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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Computing unsteady shock waves for aeroacoustic applications

The computation of unsteady shock waves, which contribute significantly to noise generation in supersonic jet flows, is investigated. This paper focuses on the difficulties of computing slowly moving shock waves. Numerical error is found to manifest itself principally as a spurious entropy wave. Calculations presented are performed using a third order essentially nonoscillatory scheme. The effect of stencil biasing parameters and of two versions of numerical flux formulas on the magnitude of spurious entropy are investigated. The level of numerical error introduced in the calculation in quantified as a function of shock pressure ratio, shock speed, Courant number, and mesh density. The spurious entropy relative to the entropy jump across a static shock decreases with increasing shock strength and shock velocity relative to the grid, but is insensitive to Courant number. The structure of the spurious entropy wave is affected by the choice of flux formulas and algorithm biasing parameters. The effect of the spurious numerical waves on the calculation of sound amplification by a shock wave is investigated. For this class of problem, the acoustic pressure waves are relatively unaffected by the spurious numerical phenomena.

Meadows,, Kristine r.↗
NASA NTRS1985

Some recent advances in computational aerodynamics for helicopter applications

The growing application of computational aerodynamics to nonlinear helicopter problems is outlined, with particular emphasis on several recent quasi-two-dimensional examples that used the thin-layer Navier-Stokes equations and an eddy-viscosity model to approximate turbulence. Rotor blade section characteristics can now be calculated accurately over a wide range of transonic flow conditions. However, a finite-difference simulation of the complete flow field about a helicopter in forward flight is not currently feasible, despite the impressive progress that is being made in both two and three dimensions. The principal limitations are today's computer speeds and memories, algorithm and solution methods, grid generation, vortex modeling, structural and aerodynamic coupling, and a shortage of engineers who are skilled in both computational fluid dynamics and helicopter aerodynamics and dynamics.

Mccroskey, W. J.↗
NASA NTRS1996

Interconnections For Stacked Parallel Computer Modules

Concept for interconnecting modules in parallel computers leads to cheaper, smaller, lighter, lower-power computing systems for aerospace, industrial, business, and consumer applications. Computer modules stacked and interconnected in various configurations. Connections among stacks controlled by switching within gateways and/or by addresses on buses.

Johannesson, Richard T.↗
NASA NTRS1987

The use of computers for instruction in fluid dynamics

Applications for computers which improve instruction in fluid dynamics are examined. Computers can be used to illustrate three-dimensional flow fields and simple fluid dynamics mechanisms, to solve fluid dynamics problems, and for electronic sketching. The usefulness of computer applications is limited by computer speed, memory, and software and the clarity and field of view of the projected display. Proposed advances in personal computers which will address these limitations are discussed. Long range applications for computers in education are considered.

Watson, Val↗
NASA NTRSDate not supplied

Use of Assistive Technology to Augment API Capabilities

Application Programming Interfaces (APIs) allow for access to data and capabilities of computer applications by developers or users with experience in computer programming. Recent development with both Thermal Desktop and ESATAN-TMS have provided APIs to allow users to develop their own capabilities that interface with the Graphical User Interfaces (GUI) or manipulate the thermal model data. However, these APIs are only as good as the breadth of features in the native code accessible through the API. If a particular code’s feature is not accessible through the API, then users have very limited options besides waiting for updates to the API that expose the necessary functionality, particularly if model data access or user action, such as a button click, is required. However, Assistive Technology features that allow for users with a disability to more fully experience a software’s capabilities may be creatively utilized to gain further access to data and capabilities not yet exposed by the API. This paper describes the process to augment the features of the OpenTD API via assistive technology and describes how to identify the application instance, navigate GUI elements, updates values on forms, and execute actions such as selecting a listbox item or clicking a button. It concludes with identifying some of the pitfalls to avoid and describes methods to best implement this approach.

Application Programming Interface↗
NASA NTRSDate not supplied

Use of Assistive Technology to Augment API Capabilities

Application Programming Interfaces (APIs) allow for access to data and capabilities of computer applications by developers or users with experience in computer programming. Recent development with both Thermal Desktop and ESATAN-TMS have provided APIs to allow users to develop their own capabilities that interface with the Graphical User Interfaces (GUI) or manipulate the thermal model data. However, these APIs are only as good as the breadth of features in the native code accessible through the API; if a particular code’s feature is not accessible through the API, then users have very limited options besides waiting for updates to the API that expose the necessary functionality, particularly if model data access or user action, such as a button click, is required. However, Assistive Technology features that allow for differently-abled users to more fully experience a software’s capabilities may be creatively utilized to gain further access to data and capabilities not yet exposed by the API. This paper describes the process to augment the features of the OpenTD API via assistive technology and describes how to identify the application instance, navigate GUI elements, updates values on forms, and execute actions such as selecting a listbox item or clicking a button. It concludes with identifying some of the pitfalls to avoid and describes methods to best implement this approach.

