Author

Zanny

Date of Award

4-1999

Degree Name

Master of Science

Department

Computer Science

First Advisor

Dr. Ajay Gupta

Second Advisor

Dr. Elise de Doncker

Third Advisor

Dr. Don Nelson

Access Setting

Masters Thesis-Open Access

Abstract

The adaptive integration algorithm is· effective in numerically solving integration problems. It is able to focus the application of integration rules on the portion of the integration region where the integrand is the least well-behaved. Parallel implementations must use dynamic load balancing or performance suffers.

Dynamic local load-balancing techniques allow each processor to maintain its own pool of work in a local priority queue and balance the workload based on local criteria. However, the use of locally controlled priority queues is known to be inefficient (in terms of the number of integration rule applications needed to reach an answer) as the number of processors increases.

This thesis implements and analyzes the use of a distributed priority queue for managing the current pool of work and performing global load balancing in the parallel adaptive integration algorithm. Initial experimental results show that the use of a distributed priority queue does not provide any clear benefits over the use of multiple local priority queues. However , analyzing the circumstances where the results are better has led to greater understanding of the basic algorithm.

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