Performance modeling of a cluster of workstations

Using off-the-shelf commodity workstations to build a cluster for parallel computing has become a common practice. In studying or designing a cluster of workstations one should have available a robust analytical model that includes the major parameters that determines the cluster performance. In this paper, we present such a model for evaluating a cluster's performance. The model covers the effect of storage limitations, interconnection networks and the impact of data partitioning. The model can be used to estimate the throughput of the cluster or the expected service time of the tasks under any specific configuration. It also, can detect the bottlenecks in the system, which can lead to more effective utilization of the available resources. The model (Multi-Class Jackson Network) we use can be considered as the base line for the cluster architecture analysis because it models the system behavior without using any special task or scheduling algorithms.