Which Applications Can Use High Performance Fortran and Fortran-D: Industry Standard Data Parallel Languages?

In this paper, we present the first, preliminary results of HPF/Fortran-D language analysis based on compiling and running benchmark applications using a prototype implementation of HPF/Fortran-D compiler. The analysis indicate that the HPF is a very convenient tool for programming many applications on massively parallel and/or distributed systems. In addition, we cumulate experience on how to parallelize irregular problems to extend the scope of Fortran-D beyond HPF and suggest future extensions to the Fortran standard

Run-time and compile-time support for adaptive irregular problems

In adaptive irregular problems the data arrays are accessed via indirection arrays, and data access patterns change during computation. Implementing such problems on distributed memory machines requires support for dynamic data partitioning, efficient preprocessing and fast data migration. This research presents efficient runtime primitives for such problems. This new set of primitives is part of the CHAOS library. It subsumes the previous PARTI library which targeted only static irregular problems. To demonstrate the efficacy of the runtime support, two real adaptive irregular applications have been parallelized using CHAOS primitives: a molecular dynamics code (CHARMM) and a particle-in-cell code (DSMC). The paper also proposes extensions to Fortran D which can allow compilers to generate more efficient code for adaptive problems. These language extensions have been implemented in the Syracuse Fortran 90D/HPF prototype compiler. The performance of the compiler parallelized codes is compared with the hand parallelized versions