On the Parallelization of Linkmap from the LINKAGE/FASTLINK Package

Aaditya Rai , Noe Lopez-Benitez , J.D. Hargis , S.E. Poduslo
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引用次数: 8

Abstract

Genetic linkage calculations can be time consuming, even on a fast computer. The ability to collect large family pedigrees has increased the magnitude of linkage computations. Sequential genetic algorithms have many successful applications in very different domains, but they have a main drawback in their utilization. Evaluations are very time-consuming, e.g., a pedigree consisting of 55 nodes takes about 70 min on a DEC-Alpha processor and about 270 min on a 166 MHz Pentium for certain likelihood calculations. This time increases exponentially with the increase in the size of the pedigree. In order to solve these shortcomings and to study new models of higher efficiency and efficacy, parallel platforms are being used for genetic programs. LINKAGE is a software package for performing genetic likelihood calculations; FASTLINK is an improved, faster version of it. This paper provides a parallel implementation of the “Linkmap” program (one of the four programs in LINKAGE/FASTLINK) for a heterogeneous environment, using a static and a dynamic strategy for task allocation. It was found that the increased performance by the dynamic strategy was close to the estimated maximum speed up.

从LINKAGE/FASTLINK包看Linkmap的并行化
即使在一台快速的计算机上,遗传连锁的计算也可能是耗时的。收集大型家族谱系的能力增加了连锁计算的规模。序列遗传算法在许多不同的领域都有成功的应用,但在实际应用中也存在很大的缺陷。评估非常耗时,例如,一个由55个节点组成的谱系在DEC-Alpha处理器上大约需要70分钟,在166 MHz的Pentium上大约需要270分钟进行某些似然计算。这个时间随着谱系大小的增加呈指数增长。为了解决这些缺点,研究更高效率和功效的新模型,并行平台正在被用于遗传程序。LINKAGE是一个用于执行遗传似然计算的软件包;FASTLINK是它的改进版,速度更快。本文提供了异构环境下“Linkmap”程序(link /FASTLINK中四个程序之一)的并行实现,使用静态和动态策略进行任务分配。结果表明,动态策略所提高的性能接近于估计的最大加速。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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