Performance Models for Multiprocessor Computer Systems.
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ILLINOIS UNIV AT URBANA COORDINATED SCIENCE LAB
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Multiprocessing is an effective architectural approach to enhance the performance of computer systems. However, various problems involved in multiprocessing may severely degrade system performance. This research has mainly centered on the memory interference problem in tightly coupled multiprocessor computer systems. Depending on the nature of the memory-requesting mechanism, discussion is centered on two important cases of such systems. The memory interference in multiprocessor systems with time-division-multiplexed TDM busses is first discussed. A general model for the memory interference in synchronous multiprocessor systems which allow arbitrary memory request rates, non-uniform memory references, and unequal processor priorities is presented next. Several application examples which make use of the memory interference models derived are presented. First, an algorithm is proposed for the estimation of the execution time of a program running in a multiprocessor system. Such an algorithm can be used to pick a computation decomposition which best utilizes the available computing power. A case study of the effect of computation decomposition on the performance of Gaussian Elimination is presented. The execution of matrix multiplication in a multiprocessor system with virtual memory was evaluated by simulation, in which a memory interference model capable of dealing with priority was used to dynamically modify various job execution times according to the number of processors and IO channels active in the system.
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