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Predicting the Resource Requirements of a Job Submission

Ali, Arshad and Anjum, Ashiq and Bunn, Julian and Cavanaugh, Richard and van Lingen, Frank and McClatchey, Richard and Mehmood, Muhammad Atif and Newman, Harvey and Steenberg, Conrad and Thomas, Michael and Willers, Ian (2004) Predicting the Resource Requirements of a Job Submission. In: Computing in High Energy Physics, 2004, Interlaken, Switzerland. (Unpublished)

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Grid computing aims to provide an infrastructure for distributed problem solving in dynamic virtual organizations. It is gaining interest among many scientific disciplines as well as the industrial community. However, current grid solutions still require highly trained programmers with expertise in networking, high-performance computing, and operating systems. One of the big issues in full-scale usage of a grid is matching the resource requirements of job submission to the resources available on the grid. Resource brokers and job schedulers must make estimates of the resource usage of job submissions in order to ensure efficient use of grid resources. We prop ose a prediction engine that will operate as part of a grid scheduler. This prediction engine will provide estimates of the resources required by job submission based upon historical information. This paper presents the need for such a prediction engine and discusses two approaches for history based estimation.

Item Type:Conference or Workshop Item (Paper)
Bunn, Julian0000-0002-3798-298X
Newman, Harvey0000-0003-0964-1480
Group:Center for Advanced Computing Research
Record Number:CaltechCACR:2004.210
Persistent URL:
Usage Policy:You are granted permission for individual, educational, research and non-commercial reproduction, distribution, display and performance of this work in any format.
ID Code:28185
Deposited By: Imported from CaltechCACR
Deposited On:16 Nov 2004
Last Modified:20 Jan 2023 00:45

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