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At least 1,351 records · Page 75

All sources NASA NTRS DOE OSTI

DOE OSTI2022

Integrating a ponderomotive guiding center algorithm into a quasi-static particle-in-cell code based on azimuthal mode decomposition

High fidelity modeling of plasma based acceleration (PBA) requires the use of three dimensional, fully nonlinear, and kinetic descriptions based on the particle-in-cell (PIC) method. In PBA an intense particle beam or laser (driver) propagates through a tenuous plasma whereby it excites a plasma wave wake. Three-dimensional PIC algorithms based on the quasi-static approximation (QSA) have been successfully applied to efficiently model the interaction between relativistic charged particle beams and plasma. In a QSA PIC algorithm, the plasma response to a charged particle beam or laser driver is calculated based on forces from the driver and self-consistent forces from the QSA form of Maxwell's equations. These fields are then used to advance the charged particle beam or laser forward by a large time step. Since the time step is not limited by the regular Courant-Friedrichs-Lewy (CFL) condition that constrains a standard 3D fully electromagnetic PIC code, a 3D QSA PIC code can achieve orders of magnitude speedup in performance. Recently, a new hybrid QSA PIC algorithm that combines another speedup technique known as an azimuthal Fourier decomposition has been proposed and implemented. This hybrid algorithm decomposes the electromagnetic fields, charge and current density into azimuthal harmonics and only the Fourier coefficients need to be updated, which can reduce the algorithmic complexity of a 3D code to that of a 2D code. Modeling the laser-plasma interaction in a full 3D electromagnetic PIC algorithm is very computationally expensive due the enormous disparity of physical scales to be resolved. In the QSA the laser is modeled using the ponderomotive guiding center (PGC) approach. We describe how to implement a PGC algorithm compatible for the QSA PIC algorithms based on the azimuthal mode expansion. Here this algorithm permits time steps orders of magnitude larger than the cell size and it can be asynchronously parallelized. Details on how this is implemented into the QSA PIC code that utilizes an azimuthal mode expansion, QPAD, are also described. Benchmarks and comparisons between a fully 3D explicit PIC code (OSIRIS), as well as a few examples related to laser wakefield acceleration, are presented.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1987

Performance studies of the multigrid algorithms implemented on hypercube multiprocessor systems

In this paper, we analyze and compare the performance on a hypercube multiprocessor of some of the major multigrid techniques used in practice. The model problem considered here is that of solving the 2-D incompressible Navier-Stokes equations representing the flow between two parallel plates. Results obtained by implementing the different multigrid schemes on an iPSC are presented. Effects on the overall performance of various parameters of the algorithms, of the partitioning strategies employed, and of some of the characteristics of the underlying architecture are discussed.

Naik, Vijay K.↗

DOE OSTI2023

LCA

The Locally Competitive Algorithm (LCA) is a dynamical sparse solver that uses only local computations, allowing for massively parallel implementations on compatible neuromorphic architectures such as Intel's Loihi research chip. In this invention, we show how unsupervised dictionary learning with spiking LCA can be implemented on GPUs and Intel's Loihi research chip.

Parpart, Gavin↗

DOE OSTI2026

JAXtronomy: A JAX port of lenstronomy

Gravitational lensing is a phenomenon where light bends around massive objects, resulting in distorted images seen by an observer. Studying gravitationally lensed systems provides insights into cosmology and astrophysics, including constraints of the expansion rate of the Universe and the distribution of dark matter. Thus, we introduce JAXtronomy, a re-implementation of the gravitational lensing software package lenstronomy (Birrer, 2021; Birrer & Amara, 2018) using JAX (Bradbury et al., 2018). JAX is a Python library that uses an accelerated linear algebra (XLA) compiler to improve the performance of computing software. Our core design principle of JAXtronomy is to maintain an identical API to that of lenstronomy. The main JAX features utilized in JAXtronomy are just-in-time compilation, which can lead to significant reductions in execution time, and automatic differentiation, which allows for the implementation of gradient-based algorithms that were previously impossible. Additionally, JAX allows code to be run on GPUs or parallelized across CPU cores, further boosting the performance of JAXtronomy.

astronomy↗

DOE OSTI2023

Quantum-inspired tempering for ground state approximation using artificial neural networks

A large body of work has demonstrated that parameterized artificial neural networks (ANNs) can efficiently describe ground states of numerous interesting quantum many-body Hamiltonians. However, the standard variational algorithms used to update or train the ANN parameters can get trapped in local minima, especially for frustrated systems and even if the representation is sufficiently expressive. We propose a parallel tempering method that facilitates escape from such local minima. This methods involves training multiple ANNs independently, with each simulation governed by a Hamiltonian with a different "driver" strength, in analogy to quantum parallel tempering, and it incorporates an update step into the training that allows for the exchange of neighboring ANN configurations. We study instances from two classes of Hamiltonians to demonstrate the utility of our approach using Restricted Boltzmann Machines as our parameterized ANN. The first instance is based on a permutation-invariant Hamiltonian whose landscape stymies the standard training algorithm by drawing it increasingly to a false local minimum. The second instance is four hydrogen atoms arranged in a rectangle, which is an instance of the second quantized electronic structure Hamiltonian discretized using Gaussian basis functions. We study this problem in a minimal basis set, which exhibits false minima that can trap the standard variational algorithm despite the problem’s small size. We show that augmenting the training with quantum parallel tempering becomes useful to finding good approximations to the ground states of these problem instances.

