Improving Scalability of OpenMP Applications on MultiCore Systems

Modern multicore architectures have become popular because of the limitations of deep pipelines and heating and power concerns. Some of these multicore architectures such as the Intel Xeon have the ability to run several threads on a single core. The OpenMP standard for compiler directive based shared memory programming allows the developer an easy path to writing multithreaded programs and is a natural fit for multicore architectures. The OpenMP standard uses loop parallelism as a basis for work division among multiple threads. These loops usually use arrays in their computation with different data distributions and access patterns. The performance of accesses to these arrays may be dependent on the underlying page size depending on the frequency and strides of these accesses. In this paper, we discuss the issues and potential benefits from using large pages for OpenMP applications. We design an OpenMP implementation capable of using large pages and evaluate the impact of using large page support available in most modern processors on the performance and scalability of parallel OpenMP applications. Results show an improvement in performance of up to 25% for some applications. It also helps improve the scalability of these applications. This research is supported in part by Department Energy’s grants #DE-FC02-06ER25755 and #DE-FC0206ER25749, National Science Foundation grants #CNS0403342 and #CNS-0509452; grants from Intel, Mellanox, and Sun Microsystems; and equipment donations from Intel, Mellanox, and SUN Microsystems.