Any architectural or operational inefficiencies in multiprocessors with thousands of processors are likely to have a significant negative impact on the performance of the system. The authors examine two such issues in large-scale shared memory multiprocessors-the delays involved in accessing global shared memory, and the low processor utilization resulting from inefficient partitioning of the system among several tasks. These studies are undertaken using a simulation model that directly integrates the nondeterministic interconnection network delays encountered during shared memory accesses into the execution of tasks on processors. The results show the quantitative impact of interconnection network delay on system performance and point to ways of reducing this impact. Furthermore, when incoming tasks have large processor requirements, the system's inability to partition the processors among several tasks efficiently has a significant detrimental effect on performance. The effectiveness of some techniques to solve this partitionability problem is discussed.
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