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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Towards reverse mode automatic differentiation of Kokkos-based codes

Derivative computation is a key component of optimization, sensitivity analysis, uncertainty quantification, and the solving of nonlinear problems. Automatic differentiation (AD) is a powerful technique for evaluating such derivatives, and in recent years, has been integrated into programming environments such as Jax, PyTorch, and TensorFlow to support derivative computations needed for training of machine learning models, facilitating wide-spread use of these technologies. The C++ language has become the de facto standard for scientific computing due to numerous factors, yet language complexity has made the wide-spread adoption of AD technologies for C++ difficult, hampering the incorporation of powerful differentiable programming approaches into C++ scientific simulations. This is exacerbated by the increasing emergence of architectures, such as GPUs, with limited memory capabilities and requiring massive thread-level concurrency. C++ AD tools must effectively use these environments to bring novel scientific simulations to next-generation DOE experimental and observational facilities. In this project, we investigated source transformation-based automatic differentiation using LLVM compiler infrastructure to automatically generate portable and efficient gradient computations of Kokkos-based code. We have demonstrated that our proposed strategy is feasible by investigating the usage of a prototype LLVM-based source transformation tool to generate gradients of simple functions made of sequences of simple Kokkos parallel regions. Speedups of up to 500x compared to Sacado were observed on NVIDIA V100 GPU.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1973

A technique for interpretation of multispectral remote sensor data

The author has identified the following significant results. The U.S. Army Engineer Waterways Experiment Station is engaged in a study to detect from ERTS-1 satellite data alterations to the absorption and scattering properties caused by movement of suspended particles and solutes in selected areas of the Chesapeake Bay and to correlate the data to determine the feasibility of delineating flow patterns, flushing action of the estuary, and sediment and pollutant dispersion. As a part of this study, ADP techniques have been developed that permit automatic interpretation of data from any multispectral remote sensor with computer systems which have limited memory capacity and computing speed. The multispectral remote sensor is considered as a reflectance spectrophotometer. The data which define the spectral reflectance characteristics of a scene are scanned pixel by pixel. Each pixel whose spectral reflectance matches a reference spectrum is identified, and the results are shown in a map that identifies the locations where spectrum matches were detected and spectrum that was matched. The interpretation technique is described and an example of interpreted data from ERTS-1 is presented.

Williamson, A. N.↗
NASA NTRS1973

A model of the human in a cognitive prediction task.

The human decision maker's behavior when predicting future states of discrete linear dynamic systems driven by zero-mean Gaussian processes is modeled. The task is on a slow enough time scale that physiological constraints are insignificant compared with cognitive limitations. The model is basically a linear regression system identifier with a limited memory and noisy observations. Experimental data are presented and compared to the model.

Rouse, W. B.↗
NASA NTRS1973

Models of man as a suboptimal predictor

Models of man making predictions of future states of discrete linear dynamic systems are considered. The task is forced-pace, but the pace is slow enough to eliminate the effects of reaction time and neuromuscular lag. The best of the several models considered includes the constraints of limited memory and observation noise.

Rouse, W. B.↗
NASA NTRS1975

Accuracy of estimating the masses of Phobos and Deimos from multiple Viking orbiter encounters

The problem was investigated of estimating the masses of Phobos and Deimos from Doppler and onboard optical measurements during the Viking extended mission. A Kalman filter was used to analyze the effects of gravitational uncertainties and nongravitational accelerations. These accelerations destroy the dynamical integrity of the orbit, and multibatch or limited memory filtering is preferred to single batch processing. Optical tracking is essential to improve the relative orbit geometry. The masses can be determined to about 10% and 25% respectively for Phobos and Deimos, assuming satellite densities of about 3 gr/cu cm.

Tolson, R. H.↗
NASA NTRS1975

Accuracy of estimating the masses of Phobos and Deimos from multiple Viking orbiter encounters

This paper addresses the problem of estimating the masses of Phobos and Deimos from Doppler and onboard optical measurements during the Viking extended mission. A Kalman filter is used to analyze the effects of gravitational uncertainties and nongravitational accelerations. These accelerations destroy the dynamical integrity of the orbit and multi-batch or limited memory filtering is preferred to single batch processing. Optical tracking is essential to improve the relative orbit geometry. The masses can be determined to about 10% and 25% respectively for Phobos and Deimos, assuming satellite densities of about 3 g per cu cm.

