Improving online performance diagnosis by the use of historical performance data
SC '99 Proceedings of the 1999 ACM/IEEE conference on Supercomputing
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Rule-based automatic software performance diagnosis and improvement
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Proceedings of the 7th annual IEEE/ACM International Symposium on Code Generation and Optimization
Rule-based automatic software performance diagnosis and improvement
Performance Evaluation
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HPCC'05 Proceedings of the First international conference on High Performance Computing and Communications
Rule-based automatic software performance diagnosis and improvement
Performance Evaluation
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Performance diagnosis, the process of finding and explaining performance problems, is an important part of parallel programming. Effective performance diagnosis requires that the programmer plan an appropriate method, and manage the experiments required by that method. This paper presents Poirot, an architecture to support performance diagnosis. It explains how the architecture helps automatically, adaptably plan and manage the diagnosis process. The paper evaluates the generality and practicality of Poirot, by reconstructing diagnosis methods found in several published performance tools.