2022/11/30 by Parinaz Barakhshan, Barakhshan, Parinaz, Rudolf Eigenmann +1
Computer Science · #Advanced Data Storage Technologies #Cloud Computing and Resource Management #Distributed #FOS: Computer and information sciences #Parallel #Parallel Computing and Optimization Techniques #Performance (cs.PF) #and Cluster Computing (cs.DC)
paper · pdf · doi:10.48550/arxiv.2212.00165
openalex publication_date 2022/11/30 · openalex created_date 2022/12/13 · openalex updated_date 2026/07/28
We compare automatically and manually parallelized NAS Benchmarks in order to identify code sections that differ. We discuss opportunities for advancing automatic parallelizers. We find ten patterns that pose challenges for current parallelization technology. We also measure the potential impact of advanced techniques that could perform the needed transformations automatically. While some of our findings are not surprising and difficult to attain -- compilers need to get better at identifying parallelism in outermost loops and in loops containing function calls -- other opportunities are within reach and can make a difference. They include combining loops into parallel regions, avoiding load imbalance, and improving reduction parallelization. Advancing compilers through the study of hand-optimized code is a necessary path to move the forefront of compiler research. Very few recent papers have pursued this goal, however. The present work tries to fill this void.