Tolson, R. H.↗
NASA NTRS1987

Conservative zonal schemes for patched grids in 2 and 3 dimensions

The computation of flow over complex geometries, such as realistic aircraft configurations, poses difficult grid generation problems for computational aerodynamicists. The creation of a traditional, single-module grid of acceptable quality about an entire configuration may be impossible even with the most sophisticated of grid generation techniques. A zonal approach, wherein the flow field is partitioned into several regions within which grids are independently generated, is a practical alternative for treating complicated geometries. This technique not only alleviates the problems of discretizing a complex region, but also facilitates a block processing approach to computation thereby circumventing computer memory limitations. The use of such a zonal scheme, however, requires the development of an interfacing procedure that ensures a stable, accurate, and conservative calculation for the transfer of information across the zonal borders.

Hessenius, Kristin A.↗
NASA NTRS1988

System identification in the microcomputer environment

An implementation of an algorithm for system identification, the eigenvalue realization algorithm (ERA), on a microcomputer is reported. Test results are presented to show that accurate structural identification can be performed in a microcomputer environment. It is also shown that the memory limits (640 K) of small machines are generally adequate for solving large scale problems (e.g., Hankel matrices with 15,000 elements), with run times being on the order of several minutes.

Garcia, Ephrahim↗
NASA NTRS1992

User's manual for the Gaussian windows program

'Gaussian Windows' is a method for exploring a set of multivariate data, in order to estimate the shape of the underlying density function. The method can be used to find and describe structural features in the data. The method is described in two earlier papers. I assume that the reader has access to both of these papers, so I will not repeat material from them. The program described herein is written in BASIC and it runs on an IBM PC or PS/2 with the DOS 3.3 operating system. Although the program is slow and has limited memory space, it is adequate for experimenting with the method. Since it is written in BASIC, it is relatively easy to modify. The program and some related files are available on a 3-inch diskette. A listing of the program is also available. This user's manual explains the use of the program. First, it gives a brief tutorial, illustrating some of the program's features with a set of artificial data. Then, it describes the results displayed after the program does a Gaussian window, and it explains each of the items on the various menus.

Jaeckel, Louis A.↗
NASA NTRS1994

Performance issues for iterative solvers in device simulation

Due to memory limitations, iterative methods have become the method of choice for large scale semiconductor device simulation. However, it is well known that these methods still suffer from reliability problems. The linear systems which appear in numerical simulation of semiconductor devices are notoriously ill-conditioned. In order to produce robust algorithms for practical problems, careful attention must be given to many implementation issues. This paper concentrates on strategies for developing robust preconditioners. In addition, effective data structures and convergence check issues are also discussed. These algorithms are compared with a standard direct sparse matrix solver on a variety of problems.

Fan, Qing↗
NASA NTRS1995

Computing Equilibrium Chemical Compositions

Chemical Equilibrium With Transport Properties, 1993 (CET93) computer program provides data on chemical-equilibrium compositions. Aids calculation of thermodynamic properties of chemical systems. Information essential in design and analysis of such equipment as compressors, turbines, nozzles, engines, shock tubes, heat exchangers, and chemical-processing equipment. CET93/PC is version of CET93 specifically designed to run within 640K memory limit of MS-DOS operating system. CET93/PC written in FORTRAN.

Mcbride, Bonnie J.↗
NASA NTRS1996

Program For Evaluation Of Reliability Of Ceramic Parts

CARES/LIFE predicts probability of failure of monolithic ceramic component as function of service time. Assesses risk that component fractures prematurely as result of subcritical crack growth (SCG). Effect of proof testing of components prior to service also considered. Coupled to such commercially available finite-element programs as ANSYS, ABAQUS, MARC, MSC/NASTRAN, and COSMOS/M. Also retains all capabilities of previous CARES code, which includes estimation of fast-fracture component reliability and Weibull parameters from inert strength (without SCG contributing to failure) specimen data. Estimates parameters that characterize SCG from specimen data as well. Written in ANSI FORTRAN 77 to be machine-independent. Program runs on any computer in which sufficient addressable memory (at least 8MB) and FORTRAN 77 compiler available. For IBM-compatible personal computer with minimum 640K memory, limited program available (CARES/PC, COSMIC number LEW-15248).

