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At least 721 records · Page 40

Optimization by nonhierarchical asynchronous decomposition

Large scale optimization problems are tractable only if they are somehow decomposed. Hierarchical decompositions are inappropriate for some types of problems and do not parallelize well. Sobieszczanski-Sobieski has proposed a nonhierarchical decomposition strategy for nonlinear constrained optimization that is naturally parallel. Despite some successes on engineering problems, the algorithm as originally proposed fails on simple two dimensional quadratic programs. The algorithm is carefully analyzed for quadratic programs, and a number of modifications are suggested to improve its robustness.

Shankar, Jayashree↗

High performance compression of science data

In the future, NASA expects to gather over a tera-byte per day of data requiring space for levels of archival storage. Data compression will be a key component in systems that store this data (e.g., optical disk and tape) as well as in communications systems (both between space and Earth and between scientific locations on Earth). We propose to develop algorithms that can be a basis for software and hardware systems that compress a wide variety of scientific data with different criteria for fidelity/bandwidth tradeoffs. The algorithmic approaches we consider are specially targeted for parallel computation where data rates of over 1 billion bits per second are achievable with current technology.

Storer, James A.↗

Optimal message log reclamation for uncoordinated checkpointing

Uncoordinated checkpointing for message-passing systems allows maximum process autonomy and general nondeterministic execution, but suffers from potential domino effect and the large space overhead for maintaining checkpoints and message logs. Traditionally, it has been assumed that only obsolete checkpoints and message logs before the global recovery line can be garbage-collected. Recently, an approach to identifying all garbage checkpoints based on recovery line transformation and decomposition has been developed. We show in this paper that the same approach can be applied to the problem of identifying all garbage message logs for systems requiring message logging to record in-transit messages. Communication trace-driven simulation for several parallel programs is used to evaluate the proposed algorithm.

Wang, Yi-Min↗

Massively parallel neurocomputing for aerospace applications

An innovative hybrid, analog-digital charge-domain technology, for the massively parallel VLSI implementation of certain large scale matrix-vector operations, has recently been introduced. It employs arrays of Charge Coupled/Charge Injection Device cells holding an analog matrix of charge, which process digital vectors in parallel by means of binary, non-destructive charge transfer operations. The impact of this technology on massively parallel processing is discussed. Fundamentally new classes of algorithms, specifically designed for this emerging technology, as applied to signal processing, are derived.

Fijany, Amir↗

High performance compression of science data

In the future, NASA expects to gather over a tera-byte per day of data requiring space for levels of archival storage. Data compression will be a key component in systems that store this data (e.g., optical disk and tape) as well as in communications systems (both between space and Earth and between scientific locations on Earth). We propose to develop algorithms that can be a basis for software and hardware systems that compress a wide variety of scientific data with different criteria for fidelity/bandwidth tradeoffs. The algorithmic approaches we consider are specially targeted for parallel computation where data rates of over 1 billion bits per second are achievable with current technology.

Storer, James A.↗

Excursion-Set-Mediated Genetic Algorithm

Excursion-set-mediated genetic algorithm (ESMGA) is embodiment of method of searching for and optimizing computerized mathematical models. Incorporates powerful search and optimization techniques based on concepts analogous to natural selection and laws of genetics. In comparison with other genetic algorithms, this one achieves stronger condition for implicit parallelism. Includes three stages of operations in each cycle, analogous to biological generation.

