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12th International Conference on Parallel and Distributed Systems - Volume 1 (ICPADS'06)
The Impact of Information Availability and Workload Characteristics on the Performance of Job Co-allocation in Multi-clusters
Minneapolis, Minnesota
July 12-July 15
ISBN: 0-7695-2612-8
ASCII Text
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William M. Jones, Walter B. Ligon III, Nishant Shrivastava, "The Impact of Information Availability and Workload Characteristics on the Performance of Job Co-allocation in Multi-clusters," Parallel and Distributed Systems, International Conference on, vol. 1, pp. 123-134, 12th International Conference on Parallel and Distributed Systems - Volume 1 (ICPADS'06), 2006.
 
 
BibTex
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@article{ 10.1109/ICPADS.2006.105,
author = {William M. Jones and Walter B. Ligon III and Nishant Shrivastava},
title = {The Impact of Information Availability and Workload Characteristics on the Performance of Job Co-allocation in Multi-clusters},
journal ={Parallel and Distributed Systems, International Conference on},
volume = {1},
year = {2006},
issn = {1521-9097},
pages = {123-134},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICPADS.2006.105},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Parallel and Distributed Systems, International Conference on
TI - The Impact of Information Availability and Workload Characteristics on the Performance of Job Co-allocation in Multi-clusters
SN - 1521-9097
SP123
EP134
A1 - William M. Jones,
A1 - Walter B. Ligon III,
A1 - Nishant Shrivastava,
PY - 2006
KW - parallel job scheduling
KW - multiple computational clusters
KW - workload effects
KW - network contention
KW - multisite scheduling
VL - 1
JA - Parallel and Distributed Systems, International Conference on
ER -
 
William M. Jones, Clemson University, USA
Walter B. Ligon III, Clemson University, USA
Nishant Shrivastava, Clemson University, USA
In this paper, we utilize a bandwidth-centric job communication model that captures the interaction and impact of simultaneously co-allocating jobs across multiple clusters. We make use of a parallel job model that seeks to capture both local and global communication access patterns. By doing so, we are able to explore scheduling strategies that attempt to improve average job turnaround time by selectively mapping jobs across cluster boundaries in a process known as job co-allocation.

In this research, we focus on scheduling strategies that make use of available information such as network link utilization, per-processor bandwidths, and job communication topology in order to make intelligent decisions regarding application partition sizes and job placement. We provide results that help to establish the relationship between the quantity of information available a priori to the scheduler and its ability to improve overall system performance. Additionally, we demonstrate the dramatic impact that salient workload characteristics can have on the effectiveness of co-allocation.

Index Terms:
parallel job scheduling, multiple computational clusters, workload effects, network contention, multisite scheduling
Citation:
William M. Jones, Walter B. Ligon III, Nishant Shrivastava, "The Impact of Information Availability and Workload Characteristics on the Performance of Job Co-allocation in Multi-clusters," icpads, vol. 1, pp.123-134, 12th International Conference on Parallel and Distributed Systems - Volume 1 (ICPADS'06), 2006
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