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At least 613 records · Page 34

Management of analytical redundancy in digital flight control systems for aircraft

This paper presents a design method for optimal redundancy management for nonlinear systems with application to highly maneuvering aircraft. The approach taken is based on selecting the failure states to be covered by the system design and constructing a cost function that represents the cost of making an incorrect decision. The decision logic which minimizes the cost requires a bank of extended Kalman filters running in parallel. This produces a severe computational requirement. To reduce this requirement, a suboptimal logic is developed based on using a nonlinear single-stage prediction algorithm in the filters with filter gains and decision logic selected using steady-state results obtained from a linearization of the vehicle and sensor dynamics. The design process is then applied to designing a redundancy management system for the F8-C aircraft. Results indicate that the system is superior in failure detection to a system using the same structure but using a linear single-stage prediction algorithm in the filters.

Montgomery, R. C.↗

Basic cluster compression algorithm

Feature extraction and data compression of LANDSAT data is accomplished by BCCA program which reduces costs associated with transmitting, storing, distributing, and interpreting multispectral image data. Algorithm uses spatially local clustering to extract features from image data to describe spectral characteristics of data set. Approach requires only simple repetitive computations, and parallel processing can be used for very high data rates. Program is written in FORTRAN IV for batch execution and has been implemented on SEL 32/55.

Hilbert, E. E.↗

Impact of new computing systems on computational mechanics and flight-vehicle structures technology

Advances in computer technology which may have an impact on computational mechanics and flight vehicle structures technology were reviewed. The characteristics of supersystems, highly parallel systems, and small systems are summarized. The interrelations of numerical algorithms and software with parallel architectures are discussed. A scenario for future hardware/software environment and engineering analysis systems is presented. Research areas with potential for improving the effectiveness of analysis methods in the new environment are identified.

Noor, A. K.↗

Advanced computing

Advanced concepts in hardware, software and algorithms are being pursued for application in next generation space computers and for ground based analysis of space data. The research program focuses on massively parallel computation and neural networks, as well as optical processing and optical networking which are discussed under photonics. Also included are theoretical programs in neural and nonlinear science, and device development for magnetic and ferroelectric memories.

Source record↗

Path planning using optically computed potential fields

An algorithm for the optical computation of potential field maps suitable for mobile robot navigation is described and experimentally produced maps and paths are presented. The parallel analog optical computation employs a two-dimensional spatial light modulator on which an image of the potential field map is generated. Optically calculated fields contain no local minima, tend to produce paths centered in gaps between obstacles, and produce paths which give preference to wide gaps. Calculation of 128 x 128 pixel fields at a few hertz are possible with current technology, and calculation time vs. map size scales favorably in comparison to digital electronic computation.

Reid, Max B.↗

Parallel Signal Processing and System Simulation using aCe

Recently, networked and cluster computation have become very popular for both signal processing and system simulation. A new language is ideally suited for parallel signal processing applications and system simulation since it allows the programmer to explicitly express the computations that can be performed concurrently. In addition, the new C based parallel language (ace C) for architecture-adaptive programming allows programmers to implement algorithms and system simulation applications on parallel architectures by providing them with the assurance that future parallel architectures will be able to run their applications with a minimum of modification. In this paper, we will focus on some fundamental features of ace C and present a signal processing application (FFT).

Dorband, John E.↗

Robot acting on moving bodies (RAMBO): Preliminary results

A robot system called RAMBO is being developed. It is equipped with a camera, which, given a sequence of simple tasks, can perform these tasks on a moving object. RAMBO is given a complete geometric model of the object. A low level vision module extracts and groups characteristic features in images of the object. The positions of the object are determined in a sequence of images, and a motion estimate of the object is obtained. This motion estimate is used to plan trajectories of the robot tool to relative locations nearby the object sufficient for achieving the tasks. More specifically, low level vision uses parallel algorithms for image enchancement by symmetric nearest neighbor filtering, edge detection by local gradient operators, and corner extraction by sector filtering. The object pose estimation is a Hough transform method accumulating position hypotheses obtained by matching triples of image features (corners) to triples of model features. To maximize computing speed, the estimate of the position in space of a triple of features is obtained by decomposing its perspective view into a product of rotations and a scaled orthographic projection. This allows the use of 2-D lookup tables at each stage of the decomposition. The position hypotheses for each possible match of model feature triples and image feature triples are calculated in parallel. Trajectory planning combines heuristic and dynamic programming techniques. Then trajectories are created using parametric cubic splines between initial and goal trajectories. All the parallel algorithms run on a Connection Machine CM-2 with 16K processors.

