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At least 937 records · Page 52

All sources NASA NTRS DOE OSTI

NASA NTRSDate not supplied

Feasibility Study of Distributed Decision-Making on the Edge for Urban Air Mobility

The Concept of Operations for Urban Air Mobility (UAM) put forward by FAA, NASA, and several industry stakeholders acknowledges the diversity and complexity in UAM operations and, thereby, envisions a federated architecture for UAM management. In this architecture, the decision-making is distributed to a set of service providers who collectively manage the shared airspace usage by different stakeholders. This notionally brings autonomy closer to the UAM businesses and encourages to explore the feasibility of decision making on the very edge, which is the topic of the presented research. This paper reports research conducted on the hypothesis based on which the residual compute capability onboard smart unmanned aerial systems (UASs) is utilized to build situational awareness and resolve conflicts by passive and active coordination among multiple UASs, thereby implementing a layer of distributed autonomy in UAM. Key features of the edge-computing approach involve inter-UAS information exchange, independent assessment of own flight and environmental conditions, and estimation of other UASs’ flight preferences, incorporating machine learning techniques in the last two. Parallel computing on portable graphics processing unit (GPU) enables the machine learning workflow on the edge. A custom-built 3D simulator is used to evaluate the efficacy of the distributed decision-making on the edge. Each edge node, representing a smart UAS, connects to the simulator from a remote location and independently controls the behavior of the corresponding virtual asset in the simulator, analogous to participants in an online multi-player game. The presented edge-computing-based distributed decision-making framework is envisioned to pave the way for collective mobility of autonomous air vehicles in the future shared airspace, while allowing the inclusion of the business preferences of the UAS operators within allowed regulatory limits.

Edge computing↗

NASA NTRSDate not supplied

Feasibility Study of Distributed Decision-Making on the Edge for Urban Air Mobility

Edge computing↗

DOE OSTI2026

Enabling the Broader Use of MOOSE for Nuclear Energy and Other Simulation

This Final Scientific and Technical Report summarizes work performed under the Phase IIA SBIR project “Enabling the Broader Use of MOOSE for Nuclear Energy and Other Simulation” (DE-SC0020906) from August 2023 through August 2025. The objective of the Phase IIA effort was to mature and harden capabilities developed during Phase II, with the goal of enabling practical interoperability between Coreform’s isogeometric analysis (IGA) technologies and the Multiphysics Object-Oriented Simulation Environment (MOOSE), while improving robustness, performance, and scalability for complex, nuclear-relevant geometries. Over the course of Phase IIA, the project established and validated an extraction-based interoperability pathway between Coreform tools and MOOSE. A combined mesh and matrix format was defined collaboratively with MOOSE developers and integrated into the solver, enabling standard MOOSE workflows to operate on data exported from Coreform’s IGA and Flex Representation Method (FRM) pipelines. Early demonstrations validated architectural compatibility using linear solid mechanics problems, while later efforts focused on benchmark testing and external use. By the end of the project period, engineers at BWXT were able to independently set up and execute a simulation using the Coreform–MOOSE workflow and provide direct feedback that informed further refinement. In parallel, substantial effort was devoted to improving the robustness of trimmed U-spline construction for complex CAD geometries. A growing test suite of nuclear-relevant models was compiled through collaboration with multiple stakeholders and used to drive extensive bug fixing and reliability improvements. These efforts resulted in improved robustness and performance, including the addition of fallback capabilities that enhance reliability when the underlying commercial CAD kernel fails. Performance-oriented work progressed later in the project, with the development and demonstration of methods to decompose complex geometries into structured subregions and updated data representations to support more efficient solver processing. Additionally, extensive enhancements to threadsafe parallel data structures and trimming operations established a foundation for scalable processing of large assemblies. Collaboration with Sandia National Laboratories on the SGM geometric modeling kernel advanced to a functioning interface test case, positioning the workflow for future kernel integration. Overall, the Phase IIA effort successfully transitioned the project from architectural proof-of-concept to externally exercised, solver-integrated capability, while clarifying remaining technical challenges related to standardization, performance optimization, and kernel integration.

