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At least 1,189 records · Page 66

A simplified procedure for correcting both errors and erasures of a Reed-Solomon code using the Euclidean algorithm

It is well known that the Euclidean algorithm or its equivalent, continued fractions, can be used to find the error locator polynomial and the error evaluator polynomial in Berlekamp's key equation needed to decode a Reed-Solomon (RS) code. A simplified procedure is developed and proved to correct erasures as well as errors by replacing the initial condition of the Euclidean algorithm by the erasure locator polynomial and the Forney syndrome polynomial. By this means, the errata locator polynomial and the errata evaluator polynomial can be obtained, simultaneously and simply, by the Euclidean algorithm only. With this improved technique the complexity of time domain RS decoders for correcting both errors and erasures is reduced substantially from previous approaches. As a consequence, decoders for correcting both errors and erasures of RS codes can be made more modular, regular, simple, and naturally suitable for both VLSI and software implementation. An example illustrating this modified decoding procedure is given for a (15, 9) RS code.

Truong, T. K.↗

An efficient algorithm for computing the crossovers in satellite altimetry

An efficient algorithm has been devised to compute the crossovers in satellite altimetry. The significance of the crossovers is twofold. First, they are needed to perform the crossover adjustment to remove the orbit error. Secondly, they yield important insight into oceanic variability. Nevertheless, there is no published algorithm to make this very time consuming task easier, which is the goal of this report. The success of the algorithm is predicated on the ability to predict (by analytical means) the crossover coordinates to within 6 km and 1 sec of the true values. Hence, only one interpolation/extrapolation step on the data is needed to derive the crossover coordinates in contrast to the many interpolation/extrapolation operations usually needed to arrive at the same accuracy level if deprived of this information.

Tai, Chang-Kou↗

Investigation of candidate data structures and search algorithms to support a knowledge based fault diagnosis system

The focus of this research is the investigation of data structures and associated search algorithms for automated fault diagnosis of complex systems such as the Hubble Space Telescope. Such data structures and algorithms will form the basis of a more sophisticated Knowledge Based Fault Diagnosis System. As a part of the research, several prototypes were written in VAXLISP and implemented on one of the VAX-11/780's at the Marshall Space Flight Center. This report describes and gives the rationale for both the data structures and algorithms selected. A brief discussion of a user interface is also included.

Bosworth, Edward L., Jr.↗

Parallel algorithms for mapping pipelined and parallel computations

Many computational problems in image processing, signal processing, and scientific computing are naturally structured for either pipelined or parallel computation. When mapping such problems onto a parallel architecture it is often necessary to aggregate an obvious problem decomposition. Even in this context the general mapping problem is known to be computationally intractable, but recent advances have been made in identifying classes of problems and architectures for which optimal solutions can be found in polynomial time. Among these, the mapping of pipelined or parallel computations onto linear array, shared memory, and host-satellite systems figures prominently. This paper extends that work first by showing how to improve existing serial mapping algorithms. These improvements have significantly lower time and space complexities: in one case a published O(nm sup 3) time algorithm for mapping m modules onto n processors is reduced to an O(nm log m) time complexity, and its space requirements reduced from O(nm sup 2) to O(m). Run time complexity is further reduced with parallel mapping algorithms based on these improvements, which run on the architecture for which they create the mappings.

Nicol, David M.↗

Strategies for concurrent processing of complex algorithms in data driven architectures

Research directed at developing a graph theoretical model for describing data and control flow associated with the execution of large grained algorithms in a special distributed computer environment is presented. This model is identified by the acronym ATAMM which represents Algorithms To Architecture Mapping Model. The purpose of such a model is to provide a basis for establishing rules for relating an algorithm to its execution in a multiprocessor environment. Specifications derived from the model lead directly to the description of a data flow architecture which is a consequence of the inherent behavior of the data and control flow described by the model. The purpose of the ATAMM based architecture is to provide an analytical basis for performance evaluation. The ATAMM model and architecture specifications are demonstrated on a prototype system for concept validation.

