UPC Performance Evaluation on a Multicore System

Abstract—As size and architectural complexity of High Per-formance Computing systems increases, the need for productive programming tools and languages becomes more important. The UPC language aims to be a good choice for a produc-tive parallel programming. However, productivity is influenced not only by expressiveness of the language, but also by its performance. To assess the current UPC performance in high performance multicore systems, and therefore to help improve UPC developers future productivity, this paper provides an up-to-date UPC performance evaluation at various levels, evaluating two collective implementations, comparing their results with their MPI counterparts, and finally evaluating UPC and MPI performance in computational kernels. This analysis shows a path to optimize UPC collectives performance. This work also provides a performance snapshot of UPC vs the currently most popular choice for parallel programming, MPI. This snapshot, altogether with the UPC collectives analysis, shows that there is room for improvement and, besides its worse performance, UPC is suitable for a productive development of most HPC applications. I