Computer simulation revolutionizes traditional experimentation providing a virtual laboratory. The goal of high-performance computing is a fast execution of applications since this enables rapid experimentation. Performance of parallel applications can be improved by increasing either capability of hardware or execution efficiency. In order to increase utilization of hardware resources, a rich variety of optimization strategies is implemented in both hardware and software layers. The interactions of these strategies, however, result in very complex systems. This complexity makes assessing and understanding the measured performance of parallel applications in real systems exceedingly difficult.

To help in this task, in with PIOsimHD an innovative event-driven simulator for MPI-IO applications and underlying heterogeneous cluster computers is developed which can help us to assess measured performance. The simulator allows conducting MPI-IO application runs in silico, including the detailed simulations of collective communication patterns, parallel I/O and cluster hardware configurations. The simulation estimates the upper bounds for expected performance and therewith facilitates the evaluation of observed performance.

In addition to the simulator, the comprehensive tracing environment HDTrace offers novel capabilities in analyzing parallel I/O. For example, it allows the internal behavior of MPI and the parallel file system PVFS to be traced. While PIOsimHD replays traced behavior of applications on arbitrary virtual cluster environments, in conjunction with HDTrace it is a powerful tool for localizing inefficiencies, conducting research on optimizations for communication algorithms, and evaluating arbitrary and future systems.

Contact Dr. Julian Kunkel
Repository Public on GitHub