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2003•Unpublished venueRequires access

Practical support for parallel programming

David C. DiNucci, Robert G. II Babb

Open publisher page 9 citations

Abstract

An approach is considered in which programs written within a higher-level parallel model are automatically transformed for execution on a particular (parallel) processor. It is based on an improved version of large-grain data-flow (LGDF) techniques. The model is described, along with a scheduler implementation strategy for shared-memory multiprocessors. Performance measurements of a specific implementation for the Sequent Balance 21000 are given. It is argued that the approach can provide the benefits of user-visible parallelism while avoiding the pitfalls inherent in hand-coding of parallel scheduling schemes.>

About this research paper

What this paper is about

An approach is considered in which programs written within a higher-level parallel model are automatically transformed for execution on a particular (parallel) processor. It is based on an improved version of large-grain data-flow (LGDF) techniques. The model is described, along with a scheduler implementation strategy for shared-memory multiprocessors. Performance measurements of a specific implementation for the Sequent Balance 21000 are given. It is argued that the approach can provide the benefits of user-visible parallelism while avoiding the pitfalls inherent in hand-coding of parallel scheduling schemes.>

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OpenAlex reports 9 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

An approach is considered in which programs written within a higher-level parallel model are automatically transformed for execution on a particular (parallel) processor. It is based on an improved version of large-grain data-flow (LGDF) techniques. The model is described, along with a scheduler implementation strategy for shared-memory multiprocessors. Performance measurements of a specific implementation for the Sequent Balance 21000 are given. It is argued that the approach can provide the benefits of user-visible parallelism while avoiding the pitfalls inherent in hand-coding of parallel scheduling schemes.>

Key concepts: Sequent, Computer science, Parallelism (grammar), Parallel computing, Coding (social sciences), Scheduling (production processes), Parallel programming model, Programming language

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