ParADE: An OpenMP Programming Environment for SMP Cluster Systems

Demand for programming environments to exploit clusters of symmetric multiprocessors (SMPs) is increasing. In this paper, we present a new programming environment, called ParADE, to enable easy, portable, and high-performance programming on SMP clusters. It is an OpenMP programming environment on top of a multi-threaded software distributed shared memory (SDSM) system with a variant of home-based lazy release consistency protocol. To boost performance, the runtime system provides explicit message-passing primitives to make it a hybrid-programming environment. Collective communication primitives are used for the synchronization and work-sharing directives associated with small data structures, lessening the synchronization overhead and avoiding the implicit barriers of work-sharing directives. The OpenMP translator bridges the gap between the OpenMP abstraction and the hybrid programming interfaces of the runtime system. The experiments with several NAS benchmarks and applications on a Linux-based cluster show promising results that ParADE overcomes the performance problem of the conventional SDSM-based OpenMP environment.