A Compiler Optimization Algorithm for Shared-Memory Multiprocessors

This paper presents a new compiler optimization algorithm that parallelizes applications for symmetric, sharedmemory multiprocessors. The algorithm considers data locality, parallelism, and the granularity of parallelism. It uses dependence analysis and a simple cache model to drive its optimizations. It also optimizes across procedures by using interprocedural analysis and transformations. We validate the algorithm by hand-applying it to sequential versions of parallel, Fortran programs operating over dense matrices. The programs initially were hand-coded to target a variety of parallel machines using loop parallelism. We ignore the user’s parallel loop directives, and use known and implemented dependence and interprocedural analysis to find parallelism. We then apply our new optimization algorithm to the resulting program. We compare the original parallel program to the hand-optimized program, and show that our algorithm improves 3 programs, matches 4 programs, and degrades 1 pro...

• Type: Journal
• Year: 1998
• Where: TPDS
• Authors: Kathryn S. McKinley
• Keywords: Algorithms, Compiler Optimizations, Parallel Machines, TPDS 1998