Mapping Computer-Vision-Related Tasks onto Reconfigurable Parallel-Processing Systems

Authors:
Howard Jay Siegel;James B. Armstrong;Daniel W. Watson
Affiliations:
-;-;-
Venue:
Computer
Year:
1992

Citing 7
Cited 18

FFT algorithms for SIMD parallel processing systems

Journal of Parallel and Distributed Computing
Parallel computing: theory and comparisons

Parallel computing: theory and comparisons
The characteristics of parallel algorithms

The characteristics of parallel algorithms
Interconnection networks for large-scale parallel processing: theory and case studies (2nd ed.)

Interconnection networks for large-scale parallel processing: theory and case studies (2nd ed.)
Experimental analysis of a mixed-mode parallel architecture using bitonic sequence sorting

Journal of Parallel and Distributed Computing
Highly parallel computing

Highly parallel computing
The processor partitioning problem in special-purpose partitionable systems

Interconnection networks for high-performance parallel computers

A case for reconfigurable parallel architectures for information retrieval

CIKM '94 Proceedings of the third international conference on Information and knowledge management
SIMD machines: do they have a significant future?

ACM SIGARCH Computer Architecture News
Parallel Genetic Simulated Annealing: A Massively Parallel SIMD Algorithm

IEEE Transactions on Parallel and Distributed Systems
Parallel Image Correlation: Case Study to Examine Trade-Offs in Algorithm-to-Machine Mappings

The Journal of Supercomputing
Mapping Conjugate Gradient Algorithms for Neutron Diffusion Applications onto SIMD, MIMD, and Mixed-Mode Machines

International Journal of Parallel Programming
Parallel Implementations of Block-Based Motion Vector Estimation for Video Compression on Four Parallel Processing Systems

International Journal of Parallel Programming
Static scheduling algorithms for allocating directed task graphs to multiprocessors

ACM Computing Surveys (CSUR)
On the Influence of Start-Up Costs in Scheduling Divisible Loads on Bus Networks

IEEE Transactions on Parallel and Distributed Systems
A Method for the On-Line Use of Off-Line Derived Remappings ofIterative Automatic Target Recognition Tasks onto a Particular Class ofHeterogeneous Parallel Platforms

The Journal of Supercomputing
Parallel Approaches for Singular Value Decomposition as Applied to Robotic Manipulator Jacobians

International Journal of Parallel Programming
Problems with Comparing Interconnection Networks: Is an Alligator Better Than an Armadillo?

IEEE Parallel & Distributed Technology: Systems & Technology
Guest Editor's Introduction: Heterogeneous Processing

Computer
Data Management and Control-Flow Aspects of an SIMD/SPMD Parallel Language/Compiler

IEEE Transactions on Parallel and Distributed Systems
Parallel approaches for singular value decomposition as applied to robotic manipulator Jacobians

International Journal of Parallel Programming
Morphological image processing on three parallel machines

FRONTIERS '96 Proceedings of the 6th Symposium on the Frontiers of Massively Parallel Computation
On-line use of off-line derived mappings for iterative automatic target recognition tasks and a particular class of hardware platforms

HCW '97 Proceedings of the 6th Heterogeneous Computing Workshop (HCW '97)
Scheduling Divisible Loads with Processor Release Times and Finite Size Buffer Capacity Constraints in Bus Networks

Cluster Computing
Design and analysis of load distribution strategies with start-up costs in scheduling divisible loads on distributed networks

Mathematical and Computer Modelling: An International Journal

Quantified Score

Hi-index	4.10

Visualization

Abstract

A tutorial overview of how selected computer-vision-related algorithms can be mapped onto reconfigurable parallel-processing systems is presented. The reconfigurable parallel-processing system assumed for the discussions is a multiprocessor system capable of mixed-mode parallelism; that is, it can operate in either the SIMD or MIMD modes of parallelism and can dynamically switch between modes at instruction-level granularity with generally negligible overhead. In addition, it can be partitioned into independent or communicating submachines, each having the same characteristics as the original machine. Furthermore, this reconfigurable system model uses a flexible multistage cube interconnection network, which allows the connection patterns among the processors to be varied. It is demonstrated how reconfigurability can be used by reviewing and examining five computer-vision-related algorithms, each one emphasizing a different aspect of reconfigurability.