through 11-04-2013",

year = "2013",

doi = "10.1109/RTAS.2013.6531098",

language = "English (US)",

isbn = "9781479901869",

series = "Real-Time Technology and Applications - Proceedings",

pages = "261--272",

booktitle = "2013 IEEE 19th Real-Time and Embedded Technology and Applications Symposium, RTAS 2013",

}

Ferry, D, Li, J, Mahadevan, M, Agrawal, K, Gill, C & Lu, C 2013, A real-time scheduling service for parallel tasks. in 2013 IEEE 19th Real-Time and Embedded Technology and Applications Symposium, RTAS 2013., 6531098, Real-Time Technology and Applications - Proceedings, pp. 261-272, 2013 IEEE 19th Real-Time and Embedded Technology and Applications Symposium, RTAS 2013, Philadelphia, PA, United States, 4/9/13. https://doi.org/10.1109/RTAS.2013.6531098

TY - GEN

T1 - A real-time scheduling service for parallel tasks

AU - Ferry, David

AU - Li, Jing

AU - Mahadevan, Mahesh

AU - Agrawal, Kunal

AU - Gill, Christopher

AU - Lu, Chenyang

PY - 2013

Y1 - 2013

N2 - The multi-core revolution presents both opportunities and challenges for real-time systems. Parallel computing can yield significant speedup for individual tasks (enabling shorter deadlines, or more computation within the same deadline), but unless managed carefully may add complexity and overhead that could potentially wreck real-time performance. There is little experience to date with the design and implementation of realtime systems that allow parallel tasks, yet the state of the art cannot progress without the construction of such systems. In this work we describe the design and implementation of a scheduler and runtime dispatcher for a new concurrency platform, RT-OpenMP, whose goal is the execution of real-time workloads with intra-task parallelism.

AB - The multi-core revolution presents both opportunities and challenges for real-time systems. Parallel computing can yield significant speedup for individual tasks (enabling shorter deadlines, or more computation within the same deadline), but unless managed carefully may add complexity and overhead that could potentially wreck real-time performance. There is little experience to date with the design and implementation of realtime systems that allow parallel tasks, yet the state of the art cannot progress without the construction of such systems. In this work we describe the design and implementation of a scheduler and runtime dispatcher for a new concurrency platform, RT-OpenMP, whose goal is the execution of real-time workloads with intra-task parallelism.

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U2 - 10.1109/RTAS.2013.6531098

DO - 10.1109/RTAS.2013.6531098

M3 - Conference contribution

AN - SCOPUS:84881097591

SN - 9781479901869

T3 - Real-Time Technology and Applications - Proceedings

SP - 261

EP - 272

BT - 2013 IEEE 19th Real-Time and Embedded Technology and Applications Symposium, RTAS 2013

T2 - 2013 IEEE 19th Real-Time and Embedded Technology and Applications Symposium, RTAS 2013

Y2 - 9 April 2013 through 11 April 2013

ER -

A real-time scheduling service for parallel tasks

Abstract

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All Science Journal Classification (ASJC) codes

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