Enhancing Software DSM for Compiler-Parallelized Applications

Abstract

Current parallelizing compilers for message-passing machines only support a limited class of data-parallel applications. One method for eliminating this restriction is to combine powerful shared-memory parallelizing compilers with software distributed-shared-memory (DSM) systems. We demonstrate such a system by combining the SUIF parallelizing compiler and the CVM software DSM. Innovations of the system include compiler-directed techniques that: 1) combine synchronization and parallelism information communication on parallel task invocation, 2) employ customized routines for evaluating reduction operations, and 3) select a hybrid update protocol that pre-sends data by flushing updates at barriers. For applications with sufficient granularity of parallelism, these optimizations yield very good speedups eight processors on an IBM SP-2 and DEC Alpha cluster, usually matching or exceeding the speedup of equivalent HPF and message-passing versions of each program. Based on our experimental results, we point out areas where additional compiler analysis and software DSM improvements can be used to achieve good performance on a broader range of applications. (Also cross-referenced as UMIACS-TR-96-70)