| Type of Document |
Master's Thesis |
| Author |
Swaminathan, Gautam
|
| Author's Email Address |
gswami@microsoft.com |
| URN |
etd-02152005-173648 |
| Title |
A scheduling framework for dynamically resizable parallel applications |
| Degree |
Master of Science |
| Department |
Computer Science |
| Advisory Committee |
| Advisor Name |
Title |
| Ribbens, Calvin J. |
Committee Chair |
| Kafura, Dennis G. |
Committee Member |
| Varadarajan, Srinidhi |
Committee Member |
|
| Keywords |
- Dynamic resizing
- parallel applications
- MPI-2
- scheduling framework
|
| Date of Defense |
2004-06-18 |
| Availability |
restricted |
Abstract
Applications in science and engineering require large parallel systems in order to solve computational problems within a reasonable timeframe. These applications can benefit from dynamic resizing during the course of their execution. Dynamic resizing enables fine-grained control over resource allocation to jobs and results in better system throughput and job turn around time. We have implemented a framework that enabled dynamic resizing of MPI applications. Our framework uses the recently released MPI-2 standard that enables dynamic resizing. The work described in this thesis is part of a larger effort to design and implement a system for supporting and leveraging dynamically resizable parallel applications. We provide a scheduling framework, an API for dynamic resizing and libraries to efficiently redistribute data to new processor topologies.
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