Nemeth, N.↗
NASA NTRS1999

Inlet Spillage Drag Predictions Using the AIRPLANE Code

AIRPLANE (Jameson/Baker) is a steady inviscid unstructured Euler flow solver. It has been validated on many HSR geometries. It is implemented as MESHPLANE, an unstructured mesh generator, and FLOPLANE, an iterative flow solver. The surface description from an Intergraph CAD system goes into MESHPLANE as collections of polygonal curves to generate the 3D mesh. The flow solver uses a multistage time stepping scheme with residual averaging to approach steady state, but R is not time accurate. The flow solver was ported from Cray to IBM SP2 by Wu-Sun Cheng (IBM); it could only be run on 4 CPUs at a time because of memory limitations. Meshes for the four cases had about 655,000 points in the flow field, about 3.9 million tetrahedra, about 77,500 points on the surface. The flow solver took about 23 wall seconds per iteration when using 4 CPUs. It took about eight and a half wall hours to run 1,300 iterations at a time (the queue limit is 10 hours). A revised version of FLOPLANE (Thomas) was used on up to 64 CPUs to finish up some calculations at the end. We had to turn on more communication when using more processors to eliminate noise that was contaminating the flow field; this added about 50% to the elapsed wall time per iteration when using 64 CPUs. This study involved computing lift and drag for a wing/body/nacelle configuration at Mach 0.9 and 4 degrees pitch. Four cases were considered, corresponding to four nacelle mass flow conditions.

Thomas, Scott D.↗
NASA NTRS2000

Functionality Improvements to Overaero

The functionality of the overset, static aeroelasticity, Navier-Stokes flow solver OVERAERO was increased by adding capability to the flow solver and enhancing code performance. Improvements were made to the fluids/structure interface, an MLP version of the parallel OVERAERO code was developed, and the OVERAERO-MPI code was ported to the Cray T3E. The OVERFLOW-MPI and OVERAERO-MPI codes were tested successfully on the IPG testbed and a means of reducing communication overhead within OVERFLOW-MPI was investigated. To solve an aeroelastic problem computationally, a structures grid surface definition and a fluids grid surface definition are required. Typically, the structures grid surface has a lower fidelity than the fluids grid surface. Thus, the methods developed to transfer data between the two grid systems are vital to the accuracy and efficiency of the aeroelasticity code. The fluids/structures interface developed for the OVERAERO code was improved to more accurately treat fluids surfaces that bridge between two different structural surfaces. For example, the method allowed the forward portion of a flap track fairing to deform with the wing and the aft end of the fairing to deform with the flap. A tightly-coupled version of the code based on OVERFLOW-MLP was developed to improve code performance on the SGI Origin 2000. This required a new parallelization strategy to couple the fluids and structures codes. The OVERAERO-MPI code was ported to the Cray T3E to extend the usability of the code. The port required extensive use of dynamic memory management techniques to fit large problems within the memory limitations of the T3E. The OVERFLOW-MPI and OVERAERO-MPI codes were tested on the IPG testbed being developed within NASA. For small problems with minimal data transfer between grids, there was little to no performance penalty spreading the computation across two machines. For very large problems, methods were developed to minimize intermachine communication via the grid partitioning scheme. By minimizing the intermachine communication requirements of the problem, it may still be beneficial to run a tightly-coupled flow solver across two machines within the IPG.