Noever, David↗

Entry Guidance for the Reusable Launch Vehicle

The X-33 Advanced Technology Demonstrator is a half-scale prototype developed to test the key technologies needed for a full-scale single-stage reusable launch vehicle (RLV). The X-33 is a suborbital vehicle that will be launched vertically, and land horizontally. The goals of this research were to develop an alternate entry guidance scheme for the X-33 in parallel to the actual X-33 entry guidance algorithms, provide comparative and complementary study, and identify potential new ways to improve entry guidance performance. Toward these goals, the nominal entry trajectory is defined by a piecewise linear drag-acceleration-versus-energy profile, which is in turn obtained by the solution of a semi-analytical parameter optimization problem. The closed-loop guidance is accomplished by tracking the nominal drag profile with primarily bank-angle modulation on-board. The bank-angle is commanded by a single full-envelope nonlinear trajectory control law. Near the end of the entry flight, the guidance logic is switched to heading control in order to meet strict conditions at the terminal area energy management interface. Two methods, one on ground-track control and the other on heading control, were proposed and examined for this phase of entry guidance where lateral control is emphasized. Trajectory dispersion studies were performed to evaluate the effectiveness of the entry guidance algorithms against a number of uncertainties including those in propulsion system, atmospheric properties, winds, aerodynamics, and propellant loading. Finally, a new trajectory-regulation method is introduced at the end as a promising precision entry guidance method. The guidance principle is very different and preliminary application in X-33 entry guidance simulation showed high precision that is difficult to achieve by existing methods.

Lu, Ping↗

Analysis and Optimization of Parallel Software Pipeline Performance

Pipelining is a common strategy for extracting parallelism from a collection of independent computational tasks, each of which is spread among a number of processors and has an implied data dependence. When implemented on MIMD parallel computers with finite process interrupt times, pipeline algorithms suffer from slowdown--in addition to the expected pipeline fill time--due to a wave-like propagation of delays. This phenomenon, which has been observed experimentally using the performance monitoring system AIMS, is investigated analytically, and an optimal correction is derived to eliminate the wave. Efficiency increase through the correction is verified experimentally.

VanderWijngaart, Rob F.↗

The Effect of Interrupts on Software Pipeline Execution on Message-Passing Architectures

Pipelining is a common strategy for extracting parallelism from a collection of independent computational tasks, each of which is spread among a number of processors and has an implied data dependence. When implemented on MIMD parallel computers with finite process interrupt times, pipeline algorithms suffer from slowdown--in addition to the expected pipeline fill time--due to a wave-like propagation of delays. This phenomenon, which has been observed experimentally using the performance monitoring system AIMS, is investigated analytically, and an optimal correction is derived to eliminate the wave. Efficiency increase through the correction is verified experimentally.

VanderWijngaart, Rob F.↗

Parametric Study of a YAV-8B Harrier in Ground Effect using Time-Dependent Navier-Stokes Computations

A process is described which enables the generation of 35 time-dependent viscous solutions for a YAV-8B Harrier in ground effect in one week. Overset grids are used to model the complex geometry of the Harrier aircraft and the interaction of its jets with the ground plane and low-speed ambient flow. The time required to complete this parametric study is drastically reduced through the use of process automation, modern computational platforms, and parallel computing. Moreover, a dual-time-stepping algorithm is described which improves solution robustness. Unsteady flow visualization and a frequency domain analysis are also used to identify and correlated key flow structures with the time variation of lift.

Pandya, Shishir↗

Progress Toward Generation of a Navier-Stokes Database for a Harrier in Ground Effect