Application Programming Interface↗
DOE OSTI2018

Photonic Memory Controller Module (P-MCM)

In this Program, a team of industry and academic experts in optical interconnect design have come together to develop optical components and network architectures for the next generation high-bandwidth memory modules for DOE relevant high-performance computing applications.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1982

Ozone Uncertainties Study Algorithm (OUSA)

An algorithm to carry out sensitivities, uncertainties and overall imprecision studies to a set of input parameters for a one dimensional steady ozone photochemistry model is described. This algorithm can be used to evaluate steady state perturbations due to point source or distributed ejection of H2O, CLX, and NOx, besides, varying the incident solar flux. This algorithm is operational on IBM OS/360-91 computer at NASA/Goddard Space Flight Center's Science and Applications Computer Center (SACC).

Bahethi, O. P.↗
DOE OSTI2017

Piecewise empirical model (PEM) of resistive memory for pulsed analog and neuromorphic applications

With the end of Dennard scaling and the ever-increasing need for more efficient, faster computation, resistive switching devices (ReRAM), often referred to as memristors, are a promising candidate for next generation computer hardware. These devices show particular promise for use in an analog neuromorphic computing accelerator as they can be tuned to multiple states and be updated like the weights in neuromorphic algorithms. Modeling a ReRAM-based neuromorphic computing accelerator requires a compact model capable of correctly simulating the small weight update behavior associated with neuromorphic training. These small updates have a nonlinear dependence on the initial state, which has a significant impact on neural network training. Consequently, we propose an empirically derived general purpose model that can accurately capture the nonlinearity of an arbitrary two-terminal device to match pulse measurements important for neuromorphic computing applications. By defining the state of the device to be proportional to its current, the model parameters can be extracted from a series of voltages pulses that mimic the behavior of a device in an analog neuromorphic computing accelerator. This allows for a general, accurate, and intuitive compact circuit model that is applicable to different resistance switching device technologies. In this work we explain the details of the model, implement the model in the circuit simulator Xyce, and give an example of its usage to model a specific Ta/TaO x device.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

The Concept of a Quantum Edge Simulator: Edge Computing and Sensing in the Quantum Era

Sensors, enabling observations across vast spatial, spectral, and temporal scales, are major data generators for information technology (IT). Processing, storing, and communicating this ever-growing amount of data pose challenges for the current IT infrastructure. Edge computing—an emerging paradigm to overcome the shortcomings of cloud-based computing—could address these challenges. Furthermore, emerging technologies such as quantum computing, quantum sensing, and quantum communications have the potential to fill the performance gaps left by their classical counterparts. Here, we present the concept of an edge quantum computing (EQC) simulator—a platform for designing the next generation of edge computing applications. An EQC simulator is envisioned to integrate elements from both quantum technologies and edge computing to allow studies of quantum edge applications. The presented concept is motivated by the increasing demand for more sensitive and precise sensors that can operate faster at lower power consumption, generating both larger and denser datasets. These demands may be fulfilled with edge quantum sensor networks. Envisioning the EQC era, we present our view on how such a scenario may be amenable to quantification and design. Given the cost and complexity of quantum systems, constructing physical prototypes to explore design and optimization spaces is not sustainable, necessitating EQC infrastructure and component simulators to aid in co-design. We discuss what such a simulator may entail and possible use cases that invoke quantum computing at the edge integrated with new sensor infrastructures.

47 OTHER INSTRUMENTATION↗
DOE OSTI2015

Understanding the Performance and Potential of Cloud Computing for Scientific Applications

In this paper, commercial clouds bring a great opportunity to the scientific computing area. Scientific applications usually require significant resources, however not all scientists have access to sufficient high-end computing systems, may of which can be found in the Top500 list. Cloud Computing has gained the attention of scientists as a competitive resource to run HPC applications at a potentially lower cost. But as a different infrastructure, it is unclear whether clouds are capable of running scientific applications with a reasonable performance per money spent. This work studies the performance of public clouds and places this performance in context to price. We evaluate the raw performance of different services of AWS cloud in terms of the basic resources, such as compute, memory, network and I/O. We also evaluate the performance of the scientific applications running in the cloud. This paper aims to assess the ability of the cloud to perform well, as well as to evaluate the cost of the cloud running scientific applications. We developed a full set of metrics and conducted a comprehensive performance evlauation over the Amazon cloud. We evaluated EC2, S3, EBS and DynamoDB among the many Amazon AWS services. We evaluated the memory sub-system performance with CacheBench, the network performance with iperf, processor and network performance with the HPL benchmark application, and shared storage with NFS and PVFS in addition to S3. We also evaluated a real scientific computing application through the Swift parallel scripting system at scale. Armed with both detailed benchmarks to gauge expected performance and a detailed monetary cost analysis, we expect this paper will be a recipe cookbook for scientists to help them decide where to deploy and run their scientific applications between public clouds, private clouds, or hybrid clouds.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

An Asynchronous Many-Task Implementation of In-Situ Statistical Analysis using Legion.

