A bibliography on parallel and vector numerical algorithms

This is a bibliography of numerical methods. It also includes a number of other references on machine architecture, programming language, and other topics of interest to scientific computing. Certain conference proceedings and anthologies which have been published in book form are listed also

Solution of partial differential equations on vector and parallel computers

The present status of numerical methods for partial differential equations on vector and parallel computers was reviewed. The relevant aspects of these computers are discussed and a brief review of their development is included, with particular attention paid to those characteristics that influence algorithm selection. Both direct and iterative methods are given for elliptic equations as well as explicit and implicit methods for initial boundary value problems. The intent is to point out attractive methods as well as areas where this class of computer architecture cannot be fully utilized because of either hardware restrictions or the lack of adequate algorithms. Application areas utilizing these computers are briefly discussed

A survey of the state of the art and focused research in range systems, task 2

Contract generated publications are compiled which describe the research activities for the reporting period. Study topics include: equivalent configurations of systolic arrays; least squares estimation algorithms with systolic array architectures; modeling and equilization of nonlinear bandlimited satellite channels; and least squares estimation and Kalman filtering by systolic arrays

Residue Arithmetic VLSI Array Architecture for Manipulator Pseudo-Inverse Jacobian Computation

Most Cartesian-based control strategies require the computation of the manipulator inverse Jacobian in real time at every sampling period. In some cases, the Jacobian matrix is not of full column or row rank due to singularity or redundant robot configuration. This requires the computation of the manipulator pseudo-inverse Jacobian in real time. The calculation of the pseudo-inverse Jacobian may become extremely sensitive to small perturbation in the data and numerical instabilities, when the Jacobian matrix is not of full column or row rank. Even if the Jacobian matrix is of full rank, the ill-conditioned problem may still plague the computation of the pseudoinverse Jacobian. This paper presents the use of residue arithmetic for the exact computation of the manipulator pseudo-inverse Jacobian to obviate the roundoff errors normally associated with the computations. A two-level macro-pipelined residue arithmetic array architecture implementing the Decell’s pseudo-inverse algorithm has been developed to overcome the ill-conditioned problem of the pseudo-inverse computation. Furthermore, the Decell algorithm is quite suitable for VLSI array implementation to achieve the real-time computation requirement. The first-level arrays are data-driven, wavefront-like arrays and perform the matrix multiplications, matrix diagonal additions, and trace computations. A pool or sequence of the first-level arrays are then configured into a second-level macro-pipeline with outputs of one array acting as inputs to another array in the pipe. The proposed architecture can calculate the pseudoinverse Jacobian with a pipelined time in the same computational complexity order as evaluating a matrix product in a wavefront array

A review of parallel processing approaches to robot kinematics and Jacobian

Due to continuously increasing demands in the area of advanced robot control, it became necessary to speed up the computation. One way to reduce the computation time is to distribute the computation onto several processing units. In this survey we present different approaches to parallel computation of robot kinematics and Jacobian. Thereby, we discuss both the forward and the reverse problem. We introduce a classification scheme and classify the references by this scheme

Hierarchical Parallelism in Finite Difference Analysis of Heat Conduction

Based on the concept of hierarchical parallelism, this research effort resulted in highly efficient parallel solution strategies for very large scale heat conduction problems. Overall, the method of hierarchical parallelism involves the partitioning of thermal models into several substructured levels wherein an optimal balance into various associated bandwidths is achieved. The details are described in this report. Overall, the report is organized into two parts. Part 1 describes the parallel modelling methodology and associated multilevel direct, iterative and mixed solution schemes. Part 2 establishes both the formal and computational properties of the scheme