The interconnection of geographically distributed supercomputers via high-speed networks allows users to access the needed compute power for large-scale, complex applications. For efficient use of such systems, the variance in processor performance and network (i.e., interconnection network versus wide area network) performance must be considered. In this paper, we present a decomposition tool, called PART, for distributed systems. PART takes into consideration the variance in performance of the networks and processors as well as the computational complexity of the application. This is achieved via the parameters used in the objective function of simulated annealing. The initial version of PART focuses on finite element based problems. The results of using PART demonstrate a 30% reduction in execution time as compared to using conventional schemes that partition the problem domain into equal-sized subdomains.