Compiler optimizations for parallel sparse programs with array intrinsics of Fortran 90

In our recent work, we have been working on providing parallel sparse supports for array intrinsics of Fortran 90. Our supporting library uses a two-level design. In the low-level routines, it requires the input sparse matrices to be specified with compression/distribution schemes for array functions. In the high-level representations, sparse array functions are overloaded with Fortran 90 array intrinsic interfaces so that programmers need not be concerned about low-level details. This raises a very interesting optimization problem in the strategies to transform high-level representations to low-level routines by automatic selections and supplies of distribution and compression schemes for sparse arrays. We propose solutions to this optimization problem. The optimization problem is shown to be NP-hard. We develop a heuristic algorithm based on annotated program graphs, and the algorithm is shown to be practical. Experimental results on an IBM SP-2 show that the selection algorithms are effective in improving the performances of application programs that use sparse data sets.