Davis, Larry S.↗

NavP: Structured and Multithreaded Distributed Parallel Programming

We present Navigational Programming (NavP) -- a distributed parallel programming methodology based on the principles of migrating computations and multithreading. The four major steps of NavP are: (1) Distribute the data using the data communication pattern in a given algorithm; (2) Insert navigational commands for the computation to migrate and follow large-sized distributed data; (3) Cut the sequential migrating thread and construct a mobile pipeline; and (4) Loop back for refinement. NavP is significantly different from the current prevailing Message Passing (MP) approach. The advantages of NavP include: (1) NavP is structured distributed programming and it does not change the code structure of an original algorithm. This is in sharp contrast to MP as MP implementations in general do not resemble the original sequential code; (2) NavP implementations are always competitive with the best MPI implementations in terms of performance. Approaches such as DSM or HPF have failed to deliver satisfying performance as of today in contrast, even if they are relatively easy to use compared to MP; (3) NavP provides incremental parallelization, which is beyond the reach of MP; and (4) NavP is a unifying approach that allows us to exploit both fine- (multithreading on shared memory) and coarse- (pipelined tasks on distributed memory) grained parallelism. This is in contrast to the currently popular hybrid use of MP+OpenMP, which is known to be complex to use. We present experimental results that demonstrate the effectiveness of NavP.

navigational programming (NavP)↗

Scalable quantum computational science: A perspective from block-encodings and polynomial transformations

Significant developments made in quantum hardware and error correction recently have been driving quantum computing toward practical utility. However, gaps remain between abstract quantum algorithmic development and practical applications in computational sciences. In this perspective article, we propose several properties that scalable quantum computational science methods should possess. We further discuss how block-encodings and polynomial transformations can potentially serve as a unified framework with the desired properties. Recent advancements on these topics are presented, including the construction and assembly of block-encodings, and various generalizations of quantum signal processing (QSP) algorithms to perform polynomial transformations. The scalability of QSP methods on parallel and distributed quantum architectures is also highlighted. Promising applications in simulation and observable estimation in chemistry, physics, and optimization problems are presented. We hope this perspective serves as a gentle introduction to state-of-the-art quantum algorithms for the computational science community and inspires future development of scalable quantum computational science methodologies that bridge theory and practice.

Bayesian inference↗

Computing the QRPA level density with the finite amplitude method

Here, we describe a new algorithm to calculate the vibrational nuclear level density of an atomic nucleus. Fictitious perturbation operators that probe the response of the system are generated by drawing their matrix elements from some probability distribution function. We use the Finite Amplitude Method to explicitly compute the response for each such sample. With the help of the Kernel Polynomial Method, we build an estimator of the vibrational level density and provide the upper bound of the relative error in the limit of infinitely many random samples. The new algorithm can give accurate estimates of the vibrational level density. Since it is based on drawing multiple samples of perturbation operators, its computational implementation is naturally parallel and scales like the number of available processing units.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Cumulative reports and publications through 31 December 1983

All reports for the calendar years 1975 through December 1983 are listed by author. Since ICASE reports are intended to be preprints of articles for journals and conference proceedings, the published reference is included when available. Thirteen older journal and conference proceedings references are included as well as five additional reports by ICASE personnel. Major categories of research covered include: (1) numerical methods, with particular emphasis on the development and analysis of basic algorithms; (2) computational problems in engineering and the physical sciences, particularly fluid dynamics, acoustics, structural analysis, and chemistry; and (3) computer systems and software, especially vector and parallel computers, microcomputers, and data management.

Source record↗

Parallel processing environment for multi-flexible body dynamics

The implementation of a dynamics solution algorithm with inherent parallelism which is applicable to the dynamics of large flexible space structures is described. The algorithm is unique in that parts of the solution can be computed simultaneously by working with different branches of its tree topology. The algorithm exhibits close to 0(n) type behavior. The data flow within the solution algorithm is discussed along with results from its implementation in a multiprocessing environment. A model of the United States Space Station is used as an example. The results show that, with fast multiple scalar processors, an efficient algorithm, and symbolically generated equations of motion, real-time performance can be achieved with present-day hardware technology, even with complex dynamical models.

Venugopal, Ravi↗

Unsteady turbomachinery flow simulations on massively parallel architectures

The accurate numerical simulation of unsteady, three-dimensional viscous flow in turbomachines is computationally very intensive, requiring prohibitively large amounts of computer time on current vector supercomputers. In recent years, computer systems based on massively parallel architectures have been developed that offer the promise of meeting the computational power requirements of such large-scale simulations. However, a rethinking of existing algorithms and methodology is required in order to fully harness the computational power of such architectures. In this paper the capabilities of the Connection Machine (CM-2) in predicting unsteady flows in turbomachines are evaluated. The implementation on the CM-2 of an implicit, time-accurate, zonal algorithm for the Navier-Stokes equations in two dimensions is described. Programming issues and modifications made to the original algorithm (developed for vector, pipelined supercomputers) in order to improve performance on the CM-2 are outlined. Algorithm performance is evaluated and compared with a functionally equivalent code for the CRAY-YMP.

