Overcoming Performance Bottlenecks in Using OpenMP on SMP Clusters Woo-Chul Jeun a Yang-Suk Kee b, ∗ Soonhoi Ha a

This paper presents a new parallel programming environment called ParADE to enable easy, portable, and high-performance computing for SMP clusters. Different from the prior studies, ParADE separates the programming model from the exe-cution model: it enables shared-address-space programming while it realizes hybrid execution of message-passing and shared-address-space. To overcome the poor per-formance of conventional OpenMP on SDSM (Software Distributed Shared Mem-ory), ParADE implements an intelligent OpenMP translator supporting efficient mutual exclusion and efficient page transmission. The experimental results on a Linux cluster demonstrate that ParADE reduces mutual exclusion overhead and overall execution time