Miller P L, Nadkarni P M, Bercovitz P A
Centre for Medical Informatics, Yale University School of Medicine, New Haven, CT 06510.
Comput Appl Biosci. 1992 Apr;8(2):141-7. doi: 10.1093/bioinformatics/8.2.141.
It is widely accepted that parallel computers, which have the ability to execute different parts of a program simultaneously, will offer dramatic speed-up for many time-consuming biological computations. The paper describes how the use of the machine-independent parallel programming language, Linda, allows parallel programs to run on an institution's network of workstations. In this way, an institution can harness existing hardware, which is often either idle or vastly underutilized, as a powerful 'parallel machine' with supercomputing capability. The paper illustrates this very general paradigm by describing the use of Linda to parallelize three widely used programs for genetic linkage analysis, a mathematical technique used in gene mapping. The paper then discusses a number of technical, administrative and social issues that arise when creating such a computational resource.
人们普遍认为，具有同时执行程序不同部分能力的并行计算机，将为许多耗时的生物计算带来显著的加速。本文描述了如何使用与机器无关的并行编程语言Linda，使并行程序能够在机构的工作站网络上运行。通过这种方式，机构可以利用现有的硬件，这些硬件通常要么闲置要么未得到充分利用，将其作为具有超级计算能力的强大“并行机器”。本文通过描述使用Linda将三个广泛用于遗传连锁分析（一种用于基因图谱绘制的数学技术）的程序并行化，来说明这种非常通用的范例。然后，本文讨论了创建这样一种计算资源时出现的一些技术、管理和社会问题。
