Access Type
Campus Access Only
Start Date
4-17-2024 12:00 AM
End Date
4-17-2024 12:00 AM
College
Lynchburg College of Arts and Sciences
Department
Computer Science
Keywords
CS, Cloud computing, Distributed Computing, Simulation
Abstract
The analysis of a distributed program that ran for five days on 50 computers determined that for much of the time, only about 10% of the resources were being fully utilized. We used a simple simulation to determine bottlenecks and to determine a different way to partition the job to get a better utilization of resources.
Faculty Mentor(s)
Dr. Ribler
Rights Statement
The right to download or print any portion of this material is granted by the copyright owner only for personal or educational use. The author/creator retains all proprietary rights, including copyright ownership. Any editing, other reproduction or other use of this material by any means requires the express written permission of the copyright owner. Except as provided above, or for any other use that is allowed by fair use (Title 17, §107 U.S.C.), you may not reproduce, republish, post, transmit or distribute any material from this web site in any physical or digital form without the permission of the copyright owner of the material.
Analyzing and Optimizing a Large Distributed Process
The analysis of a distributed program that ran for five days on 50 computers determined that for much of the time, only about 10% of the resources were being fully utilized. We used a simple simulation to determine bottlenecks and to determine a different way to partition the job to get a better utilization of resources.