Advanced Array Optimizations for High Performance Functional Languages

Abstract

In this paper, we discuss and evaluate three opti- mizations for reducing memory management overhead and data copying costs in SISAL 1.2 programs that build arrays. The first, called framework preconstruction, eliminates superfluous allocate-deallocate sequences in cyclic computations. The second, called aggregate storage subsumption, reduces the management overhead for compound array components. The third, called predictive storage preallocation, eliminates superfluous data copying in filtered array constructions and simplifies their parallelization. We have added all three optimizations to the Optimizing SISAL Compiler with rewarding improvements in SISAL program performance on vector-parallel machines such as those built by Cray Computer Corporation, Convex, and Cray Research. © 1995 IEEE