Piyush Mehrotra

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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)
Exploiting the 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. However, programs in Vienna Fortran are written using global data references. Thus,(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)
Data parallel languages, such as High Performance Fortran, can be successfully applied to a wide range of numerical applications. However, many advanced scienti c 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)
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 Vienna Fortran and HPF can be successfully applied to a wide range of numerical applications. However, many advanced scientiic and engineering applications are of a multidisciplinary and heterogeneous nature and thus do not t well into the data parallel paradigm. In this paper we present new Fortran 90 language extensions to(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)