High performance Fortran

Loveman, David B.

doi:10.1109/88.219857

Cited by 158 publications

(51 citation statements)

References 6 publications

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“…The comparison, however, should be made with other parallel programming languages. Even High Performance Fortran (Loveman, 1993) has many of the complexities that can be seen in EC. The current state-of-art in Distributed Programming is such that such com-plexities seem difficult to remove.…”

Section: Resultsmentioning

confidence: 99%

EC : A Language for Distributed Computing

Naik

Barua

1995

Computer Networks, Architecture and Applications

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Computation intensive programs can utilise idle workstations in a cluster by exploiting the parallelism inherent in the problem being solved. A programming language for distributed computing offers advantages like early detection of type mismatch in communication and offers structured mechanisms to specify possible overlap in communication and computation, and exception handling for catching run time errors. Success of a language depends on its ease of use, expressibility and efficient implementation of its constructs.EC is a super set of C supporting process creation, a message passing mechanism, and exception handling. The pipelined communication constructs and multiple process instances help in expressing concurrency between computation and communication. Data driven activation of EC processes is used for scheduling.EC has been implemented in a Sun-3 workstation cluster. An inter-node message passing mechanism has been built on top of the socket interface using the TCP protocol, and intra-node message passing is done by passing pointers to improve efficiency. However, message_type variables hide the implementation details, improve type safety and location transparency of a program.

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Section: Resultsmentioning

confidence: 99%

EC : A Language for Distributed Computing

Naik

Barua

1995

Computer Networks, Architecture and Applications

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“…In languages with semiexplicit parallelism like GPH or Eden, the programmer specifies only a few key coordination aspects, for example, what threads to create, and the language implementation automatically manages the remaining coordination aspects. In an implicitly parallel language like High-Performance Fortran [11] or PMLS [12], the programmer does not specify coordination aspects, as the parallelism is implicit in the language semantics.…”

Section: High-level Parallel Coordinationmentioning

confidence: 99%

Evaluating a High-Level Parallel Language (GpH) for Computational GRIDs

Zain¹,

Trinder²,

Michaelson

et al. 2008

IEEE Trans. Parallel Distrib. Syst.

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Abstract-Computational GRIDs potentially offer low-cost, readily available, and large-scale high-performance platforms. For the parallel execution of programs, however, computational GRIDs pose serious challenges: they are heterogeneous and have hierarchical and often shared interconnects, with high and variable latencies between clusters. This paper investigates whether a programming language with high-level parallel coordination and a Distributed Shared Memory (DSM) model can deliver good and scalable performance on a range of computational GRID configurations. The high-level language Glasgow parallel Haskell (GpH) abstracts over the architectural complexities of the computational GRID, and we have developed GRID-GUM2, a sophisticated grid-specific implementation of GpH, to produce the first high-level DSM parallel language implementation for computational GRIDs. We report a systematic performance evaluation of GRID-GUM2 on combinations of high/low and homogeneous/heterogeneous computational GRIDs. We measure the performance of a small set of kernel parallel programs representing a variety of application areas, two parallel paradigms, and ranges of communication degree and parallel irregularity. We investigate GRI D-GUM2's performance scalability on medium-scale heterogeneous and high-latency computational GRIDs and analyze the performance with respect to the program characteristics of communication frequency and degree of irregular parallelism.

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“…Programming models can range from purely task based models like Intel's TBB [4], Cilk [5], or PLASMA [6], to globally synchronous approaches, such as BSP [7]. Furthermore, they can be based on a common memory paradigm like Global Arrays [8] or HPF [9] or be data-driven, such as CHARM++ [10]. In contrast to these application domain independent systems, DSLs seek to create a language for a specific problem domain, such as MATLAB [11] for linear algebra, Liszt [12] for partial differential equations and SEQUEL [13] for databases.…”

Section: Introductionmentioning

confidence: 99%

Exploring Traditional and Emerging Parallel Programming Models Using a Proxy Application

Karlin

Bhatele

Keasler

et al. 2013

2013 IEEE 27th International Symposium on Parallel and Distributed Processing

158

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Abstract-Parallel machines are becoming more complex with increasing core counts and more heterogeneous architectures. However, the commonly used parallel programming models, C/C++ with MPI and/or OpenMP, make it difficult to write source code that is easily tuned for many targets. Newer language approaches attempt to ease this burden by providing optimization features such as automatic load balancing, overlap of computation and communication, message-driven execution, and implicit data layout optimizations. In this paper, we compare several implementations of LULESH, a proxy application for shock hydrodynamics, to determine strengths and weaknesses of different programming models for parallel computation. We focus on four traditional (OpenMP, MPI, MPI+OpenMP, CUDA) and four emerging (Chapel, Charm++, Liszt, Loci) programming models. In evaluating these models, we focus on programmer productivity, performance and ease of applying optimizations.

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High performance Fortran

Cited by 158 publications

References 6 publications

EC : A Language for Distributed Computing

EC : A Language for Distributed Computing

Evaluating a High-Level Parallel Language (GpH) for Computational GRIDs

Exploring Traditional and Emerging Parallel Programming Models Using a Proxy Application

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