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At least 181 records · Page 10

Digital Signal Processor For GPS Receivers

Three innovative components combined to produce all-digital signal processor with superior characteristics: outstanding accuracy, high-dynamics tracking, versatile integration times, lower loss-of-lock signal strengths, and infrequent cycle slips. Three components are digital chip advancer, digital carrier downconverter and code correlator, and digital tracking processor. All-digital signal processor intended for use in receivers of Global Positioning System (GPS) for geodesy, geodynamics, high-dynamics tracking, and ionospheric calibration.

Thomas, J. B.↗

Evaluation of fault-tolerant parallel-processor architectures over long space missions

The impact of a five year space mission environment on fault-tolerant parallel processor architectures is examined. The target application is a Strategic Defense Initiative (SDI) satellite requiring 256 parallel processors to provide the computation throughput. The reliability requirements are that the system still be operational after five years with .99 probability and that the probability of system failure during one-half hour of full operation be less than 10(-7). The fault tolerance features an architecture must possess to meet these reliability requirements are presented, many potential architectures are briefly evaluated, and one candidate architecture, the Charles Stark Draper Laboratory's Fault-Tolerant Parallel Processor (FTPP) is evaluated in detail. A methodology for designing a preliminary system configuration to meet the reliability and performance requirements of the mission is then presented and demonstrated by designing an FTPP configuration.

Johnson, Sally C.↗

Optimal partitioning of random programs across two processors

The optimal partitioning of random-distributed programs is discussed. It is concluded that the optimal partitioning of a homogeneous random program over a homogeneous distributed system either assigns all modules to a single processor, or distributes the modules as evenly as possible among all processors. The analysis rests heavily on the approximation which equates the expected maximum of a set of independent random variables with the set's maximum expectation. The results are strengthened by providing an approximation-free proof of this result for two processors under general conditions on the module execution time distribution. It is also shown that use of this approximation causes two of the previous central results to be false.

Nicol, David M.↗

A microcomputer based frequency-domain processor for laser Doppler anemometry

A prototype multi-channel laser Doppler anemometry (LDA) processor was assembled using a wideband transient recorder and a microcomputer with an array processor for fast Fourier transform (FFT) computations. The prototype instrument was used to acquire, process, and record signals from a three-component wind tunnel LDA system subject to various conditions of noise and flow turbulence. The recorded data was used to evaluate the effectiveness of burst acceptance criteria, processing algorithms, and selection of processing parameters such as record length. The recorded signals were also used to obtain comparative estimates of signal-to-noise ratio between time-domain and frequency-domain signal detection schemes. These comparisons show that the FFT processing scheme allows accurate processing of signals for which the signal-to-noise ratio is 10 to 15 dB less than is practical using counter processors.

Horne, W. Clifton↗

Real time processor for array speckle interferometry

The authors are constructing a real-time processor to acquire image frames, perform array flat-fielding, execute a 64 x 64 element two-dimensional complex FFT (fast Fourier transform) and average the power spectrum, all within the 25 ms coherence time for speckles at near-IR (infrared) wavelength. The processor will be a compact unit controlled by a PC with real-time display and data storage capability. This will provide the ability to optimize observations and obtain results on the telescope rather than waiting several weeks before the data can be analyzed and viewed with offline methods. The image acquisition and processing, design criteria, and processor architecture are described.

Chin, Gordon↗

The U.S. Sarsat geosynchronous experiment - Ground processor description and test results

The development of a specialized digital signal processor, the Geosynchronous Signal Processor (GSP), for short beacon burst signal detection and demodulation is described. The processing is based on fast Fourier Transform techniques for detection and message integration on the respective message bursts for demodulation. The GSP is based on array processor technology; it is designed to yield an ultimate capacity of 50-75 simultaneous beacon transmissions within the nominal 20 KHz bandwidth centered at 406.025 MHz.

