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Exploiting the full performance potential of distributed memory machines requires a careful distribution of data across the processors. Vienna Fortran is a language extension of Fortran which provides the user with a wide range of facilities for such mapping of data structures. In contrast to current programming practice , programs in Vienna Fortran are(More)
The rapidly increasing number of cores in modern microprocessors is pushing the current high performance computing (HPC) systems into the petascale and exascale era. The hybrid nature of these systems—distributed memory across nodes and shared memory with non-uniform memory access within each node—poses a challenge to application developers. In this paper,(More)
The coordination language Opus is an object-based extension of High Performance Fortran (HPF) that supports the integration of coarse-grain task parallelism with HPF-style data parallelism. In this paper we discuss Opus in the context of multidisciplinary applications (MDAs) which execute in a heterogeneous environment. After outlining the major properties(More)
Programming nonshared memory systems is more difficult than programming shared memory systems, since there is no support for shared data structures. Current programming languages for distributed memory architectures force the user to decompose all data structures into separate pieces, with each piece “owned” by one of the processors in the(More)
The stated goal of High Performance Fortran (HPF) was to \address the problems of writing data parallel programs where the distribution of data aaects performance". After examining the current version of the language we are led to the conclusion that HPF has not fully achieved this goal. While the basic distribution functions ooered by the language {(More)
Vienna Fortran is a machine-independent language extension of Fortran, which is based upon the Single-Program-Multiple-Data (SPMD) paradigm and allows the user to write programs for distributed-memory systems using global addresses. The language features focus mainly on the issue of distributing data across virtual processor structures. In this paper, we(More)
The goal of High Performance Fortran (HPF) is to " address the problems of writing data parallel programs where the distribution of data affects performance " , providing the user with a high-level language interface for programming scalable parallel architectures and delegating to the compiler the task of producing an explicitly parallel message-passing(More)