We evaluate the impact of a gigabit network on the implementation of a distributed chemical process optimization application. The optimization problem is formulated as a stochastic Linear Assignment Problem and was solved using the Thinking Machines CM-2 (SIMD) and the Cray C-90 (vector) computers at PSC, and the Intel iWarp (MIMD) system at CMU, connected by the Gigabit Nectar testbed. We report our experience distributing the application across this heterogeneous set of systems and present measurements that show how the communication requirements of the application depend on the structure of the application. We use detailed traces to build an application performance model that can be used to estimate the elapsed time of the application for different computer system and network combinations. Our results show that the application benefits from the high-speed network, and that the need for high network throughput is increasing as computer systems get faster. We also observed that supporting high burst rates is critical, although structuring the application so that communication is overlapped with computation relaxes the bandwidth requirements.