Abstract: While multicore processors increase throughput for multi-programmed and multithreaded codes,many important applications are single threaded and thus are not benefited．Automatic parallelization techniques play an important role in migrating singe threaded applications to multicore platform．Unfortunately,the prevalence of control flow,recursive data structures,and general pointer accesses in ordinary programs renders the existing techniques unsuitable．Ottoni et al．proposed an automatic parallelization algorithm called Decoupled Software Pipelining(DSWP)to exploit fine-grained pipeline parallelism at the instruction level．But it requires knowledge of micro-architectural properties and hardware support of a communication channel and two special instructions．The improved DSWP algorithm based on OpenMP increases the parallel granularity and does not rely on hardware support any more,but the existing OpenMP task scheduling mechanism cannot satisfy the need of DSWP．A new binding clause for the task construct in OpenMP was proposed to extend the task scheduling mechanism．It guarantees the correctness of the OpenMP DSWP parallelization．The new clause is implemented in the GCC runtime library libgomp,which provides support for the compilation of OpenMP DSWP programs．The experimental results show that loops failed to be parallelized by existing techniques can be parallelized by the improved automatic parallelization algorithm and gain significant performance improvement on dual-core CPU．The average performance speedup is up to 1.23．Compared with Intel and Open64compilers,the compiler with the improved algorithm can increase execution efficiency evidently and the average speedup of the OpenMP DSWP programs generated by it increases more than 22% and 26%.

Key words: Automatic parallelization,OpenMP,Decoupled software pipelining,Task scheduling mechanism,GCC