42 ENGINEERING↗

NASA NTRS1993

Computing Flow Transition On Parallel Processors

Parallel algorithm developed on multiple-microprocessor computer. Program initiated to develop computer codes capable of directly simulating and mathematically modeling transition process at mach numbers ranging from subsonic to hypersonic. Parallel computers potentially offer reduction of processing time; processing time inversely proportional to number of available processors.

Bokhari, S.↗

DOE OSTI2025

Leveraging Pre-Built Catalogs and Object-Level Scheduling to Eliminate I/O Bottlenecks in HPC Environments

Modern High-Performance Computing (HPC) environments face mounting challenges due to the shift from large to small file datasets, along with an increasing number of users and parallelized applications. As HPC systems rely on Parallel File Systems (PFS), such as Lustre for data processing, performance bottlenecks stemming from Object Storage Target (OST) contention have become a significant concern. Existing solutions, such as LADS with its object-level scheduling approach, fall short in large-scale HPC environments due to their inability to effectively address metadata I/O bottlenecks and the growing number of I/O processes. This study highlights the pressing need for a comprehensive solution that tackles both OST contention and metadata I/O challenges in diverse HPC workloads. To address these challenges, we propose SwiftLoad, an object-level I/O scheduling framework that leverages a metadata catalog to enhance the performance and efficiency of parallel HPC utilities. The adoption of the metadata catalog mitigates the metadata I/O bottlenecks that commonly occur in HPC utilities, a challenge that is particularly pronounced in object-level I/O scheduling. SwiftLoad addresses OST contention and the uneven distribution of I/O processes across different OSTs through mathematical modeling and incorporates a Loader Configuration Module to regulate the number of I/O processes. Evaluated with two representative utilities—data deduplication profiling and data augmentation—SwiftLoad achieved performance improvements of up to 5.63x and 11.0x, respectively, on a production supercomputer.

HPC↗

NASA NTRS1989

Ion reflection and downstream thermalization at the quasi-parallel bow shock

Using the results of ISEE 2 plasma and magnetic field measurements, two features related to the ion thermalization process at high-Mach-number (M above 2) quasi-parallel collisionless shocks are discussed. These are the presence of a coherent secondary beam of ions within the shock layer which is considered to be produced by reflection, and downstream ion distributions which contain both a relatively cold core of directly transmitted ions and a hotter 'shell' of ions, which appear to result from the disruption and scattering of ions initially reflected at the shock. Evidence is presented that coherent ion reflection is an important element of the ion energy dissipation process at high-Mach-number quasi-parallel shocks.

Gosling, J. T.↗

NASA NTRS1992

A novel visual hardware behavioral language

Most hardware behavioral languages just use texts to describe the behavior of the desired hardware design. This is inconvenient for VLSI designers who enjoy using the schematic approach. The proposed visual hardware behavioral language has the ability to graphically express design information using visual parallel models (blocks), visual sequential models (processes) and visual data flow graphs (which consist of primitive operational icons, control icons, and Data and Synchro links). Thus, the proposed visual hardware behavioral language can not only specify hardware concurrent and sequential functionality, but can also visually expose parallelism, sequentiality, and disjointness (mutually exclusive operations) for the hardware designers. That would make the hardware designers capture the design ideas easily and explicitly using this visual hardware behavioral language.

