Component‐based, problem‐solving environments for large‐scale scientific computing

Johnson, Christopher R.; Parker, Steven G.; Weinstein, David M.; Heffernan, Sean

doi:10.1002/cpe.693

Cited by 48 publications

(39 citation statements)

References 9 publications

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“…CILK [16] and Mentat [17] treated functional parallelism. SciRun [18] and UIntah [19] support graphical composition of data flow graphs of components and dynamic load balancing of task graphs. Tarragon (Cicotti and Baden) [20] supports fine grain communication and was originally targeted to cell microphysiology.…”

Section: Discussionmentioning

confidence: 99%

Hiding Communication Latency with Non-SPMD, Graph-Based Execution

Sørensen

Baden

2009

Lecture Notes in Computer Science

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Abstract. Reformulating an algorithm to mask communication delays is crucial in maintaining scalability, but traditional solutions embed the overlap strategy into the application. We present an alternative approach based on dataflow, that factors the overlap strategy out of the application. Using this approach we are able to reduce communication delays, meeting and in many cases exceeding performance obtained with traditional hand coded applications.

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Section: Discussionmentioning

confidence: 99%

Hiding Communication Latency with Non-SPMD, Graph-Based Execution

Sørensen

Baden

2009

Lecture Notes in Computer Science

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“…SCIRun version 3.0 [5,6], a scientific problem solving enironment, was released in late 2006. It includes a telemetry module based on [7], which provides a robust and secure set of Java tools for data transmission that assumes that a known broker exists to coordinate sensor data collection and use by applications.…”

Section: Problem Solving Environment Scirunmentioning

confidence: 99%

Dynamically Identifying and Tracking Contaminants in Water Bodies

Douglas

Cole

Dostert

et al. 2007

Computational Science – ICCS 2007

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Abstract. We present an overview of an ongoing project to build a DDDAS for identifying and tracking chemicals in water. The project involves a new class of intelligent sensor, building a library to optically identify molecules, communication techniques for moving objects, and a problem solving environment. We are developing an innovative environment so that we can create a symbiotic relationship between computational models for contaminant identification and tracking in water bodies and a new instrument, the Solid-State Spectral Imager (SSSI), to gather hydrological and geological data and to perform chemical analyses. The SSSI is both small and light and can scan ranges of up to about 10 meters. It can easily be used with remote sensing applications.

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“…The component-based software development environment [23,26] of the SciRun project feature powerful graphical composition of data flow graphs of components which are compiled to parallel programs. H2O [29] is a component-oriented framework for composition of distributed programs based on web services.…”

Section: Related Researchmentioning

confidence: 99%

“…Exceptions include SciRun [23,26] and several implementations of variants of the Common Component Architecture [6] including XCAT [19], Ccaffeine [14] and Babel [7,9]. The execution environments for parallel programs are much more diverse than those for sequential programs.…”

Section: Introductionmentioning

confidence: 99%

Compositional Development of Parallel Programs

Mahmood

Deng

Browne

2004

Languages and Compilers for Parallel Computing

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Abstract. This paper presents a programming model, a language (P-COM 2 ) and a compiler that composes parallel and distributed programs from independently written components. P-COM 2 is an interface definition language which incorporates information on behaviors and implementations of components to enable qualification of components for effectiveness in specific application instances and execution environments. The programming model targets development of families of related programs. One objective is to be able to compose programs which are near-optimal for given application instances and execution environments. Component-oriented development is motivated for parallel and distributed computations. The programming model is defined and described and illustrated with a simple example. The compilation process is briefly defined and described. Experience with one more complex application, a generalized fast multipole solver is sketched including performance data, some of which was surprising.

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Component‐based, problem‐solving environments for large‐scale scientific computing

Cited by 48 publications

References 9 publications

Hiding Communication Latency with Non-SPMD, Graph-Based Execution

Hiding Communication Latency with Non-SPMD, Graph-Based Execution

Dynamically Identifying and Tracking Contaminants in Water Bodies

Compositional Development of Parallel Programs

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