The Harrier YAV-8B aircraft is capable of vertical and short-field take-off and landing (V/STOL) by directing its four exhaust nozzles toward the ground, or conventional flight by rotating its nozzles into a horizontal position. The British Royal Air Force and the United States Marine Corps have used this aircraft for more than 30 years to provide a quick reaction time for troop support, and reduce the need for long runways. The success of this powered-lift (PL) vehicle has also prompted the more recent design of the Joint Strike Fighter (JSF). However there are significant safety issues that must be addressed when operating a PL vehicle in close proximity to the ground. Hot Gas Ingestion (HGI) by the inlets can result in a rapid loss of powered lift; and high-speed jet flows along the ground plane can induce low pressures underneath the vehicle, causing a 'suck-down' effect. Under these conditions, departure from controlled flight may occur. Moreover, unsteady ground vortices and jet fountains can affect the aircraft,s controllability and its proximity to ground troops. The viscous, time-dependent flow fields of PL vehicles are difficult to accurately and efficiently predict using Computational Fluid Dynamics (CFD). A number of researchers have used the time-dependent Reynolds-averaged Navier-Stokes (RANS) equations to compute flows for single and multiple jets in a cross-flow. A few have added some geometric complexity to the problem by computing flows for jet-augmented delta wings near a ground plane. Smith et.al. computed for the first time a single RANS solution about a simplified Harrier. This geometry included a fuselage, wing, leading edge root extension (LERX), inlets, and exhaust nozzles. All of these investigations cite two practical problems with computing these flows: 1) the need for improved solution accuracy; and, 2) the need for faster solution methods. We view the need for faster solution methods as key to improving the solution accuracy and making this class of computation more routine. One can hardly refine grids, explore the use of advanced turbulence models, and generate databases when it takes weeks of dedicated computer time for a single solution. Chaderjian, Ahmad, Pandya, and Murman have focused on reducing the time-to-solution for this very difficult and complex problem through process automation and exploitation of parallel computing. They began with the Harrier geometry reported, and added a deflected wing flap and empennage for greater realism. To date more than 80 solutions have been carried out. This paper will describe this process and progress made in reducing the time required to generate a simple longitudinal force and moment database for a Harrier in ground effect. It shows a typical snap-shot from an unsteady streakline animation, where fluid particles are colored by temperature. The ground vortex and a jet-fountain vortex are highlighted. It also shows a similar streakline image, where HGI occurs due to the vehicle in close proximity to the ground. It is show the mean lift coefficient as a function of angle of attack and height. The angle of attack range was 4 deg less than or = alpha less than or = 10 deg with an increment of 1 degree, and the height range was 10 ft less than or = h less than or = 30ft with an increment of 5 feet. This 35 solution database was extended to over 2500 cases using a monotone cubic-spline interpolation procedure. The suck-down effect (reduction of lift near the ground) is highlighted in the figure. The "cushion effect," the conventional reduction of lift as the vehicle moves out of ground effect, is also indicated. All 35 RANS solutions were obtained using 952 Silicon Graphics Origin 2000 and 3000 processors in dedicated mode for one week. Typically, 112 processors were assigned to each case. Some other cases used fewer processors to utilize all available CPUS. The final paper will report on the automation of the solution process, including: grid generation, job monitoring, solution completion criteria, and post processing. Moreover, improvements in parallel efficiency for a dual time-step algorithm for the RANS equations will also be presented. Results will be discussed in detail using unsteady streakline flow visualization to correlate unsteady flow structures with dominant aerodynamic frequencies. The stability derivatives, CL, and CL, will also be presented.

Chaderjian, Neal M.↗

Large Photospheric Doppler Shift in Solar Active Region 12673: I. Field-Aligned Flows

Delta (δ) sunspots sometimes host fast photospheric flows along the central magnetic polarity inversion line (PIL). Here we study the strong Doppler shift signature in the central penumbral light bridge of solar active region NOAA 12673. Observations from the Helioseismic and Magnetic Imager (HMI) indicate highly sheared, strong magnetic fields. Large Doppler shifts up to 3.2 km s −1 appeared during the formation of the light bridge and persisted for about 16 hours. A new velocity estimator, called DAVE4VMwDV, reveals fast converging and shearing motion along the PIL from HMI vector magnetograms, and recovers the observed Doppler signal much better than an old version of the algorithm. The inferred velocity vectors are largely (anti-)parallel to the inclined magnetic fields, suggesting that the observed Doppler shift contains significant contribution from the projected, field-aligned flows. High-resolution observations from the Hinode/Spectro-Polarimeter (SP) further exhibit a clear correlation between the Doppler velocity and the cosine of the magnetic inclination, which is in agreement with HMI results and consistent with a field-aligned flow of about 9.6 km s −1 . The complex Stokes profiles suggest significant gradients of physical variables along the line of sight. We discuss the implications on the δ-spot magnetic structure and the flow-driving mechanism.

