A data and task parallel image processing environment

C Nicolescu; PP Jonker

A data and task parallel image processing environment

Research output: Contribution to journal › Article › Scientific › peer-review

Abstract

The paper presents a data and task parallel low-level image processing environment for distributed memory systems. Image processing operators are parallelized by data decomposition using algorithmic skeletons. Image processing applications are parallelized by task decomposition, based on the image application task graph. In this way, an image processing application can be parallelized both by data and task decomposition, and thus better speed-ups can be obtained. We validate our method on the multi-baseline stereo vision application. Keywords: Data parallelism; Task parallelism; Skeletons; Image processing

Original language	Undefined/Unknown
Pages (from-to)	945-965
Number of pages	21
Journal	Parallel Computing
Volume	28
Issue number	7-8
Publication status	Published - 2002

Bibliographical note

phpub 57

Keywords

academic journal papers
ZX CWTS JFIS < 1.00

Cite this

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title = "A data and task parallel image processing environment",

abstract = "The paper presents a data and task parallel low-level image processing environment for distributed memory systems. Image processing operators are parallelized by data decomposition using algorithmic skeletons. Image processing applications are parallelized by task decomposition, based on the image application task graph. In this way, an image processing application can be parallelized both by data and task decomposition, and thus better speed-ups can be obtained. We validate our method on the multi-baseline stereo vision application. Keywords: Data parallelism; Task parallelism; Skeletons; Image processing",

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AB - The paper presents a data and task parallel low-level image processing environment for distributed memory systems. Image processing operators are parallelized by data decomposition using algorithmic skeletons. Image processing applications are parallelized by task decomposition, based on the image application task graph. In this way, an image processing application can be parallelized both by data and task decomposition, and thus better speed-ups can be obtained. We validate our method on the multi-baseline stereo vision application. Keywords: Data parallelism; Task parallelism; Skeletons; Image processing

KW - academic journal papers

KW - ZX CWTS JFIS < 1.00

UR - http://www.ph.tn.tudelft.nl/People/albert/papers/PC02Nicolescu.pdf

M3 - Article

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JO - Parallel Computing

JF - Parallel Computing

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ER -

A data and task parallel image processing environment

Abstract

Bibliographical note

Keywords

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