Theses and Dissertations
Issuing Body
Mississippi State University
Advisor
Banicescu, Ioana
Committee Member
Vaughn, Rayford B., Jr.
Committee Member
Skjellum, Anthony
Date of Degree
12-13-2003
Document Type
Graduate Thesis - Open Access
Major
Computer Science
Degree Name
Master of Science
College
James Worth Bagley College of Engineering
Department
Department of Computer Science
Abstract
Load imbalance is a major source of performance degradation in parallel scientific applications. Load balancing increases the efficient use of existing resources and improves performance of parallel applications running in distributed environments. At a coarse level of granularity, advances in runtime systems for parallel programs have been proposed in order to control available resources as efficiently as possible by utilizing idle resources and using task migration. At a finer granularity level, advances in algorithmic strategies for dynamically balancing computational loads by data redistribution have been proposed in order to respond to variations in processor performance during the execution of a given parallel application. Algorithmic and systemic load balancing strategies have complementary set of advantages. An integration of these two techniques is possible and it should result in a system, which delivers advantages over each technique used in isolation. This thesis presents a design and implementation of a system that combines an algorithmic fine-grained data parallel load balancing strategy called Fractiling with a systemic coarse-grained task-parallel load balancing system called Hector. It also reports on experimental results of running N-body simulations under this integrated system. The experimental results indicate that a distributed runtime environment, which combines both algorithmic and systemic load balancing strategies, can provide performance advantages with little overhead, underscoring the importance of this approach in large complex scientific applications.
URI
https://hdl.handle.net/11668/19205
Recommended Citation
Ghafoor, Sheikh Khaled, "Integrating Algorithmic and Systemic Load Balancing Strategies in Parallel Scientific Applications" (2003). Theses and Dissertations. 2764.
https://scholarsjunction.msstate.edu/td/2764
Comments
Load Balancing||Task Migration||Hectiling||Data Migration