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At least 73 records · Page 4

Large-Scale Numerical Simulations of Human Motion

This paper examines the feasibility of using massively-parallel and vector-processing supercomputers to solve large-scale optimal control problems for human movement. Specifically, we compare the computational expense of determining the optimal controls for the single support phase of walking using a conventional serial machine (a Silicon Graphics Personal Iris 4D25 workstation), a MIMD parallel machine (an Intel iPSC/860 comprising 128 processors), and a parallel-vector-processing machine (a Cray Y-MP 8/864). With the human body modeled as a 14 degree-of-freedom linkage actuated by 46 musculotendinous units, computation of the optimal controls for walking could take up to 3 months of CPU time on the Iris. Both the Cray Y-MP and the Intel iPSC/860 are able to reduce this time to practical levels. The optimal control solution for walking can be found with about 77 hours of CPU time on the Cray, and with about 88 hours of CPU time on the Intel. Although the overall speeds of the Cray and the Intel were found to be similar, the unique capabilities of each machine are best suited to different parts of the optimal control algorithm used. The Intel performed best in the calculation of the derivatives of the performance criterion and the constraints. In contrast, the Cray performed best during parameter optimization of the controls. These results suggest that the ideal computer architecture for solving very large-scale optimal control problems is a hybrid system in which a vector-processing machine is integrated into the communication network of a MIMD parallel machine.

Anderson, Frank C.↗

Application of high-performance computing to numerical simulation of human movement

We have examined the feasibility of using massively-parallel and vector-processing supercomputers to solve large-scale optimization problems for human movement. Specifically, we compared the computational expense of determining the optimal controls for the single support phase of gait using a conventional serial machine (SGI Iris 4D25), a MIMD parallel machine (Intel iPSC/860), and a parallel-vector-processing machine (Cray Y-MP 8/864). With the human body modeled as a 14 degree-of-freedom linkage actuated by 46 musculotendinous units, computation of the optimal controls for gait could take up to 3 months of CPU time on the Iris. Both the Cray and the Intel are able to reduce this time to practical levels. The optimal solution for gait can be found with about 77 hours of CPU on the Cray and with about 88 hours of CPU on the Intel. Although the overall speeds of the Cray and the Intel were found to be similar, the unique capabilities of each machine are better suited to different portions of the computational algorithm used. The Intel was best suited to computing the derivatives of the performance criterion and the constraints whereas the Cray was best suited to parameter optimization of the controls. These results suggest that the ideal computer architecture for solving very large-scale optimal control problems is a hybrid system in which a vector-processing machine is integrated into the communication network of a MIMD parallel machine.

NASA Discipline Musculoskeletal↗

Real time animation of space plasma phenomena

In pursuit of real time animation of computer simulated space plasma phenomena, the code was rewritten for the Massively Parallel Processor (MPP). The program creates a dynamic representation of the global bowshock which is based on actual spacecraft data and designed for three dimensional graphic output. This output consists of time slice sequences which make up the frames of the animation. With the MPP, 16384, 512 or 4 frames can be calculated simultaneously depending upon which characteristic is being computed. The run time was greatly reduced which promotes the rapid sequence of images and makes real time animation a foreseeable goal. The addition of more complex phenomenology in the constructed computer images is now possible and work proceeds to generate these images.

Jordan, K. F.↗

Neural nets on the MPP

The Massively Parallel Processor (MPP) is an ideal machine for computer experiments with simulated neural nets as well as more general cellular automata. Experiments using the MPP with a formal model neural network are described. The results on problem mapping and computational efficiency apply equally well to the neural nets of Hopfield, Hinton et al., and Geman and Geman.

Hastings, Harold M.↗

Validation of a Pressure-Based Combustion Simulation Tool Using a Single Element Injector Test Problem

The traditional design and analysis practice for advanced propulsion systems, particularly chemical rocket engines, relies heavily on expensive full-scale prototype development and testing. Over the past decade, use of high-fidelity analysis and design tools such as CFD early in the product development cycle has been identified as one way to alleviate testing costs and to develop these devices better, faster and cheaper. Increased emphasis is being placed on developing and applying CFD models to simulate the flow field environments and performance of advanced propulsion systems. This necessitates the development of next generation computational tools which can be used effectively and reliably in a design environment by non-CFD specialists. A computational tool, called Loci-STREAM is being developed for this purpose. It is a pressure-based, Reynolds-averaged Navier-Stokes (RANS) solver for generalized unstructured grids, which is designed to handle all-speed flows (incompressible to hypersonic) and is particularly suitable for solving multi-species flow in fixed-frame combustion devices. Loci-STREAM integrates proven numerical methods for generalized grids and state-of-the-art physical models in a novel rule-based programming framework called Loci which allows: (a) seamless integration of multidisciplinary physics in a unified manner, and (b) automatic handling of massively parallel computing. The objective of the ongoing work is to develop a robust simulation capability for combustion problems in rocket engines. As an initial step towards validating this capability, a model problem is investigated in the present study which involves a gaseous oxygen/gaseous hydrogen (GO2/GH2) shear coaxial single element injector, for which experimental data are available. The sensitivity of the computed solutions to grid density, grid distribution, different turbulence models, and different near-wall treatments is investigated. A refined grid, which is clustered in the vicinity of the solid walls as well as the flame, is used to obtain a steady state solution which may be considered as the best solution attainable with the steady-state RANS methodology. From a design point of view, quick turnaround times are desirable; with this in mind, coarser grids are also employed and the resulting solutions are evaluated with respect to the fine grid solution.

