OpenMP is attracting wide-spread interest because of its easy-to-use parallel programming model for shared memory multiprocessors. We have implemented a "cluster-enabled" OpenMP compiler for a page-based software distributed shared memory system, SCASH, which works on a cluster of PCs. It allows OpenMP programs to run transparently in a distributed memory environment. The compiler transforms OpenMP programs into parallel programs using SCASH so that shared global variables are allocated at run time in the shared address space of SCASH. A set of directives is added to specify data mapping and loop scheduling method which schedules iterations onto threads associated with the data mapping. Our experimental results show that the data mapping may greatly impact on the performance of OpenMP programs in the software distributed shared memory system. The performance of some NAS parallel benchmark programs in OpenMP is improved by using our extended directives.
SilkRoad: a multithreaded runtime system with software distributed shared memory for SMP clusters