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

In adaptive irregular problems, data arrays are accessed via indirection arrays, and data access patterns change during computation. Parallelizing such problems on distributed memory machines requires support for dynamic data partitioning, efficient preprocessing and fast data migration. This paper describes CHAOS, a library of efficient runtime primitives that provides such support. To demonstrate the effectiveness of the runtime support, two adaptive irregular applications have been parallelized using CHAOS primitives: a molecular dynamics code (CHARMM) and a code for simulating gas flows (DSMC). We have also proposed minor extensions to Fortran D which would enable compilers to parallelize irregular for all loops in such adaptive applications by embedding calls to primitives provided by a runtime library. We have implemented our proposed extensions in the Syracuse Fortran 90D/HPF prototype compiler, and have used the compiler to parallelize kernels from two adaptive applications