Flikkema, P. G.↗

Direct simulation Monte Carlo analysis on parallel processors

A method is presented for executing a direct simulation Monte Carlo (DSMC) analysis using parallel processing. The method is based on using domain decomposition to distribute the work load among multiple processors, and the DSMC analysis is performed completely in parallel. Message passing is used to transfer molecules between processors and to provide the synchronization necessary for the correct physical simulation. Benchmark problems are described for testing the method and results are presented which demonstrate the performance on two commercially available multicomputers. The results show that reasonable parallel speedup and efficiency can be obtained if the problem is properly sized to the number of processors. It is projected that with a massively parallel system, performance exceeding that of current supercomputers is possible.

Wilmoth, Richard G.↗

Balancing Loads Among Parallel Data Processors

Heuristic algorithm minimizes amount of memory used by multiprocessor system. Distributes load of many identical, short computations among multiple parallel digital data processors, each of which has its own (local) memory. Each processor operates on distinct and independent set of data in larger shared memory. As integral part of load-balancing scheme, total amount of space used in shared memory minimized. Possible applications include artificial neural networks or image processors for which "pipeline" and vector methods of load balancing inappropriate.

Baffes, Paul Thomas↗

Intensity dependent spread processor and workstation

The Intensity Dependent Spread (IDS) is an adaptive algorithm which is modified according to the local intensity in the scene. (This results in a nonlinear process which cannot take advantage of rather nice linear transform methods.) The computation is similar to a neural net whereby intensity information is moving from each input pixel to a set of surrounding output pixels in a manner described by Cornsweet and Yellott. A prototype of a very large scale integration IDS processor is being developed and implemented in a workstation environment. The workstation consists of a SUN 3/260 and a DATACUBE pipeline processor. The IDS prototype is a board set which operates in the DATA CUBE processor. The SUN 3/260 performs control, background processing, IDS simulation and image display functions.

Westrom, George↗

Parallel processors and nonlinear structural dynamics algorithms and software

Techniques are discussed for the implementation and improvement of vectorization and concurrency in nonlinear explicit structural finite element codes. In explicit integration methods, the computation of the element internal force vector consumes the bulk of the computer time. The program can be efficiently vectorized by subdividing the elements into blocks and executing all computations in vector mode. The structuring of elements into blocks also provides a convenient way to implement concurrency by creating tasks which can be assigned to available processors for evaluation. The techniques were implemented in a 3-D nonlinear program with one-point quadrature shell elements. Concurrency and vectorization were first implemented in a single time step version of the program. Techniques were developed to minimize processor idle time and to select the optimal vector length. A comparison of run times between the program executed in scalar, serial mode and the fully vectorized code executed concurrently using eight processors shows speed-ups of over 25. Conjugate gradient methods for solving nonlinear algebraic equations are also readily adapted to a parallel environment. A new technique for improving convergence properties of conjugate gradients in nonlinear problems is developed in conjunction with other techniques such as diagonal scaling. A significant reduction in the number of iterations required for convergence is shown for a statically loaded rigid bar suspended by three equally spaced springs.

Belytschko, Ted↗

Database for LDV signal processor performance analysis

A technique for the direct comparison of LDV signal processors is developed, based on the use of a data base of digitized signal bursts obtained from an LDV under various configurations. This data base can be used to evaluate the response of signal processors and processor algorithms to specific signal characteristics and not to generalized simplistic waveforms. Examples from such a data base are presented to illustrate the capabilities of the proposed method. This data base includes signal ensembles obtained with three laser power settings at two transmitted focal lengths.

Baker, Glenn D.↗

Adaptive domain decomposition for Monte Carlo simulations on parallel processors

A method is described for performing direct simulation Monte Carlo (DSMC) calculations on parallel processors using adaptive domain decomposition to distribute the computational work load. The method has been implemented on a commercially available hypercube and benchmark results are presented which show the performance of the method relative to current supercomputers. The problems studied were simulations of equilibrium conditions in a closed, stationary box, a two-dimensional vortex flow, and the hypersonic, rarefield flow in a two-dimensional channel. For these problems, the parallel DSMC method ran 5 to 13 times faster than on a single processor of a Cray-2. The adaptive decomposition method worked well in uniformly distributing the computational work over an arbitrary number of processors and reduced the average computational time by over a factor of two in certain cases.

