Optimization of parallel compilation techniques using genetic algorithms

Abstract

This paper addresses the issue of low parallel efficiency resulting from fixed thread allocation in automatic parallelization compilation technology. The authors employ a genetic algorithm to determine the optimal number of threads for individual parallelizable loops. They then utilize iterative compilation techniques to produce the suitable number of threads for each parallelizable loop structure, thereby enhancing the efficiency of automatic parallelization compilation. The proposed method demonstrated an average performance enhancement of 26% across ten benchmarks in the SPEC CPU2006 test suite and an overall performance improvement of 3.7% in the NPB3.4.2 test suite, thereby indicating the viability and efficacy of the approach. The approach outlined in this paper can be utilized as a benchmark for enhancing the effectiveness of automated parallel computing and promoting the progression of automated parallel computing technology.