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This brief announcement presents a pair of performance laws that bound the change in aggregate job queueing time that results when the processor speed changes in a parallel computing system. The laws require only lightweight passive external observations of a black-box system and they apply to many commonly employed scheduling policies. By predicting the application-level performance impact of processing speed adjustments in parallel processors, including traditional SMPs and now increasingly ubiquitous multicore processors, the laws address problems ranging from capacity planning to dynamic resource allocation. Finally, the results show that operational analysis-an approach to performance analysis traditionally associated with commercial transaction processing systems-usefully complements existing parallel performance analysis techniques.
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