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Parallelizing genetic linkage analysis: A case study for applying parallel computation in molecular biology

✍ Scribed by Perry L. Miller; Prakash Nadkarni; Joel E. Gelernter; Nicholas Carriero; Andrew J. Pakstis; Kenneth K. Kidd


Publisher
Elsevier Science
Year
1991
Tongue
English
Weight
970 KB
Volume
24
Category
Article
ISSN
0010-4809

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✦ Synopsis


Parallel computers offer a solution to improve the lengthy computation time of many conventional, sequential programs used in molecular biology. On a parallel computer, different pieces of the computation are performed simultaneously on different processors. LINK-MAP is a sequential program widely used by scientists to perform genetic linkage analysis. We have converted LINKMAP to run on a parallel computer, using the machine-independent parallel programming language, Linda. Using the parallelization of LINKMAP as a case study, the paper outlines an approach to converting existing highly iterative programs to a parallel form. The paper describes the steps involved in converting the sequential program to a parallel program. It presents performance benchmarks comparing the sequential version of LINKMAP with the parallel version running on different parallel machines. The paper also discusses alternative approaches to the problem of "load balancing," making sure the computational load is shared as evenly as possible among the available processors.