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.