Affiliation:
1. MIT Lab for Computer Science, Cambridge, MA
Abstract
Parallel symbolic computation has attracted considerable interest in recent years. Research groups building multiprocessors for such applications have been frustrated by the lack of data on how symbolic programs run on a parallel machine. This report describes the behavior of Multilisp programs running on a shared memory multiprocessor. Data was collected for a set of application programs on the frequency of different instructions, the type of objects accessed, and where the objects were located in the memory of the multiprocessor. The locality of data references for different multiprocessor organizations was measured. Finally, the effect of different task scheduling strategies on the locality of accesses was studied. This data is summarized here, and compared to other studies of LISP performance on uniprocessors.
Publisher
Association for Computing Machinery (ACM)
Cited by
1 articles.
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