Genetic epidemiology, parallel algorithms, and workstation networks

R. D. Chamberlain, G. D. Peterson, M. A. Franklin, M. A. Province

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Many interesting problems in genetic epidemiology are formulated as non-linear optimization problems using the Gemini/Almini library of routines. Because of the wide availability of networked workstations, we investigate cost-effectively improving the performance of the Gemini/Almini library by exploiting parallelism with a set of workstations connected via a local area network. Instrumentation of the Gemini/Almini optimization routines reveals significant potential for improving performance via parallelism. Using these instrumentation results, we identify promising targets of parallelism and discuss two preliminary implementations that demonstrate the potential benefits of cost-effective parallel implementations. By applying parallelism to the Almini/Gemini routines, we hope to potentially improve the performance of a large number of genetic epidemiological applications.

Original languageEnglish
Title of host publicationProceedings of the 28th Annual Hawaii International Conference on System Sciences, HICSS 1995
PublisherIEEE Computer Society
Pages101-111
Number of pages11
ISBN (Electronic)0818669306
DOIs
StatePublished - 1995
Event28th Annual Hawaii International Conference on System Sciences, HICSS 1995 - Wailea, United States
Duration: Jan 3 1995Jan 6 1995

Publication series

NameProceedings of the Annual Hawaii International Conference on System Sciences
Volume5
ISSN (Print)1530-1605

Conference

Conference28th Annual Hawaii International Conference on System Sciences, HICSS 1995
Country/TerritoryUnited States
CityWailea
Period01/3/9501/6/95

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