Gee, Ken↗
NASA NTRS1999

Adaptive Mesh Refinement for Microelectronic Device Design

Finite element and finite volume methods are used in a variety of design simulations when it is necessary to compute fields throughout regions that contain varying materials or geometry. Convergence of the simulation can be assessed by uniformly increasing the mesh density until an observable quantity stabilizes. Depending on the electrical size of the problem, uniform refinement of the mesh may be computationally infeasible due to memory limitations. Similarly, depending on the geometric complexity of the object being modeled, uniform refinement can be inefficient since regions that do not need refinement add to the computational expense. In either case, convergence to the correct (measured) solution is not guaranteed. Adaptive mesh refinement methods attempt to selectively refine the region of the mesh that is estimated to contain proportionally higher solution errors. The refinement may be obtained by decreasing the element size (h-refinement), by increasing the order of the element (p-refinement) or by a combination of the two (h-p refinement). A successful adaptive strategy refines the mesh to produce an accurate solution measured against the correct fields without undue computational expense. This is accomplished by the use of a) reliable a posteriori error estimates, b) hierarchal elements, and c) automatic adaptive mesh generation. Adaptive methods are also useful when problems with multi-scale field variations are encountered. These occur in active electronic devices that have thin doped layers and also when mixed physics is used in the calculation. The mesh needs to be fine at and near the thin layer to capture rapid field or charge variations, but can coarsen away from these layers where field variations smoothen and charge densities are uniform. This poster will present an adaptive mesh refinement package that runs on parallel computers and is applied to specific microelectronic device simulations. Passive sensors that operate in the infrared portion of the spectrum as well as active device simulations that model charge transport and Maxwell's equations will be presented.

Cwik, Tom↗
NASA NTRS2000

Ordering Unstructured Meshes for Sparse Matrix Computations on Leading Parallel Systems

The ability of computers to solve hitherto intractable problems and simulate complex processes using mathematical models makes them an indispensable part of modern science and engineering. Computer simulations of large-scale realistic applications usually require solving a set of non-linear partial differential equations (PDES) over a finite region. For example, one thrust area in the DOE Grand Challenge projects is to design future accelerators such as the SpaHation Neutron Source (SNS). Our colleagues at SLAC need to model complex RFQ cavities with large aspect ratios. Unstructured grids are currently used to resolve the small features in a large computational domain; dynamic mesh adaptation will be added in the future for additional efficiency. The PDEs for electromagnetics are discretized by the FEM method, which leads to a generalized eigenvalue problem Kx = AMx, where K and M are the stiffness and mass matrices, and are very sparse. In a typical cavity model, the number of degrees of freedom is about one million. For such large eigenproblems, direct solution techniques quickly reach the memory limits. Instead, the most widely-used methods are Krylov subspace methods, such as Lanczos or Jacobi-Davidson. In all the Krylov-based algorithms, sparse matrix-vector multiplication (SPMV) must be performed repeatedly. Therefore, the efficiency of SPMV usually determines the eigensolver speed. SPMV is also one of the most heavily used kernels in large-scale numerical simulations.

Oliker, Leonid↗
NASA NTRS1998

Method and system for data clustering for very large databases

Multi-dimensional data contained in very large databases is efficiently and accurately clustered to determine patterns therein and extract useful information from such patterns. Conventional computer processors may be used which have limited memory capacity and conventional operating speed, allowing massive data sets to be processed in a reasonable time and with reasonable computer resources. The clustering process is organized using a clustering feature tree structure wherein each clustering feature comprises the number of data points in the cluster, the linear sum of the data points in the cluster, and the square sum of the data points in the cluster. A dense region of data points is treated collectively as a single cluster, and points in sparsely occupied regions can be treated as outliers and removed from the clustering feature tree. The clustering can be carried out continuously with new data points being received and processed, and with the clustering feature tree being restructured as necessary to accommodate the information from the newly received data points.

Zhang, Tian↗
NASA NTRS2014

Statistical Symbolic Execution with Informed Sampling

Symbolic execution techniques have been proposed recently for the probabilistic analysis of programs. These techniques seek to quantify the likelihood of reaching program events of interest, e.g., assert violations. They have many promising applications but have scalability issues due to high computational demand. To address this challenge, we propose a statistical symbolic execution technique that performs Monte Carlo sampling of the symbolic program paths and uses the obtained information for Bayesian estimation and hypothesis testing with respect to the probability of reaching the target events. To speed up the convergence of the statistical analysis, we propose Informed Sampling, an iterative symbolic execution that first explores the paths that have high statistical significance, prunes them from the state space and guides the execution towards less likely paths. The technique combines Bayesian estimation with a partial exact analysis for the pruned paths leading to provably improved convergence of the statistical analysis. We have implemented statistical symbolic execution with in- formed sampling in the Symbolic PathFinder tool. We show experimentally that the informed sampling obtains more precise results and converges faster than a purely statistical analysis and may also be more efficient than an exact symbolic analysis. When the latter does not terminate symbolic execution with informed sampling can give meaningful results under the same time and memory limits.

Reliability↗