Abstract
Automatic trace analysis is an effective method for identifying complex performance phenomena in parallel applications. However, as the size of parallel systems and the number of processors used by individual applications is continuously raised, the traditional approach of analyzing a single global trace file, as done by kojak’s expert trace analyzer, becomes increasingly constrained by the large number of events. In this article, we present a scalable version of the expert analysis based on analyzing separate local trace files with a parallel tool which ‘replays’ the target application’s communication behavior. We describe the new parallel analyzer architecture and discuss first empirical results.
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Geimer, M., Wolf, F., Wylie, B.J.N., Mohr, B. (2006). Scalable Parallel Trace-Based Performance Analysis. In: Mohr, B., Träff, J.L., Worringen, J., Dongarra, J. (eds) Recent Advances in Parallel Virtual Machine and Message Passing Interface. EuroPVM/MPI 2006. Lecture Notes in Computer Science, vol 4192. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11846802_43
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DOI: https://doi.org/10.1007/11846802_43
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