Stoughton, John W.↗

An improved simulated annealing algorithm for standard cell placement

Simulated annealing is a general purpose Monte Carlo optimization technique that was applied to the problem of placing standard logic cells in a VLSI ship so that the total interconnection wire length is minimized. An improved standard cell placement algorithm that takes advantage of the performance enhancements that appear to come from parallelizing the uniprocessor simulated annealing algorithm is presented. An outline of this algorithm is given.

Jones, Mark↗

Efficient multiplication algorithms over the finite fields GF(q sup m), where q equals 3,5

Finite field multiplication is central to coding theory. For this application, there is a need for a multiplication algorithm which can be realized easily on VLSI chips. A new algorithm is developed which is based on the Babylonian multiplication technique utilizing tables of squares. This algorithm is applied to the finite fields GF(q sup m), where q equals 3 and 5. It is also shown that this multiplier can be used to compute complex multiplications defined on the direct sum of two identical copies of such Galois fields.

Truong, T. K.↗

A streamwise upwind algorithm for the Euler and Navier-Stokes equations applied to transonic flows

A new algorithm was developed for the Euler and Navier-Stokes equations that uses upwind differencing based on the streawise direction. This algorithm is time accurate and can be used in codes for calculating unsteady transonic flows over wings. Such codes can be used for the flutter analysis of wings. In this algorithm, the coordinate system is locally rotated to align with the streamwise direction. For differencing the convective terms in the streamwise direction, a new form of flux splitting is employed, in which the biasing depends on the local Mach number. In the plane perpendicular to the stream direction, the new flux splitting uses the condition of no flow in that local plane. By using a locally rotated coordinate system, the convective flux vector biasing depends on the total Mach number. Hence, the switching of the flux vector biasing occurs across shock waves and the proper domain of dependence is used in supersonic regions. For comparison, many other upwind methods switch differencing based on Mach number of shock waves in multidimensional flows. The formulas for the convective flux vector differencing do not contain any user specified parameters. So, the amount of numerical dissipation is automatically determined.

Goorjian, Peter M.↗

Array architectures for iterative algorithms

Regular mesh-connected arrays are shown to be isomorphic to a class of so-called regular iterative algorithms. For a wide variety of problems it is shown how to obtain appropriate iterative algorithms and then how to translate these algorithms into arrays in a systematic fashion. Several 'systolic' arrays presented in the literature are shown to be specific cases of the variety of architectures that can be derived by the techniques presented here. These include arrays for Fourier Transform, Matrix Multiplication, and Sorting.

Jagadish, Hosagrahar V.↗

Performance of a parallel algorithm for standard cell placement on the Intel Hypercube

A parallel simulated annealing algorithm for standard cell placement on the Intel Hypercube is presented. A novel tree broadcasting strategy is used extensively for updating cell locations in the parallel environment. Studies on the performance of the algorithm on example industrial circuits show that it is faster and gives better final placement results than uniprocessor simulated annealing algorithms.

Jones, Mark↗

On a finite element CFD algorithm for compressible, viscous and turbulent aerodynamic flows

This paper develops and analyses individual construction aspects of an efficient and accurate finite element algorithm for prediction of viscous and turbulent flow fields of impact in aerodynamics. The theoretical construction employs a Taylor weak statement (TWS) for coincident embedding of stability mechanisms within a classic Galerkin finite element formulation of semidiscrete approximation error orthogonalization. A wide variety of the stabilizing mechanisms of independently derived CFD algorithms are contained within the TWS theory. An implicit construction that meets the requirement of efficient convergence to steady state is developed. The theoretical asymptotic error estimates of the TWS finite element algorithm for supersonic and viscous boundary layer flows are verified. Application to a three-dimensional turbulent flow is cited.

Baker, A. J.↗

Explicit upwind algorithm for the parabolized Navier-Stokes equations

A new explicit upwind algorithm based on Roe's flux-difference splitting (FDS) method has been developed for the three-dimensional Parabolized Navier-Stokes (PNS) equations. For three-dimensional flows, FDS's are determined separately for the two nonmarching directions and modified to account for the calculated shock angle in the crossflow plane. Second-order FDS is applied to the pressure and convection terms with the streamwise pressure gradient limited in the subsonic region to maintain a hyperbolic inviscid equation set. Second-order central differencing is obtained in the two-step algorithm for the shear and heat flux terms. The new algorithm is demonstrated for three laminar flow test cases: supersonic flow over a flat plate, hypersonic flow over a 15 deg ramp, and hypersonic flow past a 10 deg cone at a 24 deg angle of attack. The computed results agree well with experimental measurements.

