The network of workstations (NOW) we consider for parallel computing is heterogeneous and nondedicated (time-sharing), where computing power varies among the workstations, and multiple jobs may interact with each other in execution. We address three performance issues in this paper. First, we examine the effects of heterogeneity on co-scheduling and local scheduling policies for parallel computing. Through experimentation and quantitative comparisons, we discuss features and requirements of scheduling policies on heterogeneous NOW. Second, the heterogeneity and non-dedication of NOW introduce new performance factors into parallel computing, which make traditional performance metrics for parallel computing under homogeneous platforms not suitable. We conducted a collection of experimental measurements to show the performance impact to parallel computing. Finally, using network latencies we experimentally evaluate the parallel computing scalability on NOW. Our objective of this study is to provide insights into unique performance bottlenecks and potentials of networks of workstations.