Proceedings Article10.1117/12.205484
Cluster-based parallel image processing toolkit
Jeffery M. Squyres,Andrew Lumsdaine,Robert L. Stevenson +2 more
- 23 Mar 1995
- Vol. 2421, pp 228-239
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TL;DR: This paper discusses the implementation of parallel image processing software library (the Parallel Image Processing Toolkit), which uses a message- passing model of parallelism designed around the Message Passing Interface (MPI) standard.
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Abstract: Many image processing tasks exhibit a high degree of data locality and parallelism and map quite readily to specialized massively parallel computing hardware. However, as network technologies continue to mature, workstation clusters are becoming a viable and economical parallel computing resource, so it is important to understand how to use these environments for parallel image processing as well. In this paper we discuss our implementation of parallel image processing software library (the Parallel Image Processing Toolkit). The Toolkit uses a message- passing model of parallelism designed around the Message Passing Interface (MPI) standard. Experimental results are presented to demonstrate the parallel speedup obtained with the Parallel Image Processing Toolkit in a typical workstation cluster over a wide variety of image processing tasks. We also discuss load balancing and the potential for parallelizing portions of image processing tasks that seem to be inherently sequential, such as visualization and data I/O.
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Citations
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Antonio Prestes García,F.M. Sanchez,Antonio Pérez,José Luis Pedraza,Rafael Méndez,María L. Córdoba,M. L. Muñoz +6 more
- 03 Dec 2003
TL;DR: A real-time eye-gaze tracking system that bases its accuracy in a very precise estimation of the user's pupil centre that consists of two cameras, four illuminators and a low cost cluster of four PC's interconnected by a gigabit network.
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A parallel approach to STAP implementation for fMRI data.
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6
References
•Book
Using MPI: Portable Parallel Programming with the Message-Passing Interface
William Gropp,Ewing Lusk,Anthony Skjellum +2 more
- 01 Jan 1994
TL;DR: Using MPI as mentioned in this paper provides a thoroughly updated guide to the MPI (Message-Passing Interface) standard library for writing programs for parallel computers, including a comparison of MPI with sockets.
2.9K
A User''s Guide to PVM Parallel Virtual Machine
Adam Beguelin,Jack Dongarra,Al Geist,Robert Manchek,Vaidy S. Sunderam +4 more
- 01 Jul 1991
TL;DR: This report is the PVM version 2.3 users'' guide, which contains an overview of PVM and how it is installed and used.
456
A user's guide to PICL a portable instrumented communication library
G.A. Geist,Michael T. Heath,Barry W. Peyton,P.H. Worley +3 more
- 01 Oct 1990
TL;DR: This report is the PCL user's guide, which contains an overview of PICL and how it is used and provides execution tracing that can be used to monitor performance or to aid in debugging.
A software environment for parallel computer vision
TL;DR: A software environment tailored to computer vision and image processing (CVIP) that focuses on how information about the CVIP problem domain can make the high-performance algorithms and the sophisticated algorithm techniques being designed by algorithm experts more readily available to CVIP researchers is presented.
54
A model for an intelligent operating system for executing image understanding tasks on a reconfigurable parallel architecture
TL;DR: In this article, the authors present a conceptual model that explores the potential of artificial intelligence tools, specifically expert systems, to design an Intelligent Operating System for multiprocessor systems.
40