Parallel program analysis on workstation clusters: Memory utilisation and load balancing

Using a workstation cluster for parallel program development requires consideration of various factors to optimise the mapping of the algorithm to the characteristics of the environment, In this paper we present a new analysis and verification of well-known ideas in parallel programming research of specific importance to both the use and design of workstation cluster computing systems. We define a new performance measure related to memory resource utilisation and show how redundant memory usage can lead to poor memory utilisation of the cluster We also present analytical and experimental evidence that the pool-of-tasks paradigm can lead to significantly improved speedup over series-parallel algorithms, especially when considering equivalent computational and communication requirements. The effect of load balancing on the series-parallel and pool-of-tasks algorithms is examined, and our analysis and experimental results confirm not only that the pool-of-tasks algorithms are more robust to load imbalances but that the effect of the imbalance is mitigated when more workstations are used. (C) 1998 John Wiley & Sons, Ltd.