A framework for data-flow distributed processing is established through the definition of a data-flow model and a set of language constructs for concurrent programming. The proposed approach is based on the following characteristics: i) the exploitation of parallelism at the operation level leads to the efficient and natural exploitation of parallelism at the program level, and ii) parallelism, communication, nondeterminism and history sensitivity are primitive concepts. The aim of the defined data-flow constructs is to enhance modularity and parallelism of programs. Two structuring levels are introduced, called «modules» and «frames», to permit both symmetric and asymmetric communication. Single assignment and guarded commands are employed inside modules. Examples of tipical programming problems, including shared resources management, are given together with a short account of a distributed data-flow architecture able to support data-flow distributed processing efficiently.

A framework for data-flow distributed processing

DE FRANCESCO, NICOLETTA;VAGLINI, GIGLIOLA;VANNESCHI, MARCO
1980

Abstract

A framework for data-flow distributed processing is established through the definition of a data-flow model and a set of language constructs for concurrent programming. The proposed approach is based on the following characteristics: i) the exploitation of parallelism at the operation level leads to the efficient and natural exploitation of parallelism at the program level, and ii) parallelism, communication, nondeterminism and history sensitivity are primitive concepts. The aim of the defined data-flow constructs is to enhance modularity and parallelism of programs. Two structuring levels are introduced, called «modules» and «frames», to permit both symmetric and asymmetric communication. Single assignment and guarded commands are employed inside modules. Examples of tipical programming problems, including shared resources management, are given together with a short account of a distributed data-flow architecture able to support data-flow distributed processing efficiently.
DE FRANCESCO, Nicoletta; Perego, G.; Vaglini, Gigliola; Vanneschi, Marco
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11568/208677
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