Automated instrumentation and monitoring of data movement in parallel programs

Writing efficient parallel programs is complicated by the need to select the right data-structure alignments and distributions, which determine the nature and volume of inter-processor communications. A large number of performance tools for parallel programs have been developed recently to expose the nature of these inter-processor communications. However, none of the tools support performance views or provide statistics in terms of inter-processor data-structure interactions. In this paper we discuss the use of compiler front end tools for automatically tracking data-structure movements in message passing programs, and low-overhead monitoring and postprocessing of such codes. In addition, our approach is compiler/pre-processor and platform independent. We demonstrate that robust instrumentation and low, overhead monitoring of inter-processor data-structure movements is possible, with the use of a number of NAS benchmarks run on the i860 hypercube. We also show that the data so collected con be efficiently used by post processing tools that expose performance bottlenecks using graphical displays and performance statistics