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At least 703 records · Page 39

Elastic-plastic crack analysis using a global-local approach on a parallel computer

A global-local finite-element analysis procedure is employed to solve elastoplastic crack problems. This procedure involves a global analysis using a coarse mesh and the subsequent locally refined analysis of a number of subregions. Parallel computation is involved in the local analyses. Numerical examples are performed on a MIMD parallel computer to demonstrate the time-saving capability of the proposed procedure.

Sun, C. T.↗

Parallel-vector solution of large-scale structural analysis problems on supercomputers

A direct linear equation solution method based on the Choleski factorization procedure is presented which exploits both parallel and vector features of supercomputers. The new equation solver is described, and its performance is evaluated by solving structural analysis problems on three high-performance computers. The method has been implemented using Force, a generic parallel FORTRAN language.

Storaasli, Olaf O.↗

BLITZEN - A highly integrated massively parallel machine

The architecture and VLSI design of a new massively parallel processing array chip are described. The BLITZEN processing element array chip, which contains 1.1 million transistors, serves as the basis for a highly integrated, miniaturized, high-performance, massively parallel machine that is currently under development. Each processing element has 1K bits of static RAM and performs bit-serial processing with functional elements for arithmetic, logic, and shifting.

Blevins, D. W.↗

Energetic particle diffusion coefficients upstream of quasi-parallel interplanetary shocks

The properties of about 30 to 130-keV/e protons and alpha particles upstream of six quasi-parallel interplanetary shocks that passed by the ISEE 3 spacecraft during 1978-1979 were analyzed, and the values for the upstream energegic particle diffusion coefficient, kappa, in these six events were deduced for a number of energies and upstream positions. These observations were compared with predictions of Lee's (1983) theory of shock acceleration. It was found that the observations verified the prediction of the A/Q dependence (where A and Q are the particle atomic mass and ionization state, respectively) of kappa for alpha and proton particles upstream of the quasi-parallel shocks.

Tan, L. C.↗

Ion reflection and downstream thermalization at the quasi-parallel bow shock

Using the results of ISEE 2 plasma and magnetic field measurements, two features related to the ion thermalization process at high-Mach-number (M above 2) quasi-parallel collisionless shocks are discussed. These are the presence of a coherent secondary beam of ions within the shock layer which is considered to be produced by reflection, and downstream ion distributions which contain both a relatively cold core of directly transmitted ions and a hotter 'shell' of ions, which appear to result from the disruption and scattering of ions initially reflected at the shock. Evidence is presented that coherent ion reflection is an important element of the ion energy dissipation process at high-Mach-number quasi-parallel shocks.

Gosling, J. T.↗

Parallel projected variable metric algorithms for unconstrained optimization

The parallel variable metric optimization algorithms of Straeter (1973) and van Laarhoven (1985) are reviewed, and the possible drawbacks of the algorithms are noted. By including Davidon (1975) projections in the variable metric updating, researchers can generalize Straeter's algorithm to a family of parallel projected variable metric algorithms which do not suffer the above drawbacks and which retain quadratic termination. Finally researchers consider the numerical performance of one member of the family on several standard example problems and illustrate how the choice of the displacement vectors affects the performance of the algorithm.

Freeman, T. L.↗

Investigation of the applicability of a functional programming model to fault-tolerant parallel processing for knowledge-based systems

In a fault-tolerant parallel computer, a functional programming model can facilitate distributed checkpointing, error recovery, load balancing, and graceful degradation. Such a model has been implemented on the Draper Fault-Tolerant Parallel Processor (FTPP). When used in conjunction with the FTPP's fault detection and masking capabilities, this implementation results in a graceful degradation of system performance after faults. Three graceful degradation algorithms have been implemented and are presented. A user interface has been implemented which requires minimal cognitive overhead by the application programmer, masking such complexities as the system's redundancy, distributed nature, variable complement of processing resources, load balancing, fault occurrence and recovery. This user interface is described and its use demonstrated. The applicability of the functional programming style to the Activation Framework, a paradigm for intelligent systems, is then briefly described.

Harper, Richard↗

Parallel asynchronous systems and image processing algorithms

A new hardware approach to implementation of image processing algorithms is described. The approach is based on silicon devices which would permit an independent analog processing channel to be dedicated to evey pixel. A laminar architecture consisting of a stack of planar arrays of the device would form a two-dimensional array processor with a 2-D array of inputs located directly behind a focal plane detector array. A 2-D image data stream would propagate in neuronlike asynchronous pulse coded form through the laminar processor. Such systems would integrate image acquisition and image processing. Acquisition and processing would be performed concurrently as in natural vision systems. The research is aimed at implementation of algorithms, such as the intensity dependent summation algorithm and pyramid processing structures, which are motivated by the operation of natural vision systems. Implementation of natural vision algorithms would benefit from the use of neuronlike information coding and the laminar, 2-D parallel, vision system type architecture. Besides providing a neural network framework for implementation of natural vision algorithms, a 2-D parallel approach could eliminate the serial bottleneck of conventional processing systems. Conversion to serial format would occur only after raw intensity data has been substantially processed. An interesting challenge arises from the fact that the mathematical formulation of natural vision algorithms does not specify the means of implementation, so that hardware implementation poses intriguing questions involving vision science.

Coon, D. D.↗

The 2nd Symposium on the Frontiers of Massively Parallel Computations

Programming languages, computer graphics, neural networks, massively parallel computers, SIMD architecture, algorithms, digital terrain models, sort computation, simulation of charged particle transport on the massively parallel processor and image processing are among the topics discussed.