Korte, John J.↗

Towards developing robust algorithms for solving partial differential equations on MIMD machines

Methods for efficient computation of numerical algorithms on a wide variety of MIMD machines are proposed. These techniques reorganize the data dependency patterns to improve the processor utilization. The model problem finds the time-accurate solution to a parabolic partial differential equation discretized in space and implicitly marched forward in time. The algorithms are extensions of Jacobi and SOR. The extensions consist of iterating over a window of several timesteps, allowing efficient overlap of computation with communication. The methods increase the degree to which work can be performed while data are communicated between processors. The effect of the window size and of domain partitioning on the system performance is examined both by implementing the algorithm on a simulated multiprocessor system.

Saltz, Joel H.↗

A sparse matrix algorithm on the Boolean vector machine

VLSI technology is being used to implement a prototype Boolean Vector Machine (BVM), which is a large network of very small processors with equally small memories that operate in SIMD mode; these use bit-serial arithmetic, and communicate via cube-connected cycles network. The BVM's bit-serial arithmetic and the small memories of individual processors are noted to compromise the system's effectiveness in large numerical problem applications. Attention is presently given to the implementation of a basic matrix-vector iteration algorithm for space matrices of the BVM, in order to generate over 1 billion useful floating-point operations/sec for this iteration algorithm. The algorithm is expressed in a novel language designated 'BVM'.

Wagner, Robert A.↗

Advances in dual algorithms and convex approximation methods

A new algorithm for solving the duals of separable convex optimization problems is presented. The algorithm is based on an active set strategy in conjunction with a variable metric method. This first order algorithm is more reliable than Newton's method used in DUAL-2 because it does not break down when the Hessian matrix becomes singular or nearly singular. A perturbation technique is introduced in order to remove the nondifferentiability of the dual function which arises when linear constraints are present in the approximate problem.

Smaoui, H.↗

An algorithm for a generalization of the Richardson extrapolation process

The paper presents a recursive method, designated the W exp (m)-algorithm, for implementing a generalization of the Richardson extrapolation process. Compared to the direct solution of the linear sytems of equations defining the extrapolation procedure, this method requires a small number of arithmetic operations and very little storage. The technique is also applied to solve recursively the coefficient problem associated with the rational approximations obtained by applying a d-transformation to power series. In the course of development a new recursive algorithm for implementing a very general extrapolation procedure is introduced, for solving the same problem. A FORTRAN program for the W exp (m)-algorithm is also appended.

Ford, William F.↗

Differential sampling for fast frequency acquisition via adaptive extended least squares algorithm

This paper presents a differential signal model along with appropriate sampling techinques for least squares estimation of the frequency and frequency derivatives and possibly the phase and amplitude of a sinusoid received in the presence of noise. The proposed algorithm is recursive in mesurements and thus the computational requirement increases only linearly with the number of measurements. The dimension of the state vector in the proposed algorithm does not depend upon the number of measurements and is quite small, typically around four. This is an advantage when compared to previous algorithms wherein the dimension of the state vector increases monotonically with the product of the frequency uncertainty and the observation period. Such a computational simplification may possibly result in some loss of optimality. However, by applying the sampling techniques of the paper such a possible loss in optimality can made small.

Kumar, Rajendra↗

Design and implementation of parallel multigrid algorithms

Techniques for mapping multigrid algorithms to solve elliptic PDEs on hypercube parallel computers are described and demonstrated. The need for proper data mapping to minimize communication distances is stressed, and an execution-time model is developed to show how algorithm efficiency is affected by changes in the machine and algorithm parameters. Particular attention is then given to the case of coarse computational grids, which can lead to idle processors, load imbalances, and inefficient performance. It is shown that convergence can be improved by using idle processors to solve a new problem concurrently on the fine grid defined by a splitting.

Chan, Tony F.↗