Albash, Tameem↗

NASA NTRS1986

Optimal design of structures with multiple design variables per group and multiple loading conditions on the personal computer

A finite element based programming system for minimum weight design of a truss-type structure subjected to displacement, stress, and lower and upper bounds on design variables is presented. The programming system consists of a number of independent processors, each performing a specific task. These processors, however, are interfaced through a well-organized data base, thus making the tasks of modifying, updating, or expanding the programming system much easier in a friendly environment provided by many inexpensive personal computers. The proposed software can be viewed as an important step in achieving a 'dummy' finite element for optimization. The programming system has been implemented on both large and small computers (such as VAX, CYBER, IBM-PC, and APPLE) although the focus is on the latter. Examples are presented to demonstrate the capabilities of the code. The present programming system can be used stand-alone or as part of the multilevel decomposition procedure to obtain optimum design for very large scale structural systems. Furthermore, other related research areas such as developing optimization algorithms (or in the larger level: a structural synthesis program) for future trends in using parallel computers may also benefit from this study.

Nguyen, D. T.↗

NASA NTRS1986

Radarclinometry

A general theory based on the implicit mathematical determinacy, and a corresponding algorithm, are developed to derive topographic maps from radar images as photometric arrays. Starting from a control profile, the theory produces topography by an area integration of radar brightness, and the control profile is formed under the assumption that the terrain properties are locally cylindrical. The calibration curve for pixel brightness versus incidence-angle is also produced. In the operational algorithm, topography is produced as a set of independent line integrations down each of the parallel range lines of the image using the theory for control-profile formation. An adaptive technique was employed to process SEASAT images of sand dunes, and the present method is demonstrated with a Motorola image of Crazy Jug Point in the Grand Canyon.

Wildey, Robert L.↗

NASA NTRS1988

Single-Mode Projection Filters for Modal Parameter Identification for Flexible Structures

Single-mode projection filters are developed for eigensystem parameter identification from both analytical results and test data. Explicit formulations of these projection filters are derived using the orthogonal matrices of the controllability and observability matrices in the general sense. A global minimum optimization algorithm is applied to update the filter parameters by using the interval analysis method. The updated modal parameters represent the characteristics of the test data. For illustration of this new approach, a numerical simulation for the MAST beam structure is shown by using a one-dimensional global optimization algorithm to identify modal frequencies and damping. Another numerical simulation of a ten-mode structure is also presented by using a two-dimensional global optimization algorithm to illustrate the feasibility of the new method. The projection filters are practical for parallel processing implementation.

Huang, Jen-Kuang↗

NASA NTRS1988

Correlation filters for orientation estimation

An important task in many vision applications is that of rapidly estimating the orientation of an object with respect to some frame of reference. Because of their speed and parallel processing capabilities, optical correlators should prove valuable in this application. This paper considers two algorithms for object orientation estimation based on optical correlations and presents some initial simulation results.

Kumar, B. V. K. Vijaya↗

NASA NTRS1990

Analog Delta-Back-Propagation Neural-Network Circuitry

Changes in synapse weights due to circuit drifts suppressed. Proposed fully parallel analog version of electronic neural-network processor based on delta-back-propagation algorithm. Processor able to "learn" when provided with suitable combinations of inputs and enforced outputs. Includes programmable resistive memory elements (corresponding to synapses), conductances (synapse weights) adjusted during learning. Buffer amplifiers, summing circuits, and sample-and-hold circuits arranged in layers of electronic neurons in accordance with delta-back-propagation algorithm.

Eberhart, Silvio↗

NASA NTRS1990

A parallel particle-in-cell model for the massively parallel processor

The availability of the nearest-neighbor communication-incorporating Massively Parallel Processor has prompted the development of a two-dimensional, particle-in-cell algorithm which loads particles in a cell randomly onto a row of processors, filling only half of them with particles. Due to the simplification of communications among processors achieved in a row by the vacant processors and the random-particle sequence, the algorithm efficiently sorts particles and performs gather/scatter procedures for collecting charge density according to their cells. The algorithm calculates electric fields at the cells by FFT.

Lin, C. S.↗

NASA NTRS1989

Computational fluid dynamics on a massively parallel computer

A finite difference code was implemented for the compressible Navier-Stokes equations on the Connection Machine, a massively parallel computer. The code is based on the ARC2D/ARC3D program and uses the implicit factored algorithm of Beam and Warming. The codes uses odd-even elimination to solve linear systems. Timings and computation rates are given for the code, and a comparison is made with a Cray XMP.

