Parallel stereocorrelation on a reconfigurable multi-ring network

A reconfigurable network termed as the reconfigurable multi-ring network (RMRN) is described. The RMRN is shown to be a truly scalable network in that each node in the network has a fixed degree of connectivity and the reconfiguration mechanism ensures a network diameter of O(log₂ N) for anN-processor network. Algorithms for the two-dimensional mesh and the SIMD or SPMD n-cube are shown to map very elegantly onto the RMRN. Basic message passing and reconfiguration primitives for the SIMD/SPMD RMRN are designed for use as building blocks for more complex parallel algorithms. The RMRN is shown to be a viable architecture for image processing and computer vision problems using the parallel computation of the stereocorrelation imaging operation as an example. Stereocorrelation is one of the most computationally intensive imaging tasks. It is used as a visualization tool in many applications, including remote sensing, geographic information systems and robot vision.An earlier version of this paper was presented at the 1995 International Conference on Parallel and Distributed Processing Techniques and Applications.     

Parallel computer vision on a reconfigurable multiprocessor network

A novel reconfigurable architecture based on a multiring multiprocessor network is described. The reconfigurability of the architecture is shown to result in a low network diameter and also a low degree of connectivity for each node in the network. The mathematical properties of the network topology and the hardware for the reconfiguration switch are described. Primitive parallel operations on the network topology are described and analyzed. The architecture is shown to contain 2D mesh topologies of varying sizes and also a single one factor of the Boolean hypercube in any given configuration. A large class of algorithms for the 2D mesh and the Boolean n-cube are shown to map efficiently on the proposed architecture without loss of performance. The architecture is shown to be well suited for a number of problems in low and intermediate level computer vision such as the FFT, edge detection, template matching, and the Hough transform. Timing results for typical low and intermediate level vision algorithms on a transputer based prototype are presented     

Editorial

The Journal of Supercomputing -     

A parallel numerical algorithm on a reconfigurable multi-ring network

A reconfigurable network termed as the reconfigurable multi-ring network (RMRN) is described. The RMRN is shown to be a truly scalable network in that each node in the network has a fixed degree of connectivity and the reconfiguration mechanism ensures a network diameter of O(log₂ N) for an N-processor network. Algorithms for the two-dimensional mesh and the SIMD or SPMD n-cube are shown to map very elegantly onto the RMRN. Basic message passing and reconfiguration primitives for the SIMD/SPMD RMRN are designed for use as building blocks for more complex parallel algorithms. Elsewhere, the RMRN is shown to be a viable architecture for image processing and computer vision problems. In this paper, the RMRN is proved to be very useful for the implementation of numerical algorithms. We describe the implementation of a nontrivial numerical scheme on the RMRN. This numerical scheme is based on the inverse scattering transform and is used to study the role of nonlinear terms in Korteweg–de Vries like equations. This revised version was published online in June 2006 with corrections to the Cover Date.     

Arbitrary Rotation of Raster Images with SIMD Machine Architectures

An algorithm for the rotation of a raster image by an arbitrary angle is described. The image data structure is closely related to runlength code. The algorithm has been designed to exploit SIMD parallel architectures. It has been implemented on an ICL DAP on which non trivial images can be rotated in times very close to real time.