“OpenMP” automatic parallelization tools: An Empirical comparative evaluation

Today, multi-core design has become the trend of enhancing the processor’s performance, and most industries have been considering multi-core as the future of development. Thus, a programmer or a compiler explicitly parallelizes the software, which is the key to enhance the performance on multi-core design. Nevertheless, currently, needs an in-depth knowledge of both software and hardware design to develop parallel applications. Automatic parallelization is one of the approaches aiming at a better and easier use of parallel computers. In recent years, several research auto-parallelization tools appeared. However, the automatic parallelization is yet to become a widely adopted industrial practice. This paper presents an empirical comparison between three research tools, namely CETUS, PLUTO and GASPARD. Indeed, we discuss the success of these tools to automatically generate OpenMP parallel codes from serial C codes and compare them using known benchmark C workloads and some evaluation