Madavan, N. K.↗

A Parallel Incompressible Navier-Stokes Solver With a Parallel Multigrid Elliptic Kernal

The paper describes numerical algorithms and parallel implementations of a time-dependent, incompressible Navier-Stokes flow solver and a multigrid elliptic solver, which is also used as a computation kernal in the flow solver. The implemented solvers are numerically stable and computationally efficient, and they scale well to a large number of processors for problems with moderate granularity.

solver Navier-Stokes solver multigrid elliptic sol↗

Implementing Connected Component Labeling as a User Defined Operator for SciDB

We have implemented a flexible User Defined Operator (UDO) for labeling connected components of a binary mask expressed as an array in SciDB, a parallel distributed database management system based on the array data model. This UDO is able to process very large multidimensional arrays by exploiting SciDB's memory management mechanism that efficiently manipulates arrays whose memory requirements far exceed available physical memory. The UDO takes as primary inputs a binary mask array and a binary stencil array that specifies the connectivity of a given cell to its neighbors. The UDO returns an array of the same shape as the input mask array with each foreground cell containing the label of the component it belongs to. By default, dimensions are treated as non-periodic, but the UDO also accepts optional input parameters to specify periodicity in any of the array dimensions. The UDO requires four stages to completely label connected components. In the first stage, labels are computed for each subarray or chunk of the mask array in parallel across SciDB instances using the weighted quick union (WQU) with half-path compression algorithm. In the second stage, labels around chunk boundaries from the first stage are stored in a temporary SciDB array that is then replicated across all SciDB instances. Equivalences are resolved by again applying the WQU algorithm to these boundary labels. In the third stage, relabeling is done for each chunk using the resolved equivalences. In the fourth stage, the resolved labels, which so far are "flattened" coordinates of the original binary mask array, are renamed with sequential integers for legibility. The UDO is demonstrated on a 3-D mask of O(1011) elements, with O(108) foreground cells and O(106) connected components. The operator completes in 19 minutes using 84 SciDB instances.

UDO↗

Field lines and magnetic surfaces in a two-component slab/2D model of interplanetary magnetic fluctuations

A two-component model for the spectrum of interplanetary magnetic fluctuations was proposed on the basis of ISEE observations, and has found an intriguing level of application in other solar wind studies. The model fluctuations consist of a fraction of 'slab' fluctuations, varying only in the direction parallel to the locally uniform mean magnetic field B(0) and a complement of 2D (two-dimensional) fluctuations that vary in the directions transverse to B(0). We have developed an spectral method computational algorithm for computing the magnetic flux surfaces (flux tubes) associated with the composite model, based upon a precise analogy with equations for ideal transport of a passive scalar in planar two dimensional geometry. Visualization of various composite models will be presented, including the 80 percent 2D/ 20 percent slab model with delta B/B(0) approximately equals 1 and a minus 5/3 spectral law, that is thought to approximately represent a snapshot of solar wind turbulence. Characteristically, the visualizations show that flux tubes, even when defined as regular on some plane, shred and disperse rapidly as they are viewed along the parallel direction. This diffusive process, which generalizes the standard picture of field line random walk, will be discussed in detail. Evidently, the traditional picture that flux tubes randomize like strands of spaghetti with a uniform tangle along the axial direction is in need of modification.

Matthaeus, W. H.↗

Approximate algorithms for partitioning and assignment problems

The problem of optimally assigning the modules of a parallel/pipelined program over the processors of a multiple computer system under certain restrictions on the interconnection structure of the program as well as the multiple computer system was considered. For a variety of such programs it is possible to find linear time if a partition of the program exists in which the load on any processor is within a certain bound. This method, when combined with a binary search over a finite range, provides an approximate solution to the partitioning problem. The specific problems considered were: a chain structured parallel program over a chain-like computer system, multiple chain-like programs over a host-satellite system, and a tree structured parallel program over a host-satellite system. For a problem with m modules and n processors, the complexity of the algorithm is no worse than O(mnlog(W sub T/epsilon)), where W sub T is the cost of assigning all modules to one processor and epsilon the desired accuracy.

Iqbal, M. A.↗

High-speed computerized tomography

The development of a high-speed reconstruction processor and a channelized architecture to use with a high-resolution tomographic unit is discussed with attention to the convolution reconstruction algorithm. By means of this algorithm, input data and intermediate result precision required throughout the algorithm execution have been studied with computer simulation using profile data derived from mathematically simulated test objects and experimental animal data. A prototype section for a highly parallel all-digital system executes 60 million arithmetic operations per second, and the full-scale version is expected to reconstruct 500 to 1000 cross sections per second.

Swartzlander, E. E., Jr.↗