Solar active region magnetic fields↗

Parallel variable-band Choleski solvers for computational structural analysis applications on vector multiprocessor supercomputers

A Choleski method used to solve linear systems of equations that arise in large scale structural analyses is described. The method uses a novel variable-band storage scheme and is structured to exploit fast local memory caches while minimizing data access delays between main memory and vector registers. Several parallel implementations of this method are described for the CRAY-2 and CRAY Y-MP computers demonstrating the use of microtasking and autotasking directives. A portable parallel language, FORCE, is also used for two different parallel implementations, demonstrating the use of CRAY macrotasking. Results are presented comparing the matrix factorization times for three representative structural analysis problems from runs made in both dedicated and multi-user modes on both the CRAY-2 and CRAY Y-MP computers. CPU and wall clock timings are given for the various parallel methods and are compared to single processor timings of the same algorithm. Computation rates over 1 GIGAFLOP (1 billion floating point operations per second) on a four processor CRAY-2 and over 2 GIGAFLOPS on an eight processor CRAY Y-MP are demonstrated as measured by wall clock time in a dedicated environment. Reduced wall clock times for the parallel methods relative to the single processor implementation of the same Choleski algorithm are also demonstrated for runs made in multi-user mode.

Poole, E. L.↗

Antenna analysis using neural networks

Conventional computing schemes have long been used to analyze problems in electromagnetics (EM). The vast majority of EM applications require computationally intensive algorithms involving numerical integration and solutions to large systems of equations. The feasibility of using neural network computing algorithms for antenna analysis is investigated. The ultimate goal is to use a trained neural network algorithm to reduce the computational demands of existing reflector surface error compensation techniques. Neural networks are computational algorithms based on neurobiological systems. Neural nets consist of massively parallel interconnected nonlinear computational elements. They are often employed in pattern recognition and image processing problems. Recently, neural network analysis has been applied in the electromagnetics area for the design of frequency selective surfaces and beam forming networks. The backpropagation training algorithm was employed to simulate classical antenna array synthesis techniques. The Woodward-Lawson (W-L) and Dolph-Chebyshev (D-C) array pattern synthesis techniques were used to train the neural network. The inputs to the network were samples of the desired synthesis pattern. The outputs are the array element excitations required to synthesize the desired pattern. Once trained, the network is used to simulate the W-L or D-C techniques. Various sector patterns and cosecant-type patterns (27 total) generated using W-L synthesis were used to train the network. Desired pattern samples were then fed to the neural network. The outputs of the network were the simulated W-L excitations. A 20 element linear array was used. There were 41 input pattern samples with 40 output excitations (20 real parts, 20 imaginary). A comparison between the simulated and actual W-L techniques is shown for a triangular-shaped pattern. Dolph-Chebyshev is a different class of synthesis technique in that D-C is used for side lobe control as opposed to pattern shaping. The interesting thing about D-C synthesis is that the side lobes have the same amplitude. Five-element arrays were used. Again, 41 pattern samples were used for the input. Nine actual D-C patterns ranging from -10 dB to -30 dB side lobe levels were used to train the network. A comparison between simulated and actual D-C techniques for a pattern with -22 dB side lobe level is shown. The goal for this research was to evaluate the performance of neural network computing with antennas. Future applications will employ the backpropagation training algorithm to drastically reduce the computational complexity involved in performing EM compensation for surface errors in large space reflector antennas.