Mills, Ronnie↗

Image segmentation by iterative parallel region growing with application to data compression and image analysis

Image segmentation can be a key step in data compression and image analysis. However, the segmentation results produced by most previous approaches to region growing are suspect because they depend on the order in which portions of the image are processed. An iterative parallel segmentation algorithm avoids this problem by performing globally best merges first. Such a segmentation approach, and two implementations of the approach on NASA's Massively Parallel Processor (MPP) are described. Application of the segmentation approach to data compression and image analysis is then described, and results of such application are given for a LANDSAT Thematic Mapper image.

Tilton, James C.↗

BLITZEN: A highly integrated massively parallel machine

The architecture and VLSI design of a new massively parallel processing array chip are described. The BLITZEN processing element array chip, which contains 1.1 million transistors, serves as the basis for a highly integrated, miniaturized, high-performance, massively parallel machine that is currently under development. Each processing element has 1K bits of static RAM and performs bit-serial processing with functional elements for arithmetic, logic, and shifting.

Blevins, D. W.↗

Parallel algorithms for boundary value problems

A general approach to solve boundary value problems numerically in a parallel environment is discussed. The basic algorithm consists of two steps: the local step where all the P available processors work in parallel, and the global step where one processor solves a tridiagonal linear system of the order P. The main advantages of this approach are two fold. First, this suggested approach is very flexible, especially in the local step and thus the algorithm can be used with any number of processors and with any of the SIMD or MIMD machines. Secondly, the communication complexity is very small and thus can be used as easily with shared memory machines. Several examples for using this strategy are discussed.

Lin, Avi↗

On the parallel efficiency of the Frederickson-McBryan multigrid

To take full advantage of the parallelism in a standard multigrid algorithm requires as many processors as points. However, since coarse grids contain fewer points, most processors are idle during the coarse grid iterations. Frederickson and McBryan claim that retaining all points on all grid levels (using all processors) can lead to a superconvergent algorithm. The purpose of this work is to show that the parellel superconvergent multigrid (PSMG) algorithm of Frederickson and McBryan, though it achieves perfect processor utilization, is no more efficient than a parallel implementation of standard multigrid methods. PSMG is simply a new and perhaps simpler way of achieving the same results.

Decker, Naomi H.↗

Hypercluster parallel processing library user's manual

This User's Manual describes the Hypercluster Parallel Processing Library, composed of FORTRAN-callable subroutines which enable a FORTRAN programmer to manipulate and transfer information throughout the Hypercluster at NASA Lewis Research Center. Each subroutine and its parameters are described in detail. A simple heat flow application using Laplace's equation is included to demonstrate the use of some of the library's subroutines. The manual can be used initially as an introduction to the parallel features provided by the library. Thereafter it can be used as a reference when programming an application.

Quealy, Angela↗

NETRA: A parallel architecture for integrated vision systems 2: Algorithms and performance evaluation

In part 1 architecture of NETRA is presented. A performance evaluation of NETRA using several common vision algorithms is also presented. Performance of algorithms when they are mapped on one cluster is described. It is shown that SIMD, MIMD, and systolic algorithms can be easily mapped onto processor clusters, and almost linear speedups are possible. For some algorithms, analytical performance results are compared with implementation performance results. It is observed that the analysis is very accurate. Performance analysis of parallel algorithms when mapped across clusters is presented. Mappings across clusters illustrate the importance and use of shared as well as distributed memory in achieving high performance. The parameters for evaluation are derived from the characteristics of the parallel algorithms, and these parameters are used to evaluate the alternative communication strategies in NETRA. Furthermore, the effect of communication interference from other processors in the system on the execution of an algorithm is studied. Using the analysis, performance of many algorithms with different characteristics is presented. It is observed that if communication speeds are matched with the computation speeds, good speedups are possible when algorithms are mapped across clusters.

Choudhary, Alok N.↗

Computation and parallel implementation for early vision

The problem of early vision is to transform one or more retinal illuminance images-pixel arrays-to image representations built out of such primitive visual features such as edges, regions, disparities, and clusters. These transformed representations form the input to later vision stages that perform higher level vision tasks including matching and recognition. Researchers developed algorithms for: (1) edge finding in the scale space formulation; (2) correlation methods for computing matches between pairs of images; and (3) clustering of data by neural networks. These algorithms are formulated for parallel implementation of SIMD machines, such as the Massively Parallel Processor, a 128 x 128 array processor with 1024 bits of local memory per processor. For some cases, researchers can show speedups of three orders of magnitude over serial implementations.

Gualtieri, J. Anthony↗

Run-time parallelization and scheduling of loops

Run time methods are studied to automatically parallelize and schedule iterations of a do loop in certain cases, where compile-time information is inadequate. The methods presented involve execution time preprocessing of the loop. At compile-time, these methods set up the framework for performing a loop dependency analysis. At run time, wave fronts of concurrently executable loop iterations are identified. Using this wavefront information, loop iterations are reordered for increased parallelism. Symbolic transformation rules are used to produce: inspector procedures that perform execution time preprocessing and executors or transformed versions of source code loop structures. These transformed loop structures carry out the calculations planned in the inspector procedures. Performance results are presented from experiments conducted on the Encore Multimax. These results illustrate that run time reordering of loop indices can have a significant impact on performance. Furthermore, the overheads associated with this type of reordering are amortized when the loop is executed several times with the same dependency structure.

Saltz, Joel H.↗

Graphics applications utilizing parallel processing

The results are presented of research conducted to develop a parallel graphic application algorithm to depict the numerical solution of the 1-D wave equation, the vibrating string. The research was conducted on a Flexible Flex/32 multiprocessor and a Sequent Balance 21000 multiprocessor. The wave equation is implemented using the finite difference method. The synchronization issues that arose from the parallel implementation and the strategies used to alleviate the effects of the synchronization overhead are discussed.

Rice, John R.↗