Thakur, Siddarth↗

The NASA Computational Aerosciences Program - Toward teraFLOPS computing

The Computational Aerosciences (CAS) project of the High Performance Computing and Communications program is presented and discussed. The main emphasis of this presentation is on the applications portion of the CAS program, which includes a High-Speed Civil Transport element, a High Performance Aircraft element, a NASP-Derived Vehicle element, and an Aerobraking element. Two major thrusts of this program are the enhancement of simulation capabilities using multidiscipline formulations and the improvement in processing efficiency via massive parallel computer hardware. Current activities in these two areas at Ames, Langley and Lewis, are presented and discussed.

Holst, Terry L.↗

Large Scale Finite Element Modeling Using Scalable Parallel Processing

An iterative solver for use with finite element codes was developed for the Cray T3D massively parallel processor at the Jet Propulsion Laboratory. Finite element modeling is useful for simulating scattered or radiated electromagnetic fields from complex three-dimensional objects with geometry variations smaller than an electrical wavelength.

finite element modeling parallel processing iterat↗

A collision-selection rule for a particle simulation method suited to vector computers

A theory is developed for a selection rule governing collisions in a particle simulation of rarefied gas-dynamic flows. The selection rule leads to an algorithmic form highly compatible with fine grain parallel decomposition, allowing for efficient utilization of supercomputers having vector or massively parallel single instruction multiple data architectures. A comparison of shock-wave profiles obtained using both the selection rule and Bird's direct simulation Monte Carlo (DSMC) method show excellent agreement. The equation on which the selection rule is based is shown to be directly related to the time-counter procedure in the DSMC method. The results of several example simulations of representative rarefied flows are presented, for which the number of particles used ranged from 10 to the 6th to 10 to the 7th demonstrating the greatly improved computational efficiency of the method.

Baganoff, D.↗

How to cluster in parallel with neural networks

Partitioning a set of N patterns in a d-dimensional metric space into K clusters - in a way that those in a given cluster are more similar to each other than the rest - is a problem of interest in astrophysics, image analysis and other fields. As there are approximately K(N)/K (factorial) possible ways of partitioning the patterns among K clusters, finding the best solution is beyond exhaustive search when N is large. Researchers show that this problem can be formulated as an optimization problem for which very good, but not necessarily optimal solutions can be found by using a neural network. To do this the network must start from many randomly selected initial states. The network is simulated on the MPP (a 128 x 128 SIMD array machine), where researchers use the massive parallelism not only in solving the differential equations that govern the evolution of the network, but also by starting the network from many initial states at once, thus obtaining many solutions in one run. Researchers obtain speedups of two to three orders of magnitude over serial implementations and the promise through Analog VLSI implementations of speedups comensurate with human perceptual abilities.

Kamgar-Parsi, Behzad↗

Massively Parallel Processor

The feasibility of using the Massively Parallel Processor (MPP) and possible future machines with parallel architecture for weather prediction and climate simulation was studied. A shallow water model and a two-level primitive equations model were implemented.

Suarez, M. J.↗

Parallel computations and control of adaptive structures

The equations of motion for structures with adaptive elements for vibration control are presented for parallel computations to be used as a software package for real-time control of flexible space structures. A brief introduction of the state-of-the-art parallel computational capability is also presented. Time marching strategies are developed for an effective use of massive parallel mapping, partitioning, and the necessary arithmetic operations. An example is offered for the simulation of control-structure interaction on a parallel computer and the impact of the approach presented for applications in other disciplines than aerospace industry is assessed.

Park, K. C.↗

Combustor Simulation

The goal was to perform 3D simulation of GE90 combustor, as part of full turbofan engine simulation. Requirements of high fidelity as well as fast turn-around time require massively parallel code. National Combustion Code (NCC) was chosen for this task as supports up to 999 processors and includes state-of-the-art combustion models. Also required is ability to take inlet conditions from compressor code and give exit conditions to turbine code.

