Abstract

We have developed the HPF (High Performance Fortran) compiler HPF/SX V2 as an interface for distributed memory parallel programming. HPF is a de facto standard language for parallel programs. It is possible to write parallel programs just by inserting comment directives into existing serial Fortran programs in HPF. This paper treats two parallelization methods in the HPF/SX V2 on an SMP (Symmetric Multiprocessor) cluster system, each node of which is built by connecting multiple vector PEs (Processor Elements) with a shared memory. The one is hybrid parallelization, which consists of vectorization on a PE, multi-thread parallelization within a node, and distributed memory parallelization across nodes. The other is flat parallelization, which consists of vectorization and distributed memory parallelization. We compare hybrid parallelization with flat parallelization by evaluating several typical codes. The result shows that hybrid parallelization is particularly beneficial, when reduction of memory is expected.

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