Wilmoth, Richard G.↗

Computations on the massively parallel processor at the Goddard Space Flight Center

Described are four significant algorithms implemented on the massively parallel processor (MPP) at the Goddard Space Flight Center. Two are in the area of image analysis. Of the other two, one is a mathematical simulation experiment and the other deals with the efficient transfer of data between distantly separated processors in the MPP array. The first algorithm presented is the automatic determination of elevations from stereo pairs. The second algorithm solves mathematical logistic equations capable of producing both ordered and chaotic (or random) solutions. This work can potentially lead to the simulation of artificial life processes. The third algorithm is the automatic segmentation of images into reasonable regions based on some similarity criterion, while the fourth is an implementation of a bitonic sort of data which significantly overcomes the nearest neighbor interconnection constraints on the MPP for transferring data between distant processors.

Strong, James P.↗

Accuracies Of Optical Processors For Adaptive Optics

Paper presents analysis of accuracies and requirements concerning accuracies of optical linear-algebra processors (OLAP's) in adaptive-optics imaging systems. Much faster than digital electronic processor and eliminate some residual distortion. Question whether errors introduced by analog processing of OLAP overcome advantage of greater speed. Paper addresses issue by presenting estimate of accuracy required in general OLAP that yields smaller average residual aberration of wave front than digital electronic processor computing at given speed.

Downie, John D.↗

Impact of diet on the design of waste processors in CELSS

The preliminary results of a design analysis for a waste processor which employs existing technologies and takes into account the constraints of human diet are presented. The impact of diet is determined by using a model and an algorithm developed for the control and management of diet in a Controlled Ecological Life Support System (CELSS). A material and energy balance model for thermal oxidation of waste is developed which is consistent with both physical/chemical methods of incineration and supercritical water oxidation. The two models yield quantitative analysis of the diet and waste streams and the specific design parameters for waste processors, respectively. The results demonstrate that existing technologies can meet the demands of waste processing, but the choice and design of the processors or processing methods will be sensitive to the constraints of diet. The numerical examples are chosen to display the nature and extent of the gap in the available experiment information about CELSS requirements.

Waleh, Ahmad↗

An enhanced Ada run-time system for real-time embedded processors

An enhanced Ada run-time system has been developed to support real-time embedded processor applications. The primary focus of this development effort has been on the tasking system and the memory management facilities of the run-time system. The tasking system has been extended to support efficient and precise periodic task execution as required for control applications. Event-driven task execution providing a means of task-asynchronous control and communication among Ada tasks is supported in this system. Inter-task control is even provided among tasks distributed on separate physical processors. The memory management system has been enhanced to provide object allocation and protected access support for memory shared between disjoint processors, each of which is executing a distinct Ada program.

Sims, J. T.↗

Adaptive domain decomposition for Monte Carlo simulations on parallel processors

A method is described for performing direct simulation Monte Carlo (DSMC) calculations on parallel processors using adaptive domain decomposition to distribute the computational work load. The method has been implemented on a commercially available hypercube and benchmark results are presented which show the performance of the method relative to current supercomputers. The problems studied were simulations of equilibrium conditions in a closed, stationary box, a two-dimensional vortex flow, and the hypersonic, rarefied flow in a two-dimensional channel. For these problems, the parallel DSMC method ran 5 to 13 times faster than on a single processor of a Cray-2. The adaptive decomposition method worked well in uniformly distributing the computational work over an arbitrary number of processors and reduced the average computational time by over a factor of two in certain cases.

Wilmoth, Richard G.↗

Analog Processor To Solve Optimization Problems

Proposed analog processor solves "traveling-salesman" problem, considered paradigm of global-optimization problems involving routing or allocation of resources. Includes electronic neural network and auxiliary circuitry based partly on concepts described in "Neural-Network Processor Would Allocate Resources" (NPO-17781) and "Neural Network Solves 'Traveling-Salesman' Problem" (NPO-17807). Processor based on highly parallel computing solves problem in significantly less time.

Duong, Tuan A.↗