Effective fine-grain synchronization for automatically parallelized programs using optimistic synchronization primitives

Abstract

This article presents our experience using optimistic synchronization to implement fine-grain atomic operations in the context of a parallelizing compiler for irregular, object-based computations. Our experience shows that the synchronization requirements of these programs differ significantly from those of traditional parallel computations, which use loop nests to access dense matrices using affine access functions. In addition to coarse-grain barrier synchronization, our irregular computations require synchronization primitives that support efficient fine-grain atomic operations. The standard implementation mechanism for atomic operations uses mutual exclusion locks. But the overhead of acquiring and releasing locks can reduce the performance. Locks can also consume significant amounts of memory. Optimistic synchronization primitives such as loud-linked/store conditional are an attractive alternative. They require no additional memory and eliminate the use of heavyweight blocking synchronization constructs. We evaluate the effectiveness of optimistic synchronization by comparing experimental results from two versions of a parallelizing compiler for irregular, object-based computations. One version generates code that uses mutual exclusion locks to make operations execute atomically. The other version generates code that uses mutual exclusion locks to make operations execute atomically. The other version uses optimistic synchronization. We used this compiler to automatically parallelize three irregular, object-based benchmark applications of interest to the scientific and engineering computation community. The presented experimental results indicate that the use of optimistic synchronization in this context can significantly reduce the memory consumption and improve the overall performance.