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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)
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)
Data parallel languages, such as High Performance F ortran, can be successfully applied to a wide range of numerical applications. However, many advanced scientic and engineering applications are multidisciplinary and heterogeneous in nature, and thus do not t well into the data parallel paradigm. In this paper we present Opus, a language designed to ll(More)
Distributed memory architectures offer high levels of performance and flexibility, but have proven awkward to program. Current languages for nonshared memory architectures provide a relatively low-level programming environment, and are poorly suited to modular programming, and to the construction of libraries. This paper describes a set of language(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)
Cloud computing environments are now widely available and are being increasingly utilized for technical computing. They are also being touted for high-performance computing (HPC) applications in science and engineering. For example, Amazon EC2 Services offers a specialized Cluster Compute instance to run HPC applications. In this paper, we compare the(More)
We h a v e recently introduced a set of Fortran language extensions that allow for integrated support of task and data parallelism, and provide for shared data abstractions SDAs as a method for communication and synchronization among these tasks. In this paper we discuss the design and implementation issues of the runtime system necessary to support these(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)