Norris, Andrew↗

A transient FETI methodology for large-scale parallel implicit computations in structural mechanics

Explicit codes are often used to simulate the nonlinear dynamics of large-scale structural systems, even for low frequency response, because the storage and CPU requirements entailed by the repeated factorizations traditionally found in implicit codes rapidly overwhelm the available computing resources. With the advent of parallel processing, this trend is accelerating because explicit schemes are also easier to parallelize than implicit ones. However, the time step restriction imposed by the Courant stability condition on all explicit schemes cannot yet -- and perhaps will never -- be offset by the speed of parallel hardware. Therefore, it is essential to develop efficient and robust alternatives to direct methods that are also amenable to massively parallel processing because implicit codes using unconditionally stable time-integration algorithms are computationally more efficient when simulating low-frequency dynamics. Here we present a domain decomposition method for implicit schemes that requires significantly less storage than factorization algorithms, that is several times faster than other popular direct and iterative methods, that can be easily implemented on both shared and local memory parallel processors, and that is both computationally and communication-wise efficient. The proposed transient domain decomposition method is an extension of the method of Finite Element Tearing and Interconnecting (FETI) developed by Farhat and Roux for the solution of static problems. Serial and parallel performance results on the CRAY Y-MP/8 and the iPSC-860/128 systems are reported and analyzed for realistic structural dynamics problems. These results establish the superiority of the FETI method over both the serial/parallel conjugate gradient algorithm with diagonal scaling and the serial/parallel direct method, and contrast the computational power of the iPSC-860/128 parallel processor with that of the CRAY Y-MP/8 system.

Farhat, Charbel↗

Design of a massively parallel computer using bit serial processing elements

A 1-bit serial processor designed for a parallel computer architecture is described. This processor is used to develop a massively parallel computational engine, with a single instruction-multiple data (SIMD) architecture. The computer is simulated and tested to verify its operation and to measure its performance for further development.

Aburdene, Maurice F.↗

Modeling of High Speed Reacting Flows: Established Practices and Future Challenges

Computational fluid dynamics (CFD) has proven to be an invaluable tool for the design and analysis of high- speed propulsion devices. Massively parallel computing, together with the maturation of robust CFD codes, has made it possible to perform simulations of complete engine flowpaths. Steady-state Reynolds-Averaged Navier-Stokes simulations are now routinely used in the scramjet engine development cycle to determine optimal fuel injector arrangements, investigate trends noted during testing, and extract various measures of engine efficiency. Unfortunately, the turbulence and combustion models used in these codes have not changed significantly over the past decade. Hence, the CFD practitioner must often rely heavily on existing measurements (at similar flow conditions) to calibrate model coefficients on a case- by-case basis. This paper provides an overview of the modeled equations typically employed by commercial- quality CFD codes for high-speed combustion applications. Careful attention is given to the approximations employed for each of the unclosed terms in the averaged equation set. The salient features (and shortcomings) of common models used to close these terms are covered in detail, and several academic efforts aimed at addressing these shortcomings are discussed.

Baurle, R. A.↗

A transient FETI methodology for large-scale parallel implicit computations in structural mechanics, part 2

Explicit codes are often used to simulate the nonlinear dynamics of large-scale structural systems, even for low frequency response, because the storage and CPU requirements entailed by the repeated factorizations traditionally found in implicit codes rapidly overwhelm the available computing resources. With the advent of parallel processing, this trend is accelerating because explicit schemes are also easier to parallellize than implicit ones. However, the time step restriction imposed by the Courant stability condition on all explicit schemes cannot yet and perhaps will never be offset by the speed of parallel hardware. Therefore, it is essential to develop efficient and robust alternatives to direct methods that are also amenable to massively parallel processing because implicit codes using unconditionally stable time-integration algorithms are computationally more efficient than explicit codes when simulating low-frequency dynamics. Here we present a domain decomposition method for implicit schemes that requires significantly less storage than factorization algorithms, that is several times faster than other popular direct and iterative methods, that can be easily implemented on both shared and local memory parallel processors, and that is both computationally and communication-wise efficient. The proposed transient domain decomposition method is an extension of the method of Finite Element Tearing and Interconnecting (FETI) developed by Farhat and Roux for the solution of static problems. Serial and parallel performance results on the CRAY Y-MP/8 and the iPSC-860/128 systems are reported and analyzed for realistic structural dynamics problems. These results establish the superiority of the FETI method over both the serial/parallel conjugate gradient algorithm with diagonal scaling and the serial/parallel direct method, and contrast the computational power of the iPSC-860/128 parallel processor with that of the CRAY Y-MP/8 system.

Farhat, Charbel↗

Simulation of charged particle transport on the MPP

Computations of cosmic ray transport based upon finite difference methods are afflicted by instabilities, inaccuracies, and artifacts. To avoid these problems, a Monte Carlo formulation was developed which is closely related not only to the finite difference formulation, but also to the underlying physics of transport phenomena. Implementations of this approach are currently running on the Massively Parallel Processor at Goddard, whose enormous computing power overwhelms the poor statistical accuracy that usually limits the use of stochastic methods. In a Monte Carlo simulation of rectilinear transport, the coherent and diffusive effects that appeared are in good quantitative agreement with both finite difference and analytical calculations.

Earl, James A.↗