In this report, we propose a framework for the design and implementation of in-situ analy- ses using an asynchronous many-task (AMT) model, using the Legion programming model together with the MiniAero mini-application as a surrogate for full-scale parallel scientific computing applications. The bulk of this work consists of converting the Learn/Derive/Assess model which we had initially developed for parallel statistical analysis using MPI [PTBM11], from a SPMD to an AMT model. In this goal, we propose an original use of the concept of Legion logical regions as a replacement for the parallel communication schemes used for the only operation of the statistics engines that require explicit communication. We then evaluate this proposed scheme in a shared memory environment, using the Legion port of MiniAero as a proxy for a full-scale scientific application, as a means to provide input data sets of variable size for the in-situ statistical analyses in an AMT context. We demonstrate in particular that the approach has merit, and warrants further investigation, in collaboration with ongoing efforts to improve the overall parallel performance of the Legion system.

Pebay, Philippe Pierre↗
NASA NTRS1985

Nuclear Science Symposium, 31st and Symposium on Nuclear Power Systems, 16th, Orlando, FL, October 31-November 2, 1984, Proceedings

Topics related to physics instrumentation are discussed, taking into account cryostat and electronic development associated with multidetector spectrometer systems, the influence of materials and counting-rate effects on He-3 neutron spectrometry, a data acquisition system for time-resolved muscle experiments, and a sensitive null detector for precise measurements of integral linearity. Other subjects explored are concerned with space instrumentation, computer applications, detectors, instrumentation for high energy physics, instrumentation for nuclear medicine, environmental monitoring and health physics instrumentation, nuclear safeguards and reactor instrumentation, and a 1984 symposium on nuclear power systems. Attention is given to the application of multiprocessors to scientific problems, a large-scale computer facility for computational aerodynamics, a single-board 32-bit computer for the Fastbus, the integration of detector arrays and readout electronics on a single chip, and three-dimensional Monte Carlo simulation of the electron avalanche in a proportional counter.

Biggerstaff, J. A.↗
NASA NTRS1985

Multidimensional Modeling of Atmospheric Effects and Surface Heterogeneities on Remote Sensing

The overall goal of this project is to establish a modeling capability that allows a quantitative determination of atmospheric effects on remote sensing including the effects of surface heterogeneities. This includes an improved understanding of aerosol and haze effects in connection with structural, angular, and spatial surface heterogeneities. One important objective of the research is the possible identification of intrinsic surface or canopy characteristics that might be invariant to atmospheric perturbations so that they could be used for scene identification. Conversely, an equally important objective is to find a correction algorithm for atmospheric effects in satellite-sensed surface reflectances. The technical approach is centered around a systematic model and code development effort based on existing, highly advanced computer codes that were originally developed for nuclear radiation shielding applications. Computational techniques for the numerical solution of the radiative transfer equation are adapted on the basis of the discrete-ordinates finite-element method which proved highly successful for one and two-dimensional radiative transfer problems with fully resolved angular representation of the radiation field.

Gerstl, S. A. W.↗
NASA NTRS1975

Technology survey of computer software as applicable to the MIUS project

Existing computer software, available from either governmental or private sources, applicable to modular integrated utility system program simulation is surveyed. Several programs and subprograms are described to provide a consolidated reference, and a bibliography is included. The report covers the two broad areas of design simulation and system simulation.

Fulbright, B. E.↗
DOE OSTI2024

Impacts of floating-point non-associativity on reproducibility for HPC and deep learning applications

Run to run variability in parallel programs caused by floating-point non-associativity has been known to significantly affect reproducibility in iterative algorithms, due to accumulating errors. Non-reproducibility can critically affect the efficiency and effectiveness of correctness testing for stochastic programs. Recently, the sensitivity of deep learning training and inference pipelines to floating-point non-associativity has been found to sometimes be extreme. It can prevent certification for commercial applications, accurate assessment of robustness and sensitivity, and bug detection. New approaches in scientific computing applications have coupled deep learning models with high-performance computing, leading to an aggravation of debugging and testing challenges. Here we perform an investigation of the statistical properties of floating-point non-associativity within modern parallel programming models, and analyze performance and productivity impacts of replacing atomic operations with deterministic alternatives on GPUs. We examine the recently-added deterministic options in PyTorch within the context of GPU deployment for deep learning, uncovering and quantifying the impacts of input parameters triggering run to run variability and reporting on the reliability and completeness of the documentation. Finally, we evaluate the strategy of exploiting automatic determinism that could be provided by deterministic hardware, using the Groq LPUTM accelerator for inference portions of the deep learning pipeline. We demonstrate the benefits that a hardware-based strategy can provide within reproducibility and correctness efforts.

Shanmugavelu, Sanjif↗