Advanced Program Restructuring for High-Performance Computers with Polaris

Multiprocessor computers are rapidly becoming the norm. Parallel workstations are widely available today, and it is likely that most PCs in the near future will contain multiple processors. To accommodate these changes, some classes of applications must be developed in explicitly parallel form. Yet, in order to avoid a substantial increase in software development costs, compilers that translate conventional programs into efficient parallel form clearly will be necessary. In the ideal case, multiprocessor parallelism should be as transparent to programmers as instruction level parallelism is to programmers of today’s superscalar machines. However, compiling for multiprocessors is substantially more complex than compiling for functional unit parallelism, in part because successful parallelization often requires a very accurate analysis of long sections of code. This article discusses recent experience at Illinois on the automatic parallelization of scientific codes using the Polaris restructurer. We also present several new analysis techniques that we have developed in recent years based on an extensive analysis of the characteristics of real Fortran codes. These techniques, based on both static and dynamic parallelization strategies, have been incorporated into the Polaris restructurer. Preliminary results on parallel workstations are encouraging, and once the implementation of the new techniques is complete, we expect that Polaris will be able to obtain good speedups for many real scientific codes on parallel workstations