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.