A scheduling framework for dynamically resizable parallel applications

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.

Name thesis:degree_name

Master of Science

Level thesis:degree_level

masters

Discipline thesis:degree_discipline

Computer Science

Department dc:contributor.department

Computer Science

Grantor dc:publisher

Virginia Tech

Year dc:date.issued

2004

Author dc:creator

• Swaminathan, Gautam

Chair dc:contributor.committeechair

• Ribbens, Calvin J.

Committee members dc:contributor.committeemember

• Kafura, Dennis G.
• Varadarajan, Srinidhi

• Dynamic resizing
• parallel applications
• MPI-2
• scheduling framework

Statement dc:rights

• In Copyright

Licence dc:rights.uri

• http://rightsstatements.org/vocab/InC/1.0/

Dc Identifier Other

etd-02152005-173648

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/41130