Cluster-Based Parallel Image Processing

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 workstation clusters are becoming a viable and economical parallel computing resource, it is important to understand how to use these environments for parallel image processing as well. In this paper we discuss our implementation of a parallel image processing software library (the Parallel Image Processing Toolkit). The library is easily extensible and hides most parallelism from the user. Inside the Toolkit, a message-passing model of parallelism is 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 with some common 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.

[1]  Ewing Lusk,et al.  User''s Guide to the p4 Parallel Programming System , 1992 .

[2]  Andrew B. Whinston,et al.  A Model for an Intelligent Operating System for Executing Image Understanding Tasks on a Reconfigurable Parallel Architecture , 1985, J. Parallel Distributed Comput..

[3]  Juan Li,et al.  A software environment for parallel computer vision , 1992, Computer.

[4]  D.-L. Lee,et al.  A multiple-processor architecture for image processing , 1987 .

[5]  Howard Jay Siegel,et al.  Mapping computer-vision-related tasks onto reconfigurable parallel-processing systems , 1992, Computer.

[6]  Greg Burns,et al.  LAM: An Open Cluster Environment for MPI , 2002 .

[7]  Edward J. Delp,et al.  Parallel implementation for iterative image restoration algorithms on a parallel DSP machine , 1993, J. VLSI Signal Process..

[8]  Anthony Skjellum,et al.  An initial implementation of MPI , 1993 .

[9]  William Gropp,et al.  MPI-2: Extending the Message-Passing Interface , 1996, Euro-Par, Vol. I.

[10]  Zang-Hee Cho,et al.  A parallel implementation of 3-D CT image reconstruction on hypercube multiprocessor , 1990 .

[11]  Viktor K. Prasanna,et al.  Parallel memory systems for image processing , 1989, Proceedings CVPR '89: IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[12]  G. A. Geist,et al.  A user's guide to PICL a portable instrumented communication library , 1990 .

[13]  Document for a Standard Message-Passing Interface , 1993 .

[14]  Anthony Skjellum,et al.  A Portable Multicomputer Communication Library atop the Reactive Kernel , 1990, Proceedings of the Fifth Distributed Memory Computing Conference, 1990..