Jespersen, Dennis C.↗

NASA NTRS1991

Modeling methods for the design and evaluation of fault-tolerant systems

The authors describe an approach for using directed graph simulation models, behavioral simulation models, and semi-Markov analytic models to implement early- to mid-design analysis activities specified by the SDIO BM/C3 Processor and Algorithm Working Group. The use of the models was demonstrated for a mission scenario requiring parallel, reliable computations with a maximum probability of system failure between 10-4 and 10-2 over a 5-year-preengagement phase and between 10-7 and 10-5 over a half-hour engagement phase.

Scheper, Charlotte O.↗

NASA NTRS1992

Repetitive control in the presence of multiple periodic disturbances

In this paper, the authors introduce several methods for implementing repetitive control of systems subjected to noninteger multiple periodic disturbances. One method uses a single repetitive controller to learn at the common period of the disturbances. The second employs multiple p-integrator based repetitive controllers operating in parallel. The third method introduces the concept of sequenced repetitive controllers. Cross-talk elimination algorithms are proposed to improve the repetitive control performance in the presence of transients. A novel averaging algorithm is introduced for on-line and off-line control strategies.

Solcz, Edward J.↗

NASA NTRS1998

Time-Critical Volume Rendering

For the past twelve months, we have conducted and completed a joint research entitled "Time- Critical Volume Rendering" with NASA Ames. As expected, High performance volume rendering algorithms have been developed by exploring some new faster rendering techniques, including object presence acceleration, parallel processing, and hierarchical level-of-detail representation. Using our new techniques, initial experiments have achieved real-time rendering rates of more than 10 frames per second of various 3D data sets with highest resolution. A couple of joint papers and technique reports as well as an interactive real-time demo have been compiled as the result of this project.

Kaufman, Arie↗

NASA NTRS2003

Performance of Goddard Earth Observing System GCM Column Radiation Models under Heterogeneous Cloud Conditions

We test the performance of the shortwave (SW) and longwave (LW) Column Radiation Models (CORAMs) of Chou and collaborators with heterogeneous cloud fields from a global single-day dataset produced by NCAR's Community Atmospheric Model with a 2-D CRM installed in each gridbox. The original SW version of the CORAM performs quite well compared to reference Independent Column Approximation (ICA) calculations for boundary fluxes, largely due to the success of a combined overlap and cloud scaling parameterization scheme. The absolute magnitude of errors relative to ICA are even smaller for the LW CORAM which applies similar overlap. The vertical distribution of heating and cooling within the atmosphere is also simulated quite well with daily-averaged zonal errors always below 0.3 K/d for SW heating rates and 0.6 K/d for LW cooling rates. The SW CORAM's performance improves by introducing a scheme that accounts for cloud inhomogeneity. These results suggest that previous studies demonstrating the inaccuracy of plane-parallel models may have unfairly focused on worst scenario cases, and that current radiative transfer algorithms of General Circulation Models (GCMs) may be more capable than previously thought in estimating realistic spatial and temporal averages of radiative fluxes, as long as they are provided with correct mean cloud profiles. However, even if the errors of the particular CORAMs are small, they seem to be systematic, and the impact of the biases can be fully assessed only with GCM climate simulations.

Oreopoulos, L.↗

NASA NTRS2003

Multifunction Sensor Algorithm Development

A multifunction sensor has been developed in the Sensors and Electronics Technology Branch. It is capable of measuring heat flux, surface temperature, and, in principle, strain magnitude & direction, while compensating for the apparent strain due to changes in operating temperature. In order to achieve this strain measuring capability, Mr. Zeller will work on improving the signal processing algorithm to include several special cases, such as when the principal strain axis lies either parallel to or perpendicular to one of the arms of the sensor. In addition, he will implement a GUI to make the sensor more user friendly.

Zeller, Donald F.↗

NASA NTRS2001

Algorithms and Application of Sparse Matrix Assembly and Equation Solvers for Aeroacoustics

An algorithm for symmetric sparse equation solutions on an unstructured grid is described. Efficient, sequential sparse algorithms for degree-of-freedom reordering, supernodes, symbolic/numerical factorization, and forward backward solution phases are reviewed. Three sparse algorithms for the generation and assembly of symmetric systems of matrix equations are presented. The accuracy and numerical performance of the sequential version of the sparse algorithms are evaluated over the frequency range of interest in a three-dimensional aeroacoustics application. Results show that the solver solutions are accurate using a discretization of 12 points per wavelength. Results also show that the first assembly algorithm is impractical for high-frequency noise calculations. The second and third assembly algorithms have nearly equal performance at low values of source frequencies, but at higher values of source frequencies the third algorithm saves CPU time and RAM. The CPU time and the RAM required by the second and third assembly algorithms are two orders of magnitude smaller than that required by the sparse equation solver. A sequential version of these sparse algorithms can, therefore, be conveniently incorporated into a substructuring for domain decomposition formulation to achieve parallel computation, where different substructures are handles by different parallel processors.

Watson, W. R.↗