Monitoring and Visualization in Cluster Environments

Cluster computing has evolved into a popular and effective mode of high performance computing. Cluster environments are intrinsically different from hardware multiprocessors, and hence require a different approach to measuring and characterizing performance, monitoring an application's progress, and understanding program behavior. In this article, we present the design and implementation of PVaniM, an experimental visualization environment we have developed for the PVM network computing system. PVaniM supports a two-phase approach whereby on-line visualization focuses on large-grained events that are influenced by and relate to the dynamic cluster environment, and postmortem visualization provides for detailed program analysis and tuning. PVaniM's capabilities are illustrated via its use on several applications and it is compared with other visualization environments developed for cluster computing. Our experiences indicate that for several classes of applications, the two-phase visualization scheme can provide more insight into the behavior, efficiency, and operation of distributed and parallel programs in cluster environments