Smith, William T.↗

Punctured Parallel and Serial Concatenated Convolutional Codes for BPSK/QPSK Channels

As available bandwidth for communication applications becomes scarce, bandwidth-efficient modulation and coding schemes become ever important. Since their discovery in 1993, turbo codes (parallel concatenated convolutional codes) have been the center of the attention in the coding community because of their bit error rate performance near the Shannon limit. Serial concatenated convolutional codes have also been shown to be as powerful as turbo codes. In this dissertation, we introduce algorithms for designing bandwidth-efficient rate r = k/(k + 1),k = 2, 3,..., 16, parallel and rate 3/4, 7/8, and 15/16 serial concatenated convolutional codes via puncturing for BPSK/QPSK (Binary Phase Shift Keying/Quadrature Phase Shift Keying) channels. Both parallel and serial concatenated convolutional codes have initially, steep bit error rate versus signal-to-noise ratio slope (called the -"cliff region"). However, this steep slope changes to a moderate slope with increasing signal-to-noise ratio, where the slope is characterized by the weight spectrum of the code. The region after the cliff region is called the "error rate floor" which dominates the behavior of these codes in moderate to high signal-to-noise ratios. Our goal is to design high rate parallel and serial concatenated convolutional codes while minimizing the error rate floor effect. The design algorithm includes an interleaver enhancement procedure and finds the polynomial sets (only for parallel concatenated convolutional codes) and the puncturing schemes that achieve the lowest bit error rate performance around the floor for the code rates of interest.

Acikel, Omer Fatih↗

Feasibility of using the Massively Parallel Processor for large eddy simulations and other Computational Fluid Dynamics applications

The results of an investigation into the feasibility of using the MPP for direct and large eddy simulations of the Navier-Stokes equations is presented. A major part of this study was devoted to the implementation of two of the standard numerical algorithms for CFD. These implementations were not run on the Massively Parallel Processor (MPP) since the machine delivered to NASA Goddard does not have sufficient capacity. Instead, a detailed implementation plan was designed and from these were derived estimates of the time and space requirements of the algorithms on a suitably configured MPP. In addition, other issues related to the practical implementation of these algorithms on an MPP-like architecture were considered; namely, adaptive grid generation, zonal boundary conditions, the table lookup problem, and the software interface. Performance estimates show that the architectural components of the MPP, the Staging Memory and the Array Unit, appear to be well suited to the numerical algorithms of CFD. This combined with the prospect of building a faster and larger MMP-like machine holds the promise of achieving sustained gigaflop rates that are required for the numerical simulations in CFD.

Bruno, John↗

Progress in the Simulation of Steady and Time-Dependent Flows with 3D Parallel Unstructured Cartesian Methods

The proposed paper will present recent extensions in the development of an efficient Euler solver for adaptively-refined Cartesian meshes with embedded boundaries. The paper will focus on extensions of the basic method to include solution adaptation, time-dependent flow simulation, and arbitrary rigid domain motion. The parallel multilevel method makes use of on-the-fly parallel domain decomposition to achieve extremely good scalability on large numbers of processors, and is coupled with an automatic coarse mesh generation algorithm for efficient processing by a multigrid smoother. Numerical results are presented demonstrating parallel speed-ups of up to 435 on 512 processors. Solution-based adaptation may be keyed off truncation error estimates using tau-extrapolation or a variety of feature detection based refinement parameters. The multigrid method is extended to for time-dependent flows through the use of a dual-time approach. The extension to rigid domain motion uses an Arbitrary Lagrangian-Eulerlarian (ALE) formulation, and results will be presented for a variety of two- and three-dimensional example problems with both simple and complex geometry.

Aftosmis, M. J.↗

The question of the possibility of using Associative Computer Devices (ACD) for parallel adaptive discretization of multichannel telemetry information

The method of parallel adaptive discretization of data is considered the most promising and allows the effective compression algorithms to be used for high information-capacity radio telemetry systems. An associative computer device (ACD), i.e., parallel computers based on associative memory units (AMU), are recommended for realization of this method. A detailed discussion of the problems of application of AMU is followed by description of a particular ACD and its recommended use.

Kantor, A. V.↗