A Framework for Comparative Performance Analysis of MPI Applications.
Edgar Gabriel, Feng Sheng, Rainer Keller, Michael Resch · 2006
Parallel application developers are facing a myriad of parameters when trying to understand the performance behavior of their code. Even within a single hardware configuration, the performance of any application will depend among others on factors such as the MPI library or some application level input parameters. This paper deals with the problem on how to determine the cause for performance variations of an application. Based on tracefiles of the application generated for several scenarios and an according documentation of the parameters used for each run, the PERDAC performance analysis tool is calculating statistical properties of the performance data gathered, such as average, standard deviation, maximum and minimum across the different runs. In the current implementation, the performance data comprises of the total execution time of an MPI function on a process, the number of occurrences of each MPI function and optionally some hardware performance counters such as cache hits or cache misses. In a second step, the results of the statistical analysis are traversed in search for parameters, which show an non-uniform behavior in the analyzed execution scenarios. 1