Abstract-This paper proposes a trace reduction method for assessing the improvability of the performance of message passing parallel programs. This assessment is based on a what-if prediction approach that forecasts future program performance, for example, the execution time if the target program is modified according to typical tuning techniques. Our method reduces the size of trace files by aggregating records of communications that do not change the predicted execution time. In order to avoid recording such useless information, our method automatically identifies them during program execution by comparing the occurrence time of sends and receives. In case studies, our method reduces the analysis time for what-if predictions as well as the size of trace files roughly into half. We also discuss the usability of our method.

This paper presents PerWiz, a performance prediction tool for improving the performance of message passing programs. PerWiz focuses on locating where a significant improvement can be achieved. To locate this, PerWiz performs a post-mortem analysis based on a realistic parallel computational model, LogGPS, so that predicts what performance will be achieved if the programs are modified according to typical tuning techniques, such as load balancing for a better workload distribution and message scheduling for a shorter waiting time. We also show two case studies where PerWiz played an important role in improving the performance of regular applications. Our results indicate that PerWiz is useful for application developers to assess the potential reduction in execution time that will be derived from program modification.