An Integrated Compilation and Performance Analysis Environment for Data Parallel Programs

To support the transition from programming languages in which parallelism and communication are explicit to high-level languages that rely on compilers to infer such details from data decomposition directives, tools for performance analysis require increased sophistication and integration with other components in the programming system. We explore integration of performance tools with compilers for data parallel languages by integrating the Rice Fortran 77D compiler and the Illinois Pablo Environment. This integration permits analysis and correlation of the compiler-generated code's dynamic behavior and performance with the original data parallel source code. We expect that our strategy can serve as a model for integration of other data parallel compilers and performance tools. 1 Introduction High-level, data parallel languages such as High Performance Fortran and Fortran D [4] have attracted considerable attention because they offer a simple and portable programming model for paralle..