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Multicore processors promise continued hardware performance improvements even as single-core performance flattens out. However they also enable increasingly complex application software that threatens to obfuscate application-level performance. This paper applies operational analysis to the problem of understanding and predicting application-level performance in parallel servers. The paper presents operational laws that offer both insight and actionable information based on lightweight passive external observations of black-box applications. One law accurately infers queuing delays; others predict the performance implications of expanding or reducing capacity. The former enables improved monitoring and system management; the latter enable capacity planning and dynamic resource provisioning to incorporate application-level performance in a principled way.
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