Parallel application performance in a shared resource environment

The utilization of networked, shared, heterogeneous workstations as an inexpensive parallel computational platform is an appealing idea. However, most performance models for parallel computation are oriented towards the use of tightly-coupled, dedicated, homogeneous processors. We develop and validate an analytic performance modelling methodology for synchronous iterative algorithms executing on networked workstations. The model includes the effects of application load, background load, and processor heterogeneity. We use two applications, nonlinear optimization and discrete-event simulation, to validate the model. Various policies for the use of the workstations are considered and the optimal (or near-optimal) scheduling found. The performance modelling methodology provides significant help in addressing scheduling and similar issues in a shared resource environment.