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https://doi.org/10.1109/empdp....
Article . 2003 . Peer-reviewed
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Integrating MPI-based numerical software into an advanced parallel computing environment

Authors: Pasqua D'Ambra; Marco Danelutto; Daniela di Serafino; Marco Lapegna;

Integrating MPI-based numerical software into an advanced parallel computing environment

Abstract

In this paper we present first experiences concerning the integration of MPI-based numerical software into an advanced programming environment for building parallel and distributed high-performance applications, which is under development in the context of Italian national research projects. Such a programming environment, named ASSIST, is based on a combination of the concepts of structured parallel programming and component-based programming. Some activities within the projects are devoted to the definition, implementation and testing of a methodology for the integration of a parallel numerical library into ASSIST. The goal is providing a set of efficient, accurate and reliable tools that can be easily used as building blocks for high-performance scientific applications. We focus on the integration of existing and widely used MPI-based numerical library modules. To this aim, we propose a general approach to embed MPI computations into the ASSIST basic programming unit. This approach has been tested using the MPICH implementation of MPI for networks of workstations. Some modifications have been applied to the MPICH process startup procedure, in order to make it compliant with the ASSIST environment. Results of experiments concerning the integration of routines from a well-known FFT package are discussed.

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Italy
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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
9
Average
Top 10%
Average