Abstract

Existing tools for locating performance bottlenecks of message passing parallel programs either provide visualizations or profiles of program executions only; they do not highlight the cause of poor program performance. From the perspective of the application, the location and cause of performance problems in terms of procedures, processors and data structures are all important. Identifying the cause of poor performance necessitates the need to expose how well the underlying algorithm has been mapped onto the parallel machine.In this paper, we present a suite of normalized performance indices that provide a convenient mechanism for focusing on a location with poor performance. These indices are complemented by additional indices that highlight the cause of the performance failure in terms of processors, procedures and data structure interactions.With the help of examples from the NAS benchmark suite, we show that the automatically generated indices help detect potential causes of poor performance. These indices are generated from execution traces (augmented with data structure information) obtained from monitoring program executions on the Intel iPSC/860.

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