Optimizing job scheduling on multicore computers

Huanzhou Zhu; Ligang He; Stephen A. Jarvis

doi:10.1109/MASCOTS.2014.16

Optimizing job scheduling on multicore computers

Huanzhou Zhu, Ligang He^*, Stephen A. Jarvis

^*Corresponding author for this work

Engineering and Physical Sciences

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

2 Citations (Scopus)

Abstract

It is common nowadays that multiple cores reside on the same chip and share the on-chip cache. Resource sharing may cause performance degradation of the co-running jobs. Job co-scheduling is a technique that can effectively alleviate the contention. Many co-schedulers have been developed in the literature, but most of them do not aim to find the optimal co-scheduling solution. Being able to determine the optimal solution is critical for evaluating co-scheduling systems. Moreover, most co-schedulers only consider serial jobs. However, there often exist both parallel and serial jobs in some situations. This paper aims to tackle these issues. In this paper, a graph-based method is developed to find the optimal co-scheduling solution for serial jobs, and then the method is extended to incorporate parallel jobs. The extensive experiments have been conducted to evaluate the effectiveness and efficiency of the proposed co-scheduling algorithms. The results show that the proposed algorithms can find the optimal co-scheduling solution for both serial and parallel jobs.

Original language	English
Title of host publication	Proceedings - 2014 22nd Annual IEEE International Symposium on Modeling, Analysis and Simulation of Computer, and Telecommunication Systems, MASCOTS 2014
Publisher	IEEE Computer Society
Pages	61-70
Number of pages	10
Edition	February
ISBN (Electronic)	9781479956104
DOIs	https://doi.org/10.1109/MASCOTS.2014.16
Publication status	Published - 5 Feb 2015
Event	2014 22nd Annual IEEE International Symposium on Modeling, Analysis and Simulation of Computer, and Telecommunication Systems, MASCOTS 2014 - Paris, France Duration: 9 Sept 2014 → 11 Sept 2014

Publication series

Name	Proceedings - IEEE Computer Society's Annual International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunications Systems, MASCOTS
Number	February
Volume	2015-February
ISSN (Print)	1526-7539

Conference

Conference	2014 22nd Annual IEEE International Symposium on Modeling, Analysis and Simulation of Computer, and Telecommunication Systems, MASCOTS 2014
Country/Territory	France
City	Paris
Period	9/09/14 → 11/09/14

Bibliographical note

Publisher Copyright:
© 2014 IEEE.

Keywords

Co-scheduling
Multicore
Parallel application

ASJC Scopus subject areas

Electrical and Electronic Engineering
Computer Networks and Communications
Software
Modelling and Simulation

Access to Document

10.1109/MASCOTS.2014.16

Cite this

Zhu, H., He, L., & Jarvis, S. A. (2015). Optimizing job scheduling on multicore computers. In Proceedings - 2014 22nd Annual IEEE International Symposium on Modeling, Analysis and Simulation of Computer, and Telecommunication Systems, MASCOTS 2014 (February ed., pp. 61-70). Article 7033638 (Proceedings - IEEE Computer Society's Annual International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunications Systems, MASCOTS; Vol. 2015-February, No. February). IEEE Computer Society. https://doi.org/10.1109/MASCOTS.2014.16

Zhu, Huanzhou ; He, Ligang ; Jarvis, Stephen A. / Optimizing job scheduling on multicore computers. Proceedings - 2014 22nd Annual IEEE International Symposium on Modeling, Analysis and Simulation of Computer, and Telecommunication Systems, MASCOTS 2014. February. ed. IEEE Computer Society, 2015. pp. 61-70 (Proceedings - IEEE Computer Society's Annual International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunications Systems, MASCOTS; February).

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Zhu, H, He, L & Jarvis, SA 2015, Optimizing job scheduling on multicore computers. in Proceedings - 2014 22nd Annual IEEE International Symposium on Modeling, Analysis and Simulation of Computer, and Telecommunication Systems, MASCOTS 2014. February edn, 7033638, Proceedings - IEEE Computer Society's Annual International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunications Systems, MASCOTS, no. February, vol. 2015-February, IEEE Computer Society, pp. 61-70, 2014 22nd Annual IEEE International Symposium on Modeling, Analysis and Simulation of Computer, and Telecommunication Systems, MASCOTS 2014, Paris, France, 9/09/14. https://doi.org/10.1109/MASCOTS.2014.16

Optimizing job scheduling on multicore computers. / Zhu, Huanzhou; He, Ligang; Jarvis, Stephen A.
Proceedings - 2014 22nd Annual IEEE International Symposium on Modeling, Analysis and Simulation of Computer, and Telecommunication Systems, MASCOTS 2014. February. ed. IEEE Computer Society, 2015. p. 61-70 7033638 (Proceedings - IEEE Computer Society's Annual International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunications Systems, MASCOTS; Vol. 2015-February, No. February).

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

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AU - Jarvis, Stephen A.

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N2 - It is common nowadays that multiple cores reside on the same chip and share the on-chip cache. Resource sharing may cause performance degradation of the co-running jobs. Job co-scheduling is a technique that can effectively alleviate the contention. Many co-schedulers have been developed in the literature, but most of them do not aim to find the optimal co-scheduling solution. Being able to determine the optimal solution is critical for evaluating co-scheduling systems. Moreover, most co-schedulers only consider serial jobs. However, there often exist both parallel and serial jobs in some situations. This paper aims to tackle these issues. In this paper, a graph-based method is developed to find the optimal co-scheduling solution for serial jobs, and then the method is extended to incorporate parallel jobs. The extensive experiments have been conducted to evaluate the effectiveness and efficiency of the proposed co-scheduling algorithms. The results show that the proposed algorithms can find the optimal co-scheduling solution for both serial and parallel jobs.

AB - It is common nowadays that multiple cores reside on the same chip and share the on-chip cache. Resource sharing may cause performance degradation of the co-running jobs. Job co-scheduling is a technique that can effectively alleviate the contention. Many co-schedulers have been developed in the literature, but most of them do not aim to find the optimal co-scheduling solution. Being able to determine the optimal solution is critical for evaluating co-scheduling systems. Moreover, most co-schedulers only consider serial jobs. However, there often exist both parallel and serial jobs in some situations. This paper aims to tackle these issues. In this paper, a graph-based method is developed to find the optimal co-scheduling solution for serial jobs, and then the method is extended to incorporate parallel jobs. The extensive experiments have been conducted to evaluate the effectiveness and efficiency of the proposed co-scheduling algorithms. The results show that the proposed algorithms can find the optimal co-scheduling solution for both serial and parallel jobs.

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Zhu H, He L, Jarvis SA. Optimizing job scheduling on multicore computers. In Proceedings - 2014 22nd Annual IEEE International Symposium on Modeling, Analysis and Simulation of Computer, and Telecommunication Systems, MASCOTS 2014. February ed. IEEE Computer Society. 2015. p. 61-70. 7033638. (Proceedings - IEEE Computer Society's Annual International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunications Systems, MASCOTS; February). doi: 10.1109/MASCOTS.2014.16

Optimizing job scheduling on multicore computers

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this