Li, Xueqin↗

NASA NTRSDate not supplied

Adding GPU Support to the Markov Chain Monte Carlo Code Catmip

In geophysics, we are confronted with many under-determined inverse problems. For example, all of our observations of earthquakes are made at the Earth’s surface. So, when we try to infer how slip during an earthquake evolves in space and time, we find that there are many potential slip histories that are consistent with our limited observations and our understanding of earthquake physics. One way to approach these problems is with Bayesian analysis which allows us to infer the ensemble of all potential slip models that satisfy the observations and our prior knowledge of earthquake physics. In Bayesian analysis, our prior knowledge is known as the prior probability density function or prior PDF, the fit to the data is known as the data likelihood, and the target PDF that satisfies both the prior PDF and data likelihood is known as the posterior PDF. However, simulating the posterior PDF typically requires using Markov Chain Monte Carlo (MCMC) to draw tens of billions of random realizations of earthquake slip models, which may not be computationally feasible. To make this and similar geophysical inversions computationally tractable, we developed the Cascading Adaptive Transitional Metropolis In Parallel (CATMIP) algorithm. CATMIP is an efficient parallel Markov Chain Monte Carlo (MCMC) sampler that is used for model fitting and uncertainty quantification in geophysics. Example use cases are earthquake rupture modeling, determining mineral composition on Mars, reconstructing the history of ocean salinity, and historical earthquake relocation. CATMIP employs many parallel instances of the Metropolis algorithm for sampling in a transitioning framework. Transitioning is a process in which a set of random samples at equilibrium with a known probability density function (PDF) are used as seeds for the Markov chains to sample successive target PDFs that incrementally move the distribution from the starting seeds to the final desired PDF that describes the relative plausibility of potential values for the model parameters. The algorithm is implemented as a Master-Worker model employing MPI for communication. The worker processes are loosely coupled with global parameters periodically optimized by the master process. This provides a very high amount of parallelism with little communication between updates. During the presentation we will discuss the history of the algorithm and elaborate the earthquake rupture modeling use case for the CATMIP package. Our first step toward GPU optimization was to optimize the code for the CPU. CPU profiling revealed that most of the compute time is spent in calls to level 2 BLAS routines and calls to GSL random number generators. We revised the algorithm to employ level 3 BLAS routines instead. In our presentation we will describe how this was accomplished. Adding GPU support to CATMIP consisted mostly of replacing the calls to GSL with calls to GPU vendor-provided library routines. A small number of loops were directly implemented in CUDA. In the presentation will provide implementation details. Finally, we will discuss methods for profiling and opportunities for further optimizing GPU execution. By creating a code with the flexibility to run on either a CPU or GPU architecture, CATMIP can be used on systems ranging from large CPU-based HPC environments to single servers with GPU acceleration and everything in between.

HECC↗

NASA NTRS1981

Multigrid solvers on parallel computers

Massively parallel computers, as considered in this investigation, are not yet available. However, a large-scale parallel computer cannot usefully be designed before the hypothetical algorithms which will employ it are studied. Most of the studies of parallel partial differential equations (PDE) solvers are based on solution techniques much slower (on sequential machines) than multigrid methods. Multigrid methods are highly parallelizable. Each of their processes can simultaneously be performed at all grid points. The present investigation is concerned with a preliminary exploration of the potential of multigrid, or, more generally, Multi-Level Adaptive Techniques (MLAT) on computers with many processors. Basic processes are considered, taking into account coarse-grid approximation, relaxation, coarse-grid corrections, full multigrid algorithms, nonlinear problems and eigenvalue problems, fine-to-coarse correction, and chains of problems. Details of parallel multigrid processing are also examined.

Brandt, A.↗

DOE OSTI2026

Real-Time GPU-Accelerated OFDR With an Integrated Auxiliary Interferometer

A GPU-accelerated optical frequency domain reflectometry (OFDR) system with an improved integrated auxiliary interferometer is proposed. Unlike conventional approaches that require separate auxiliary interferometers and multiple detection channels, the proposed OFDR system embeds this functionality directly into the signal via an intentional beat component. This enables self-calibration of laser nonlinearity while maintaining a cost-effective hardware configuration. Building on this simplified configuration, the system leverages GPU acceleration with an NVIDIA RTX 4070 Ti to achieve real-time performance, delivering high-throughput signal processing for continuous OFDR interrogation. The signal processing pipeline comprises signal capture, resampling for nonlinearity compensation, and frequency shift computation, all optimized for parallel execution. Hardware benchmarking demonstrates substantial acceleration over CPU implementations, achieving up to a 45× speedup for resampling and frequency shift computations and enabling processing latencies below 30 ms. Thermal response validation is conducted under two complementary scenarios: localized heating using a water bath and cryogenic-temperature conditions using liquid nitrogen. Under localized heating, the system achieves an accuracy of 0.249 °C with a thermal sensitivity of 5.971 GHz/°C, while cryogenic-temperature validation demonstrates a frequency shift response with a sensitivity of 2.383 GHz/°C and an accuracy of 2.04 °C. The high acceleration of the proposed GPU-accelerated OFDR system and its accuracy are achieved by exploiting CUDA-based stride indexing, enabling efficient parallel segmentation and processing of large datasets without additional memory copies. The benchmarking results confirm the robustness, accuracy, and deployability of the proposed OFDR system across a wide temperature range, establishing it as a practical platform for real-time distributed fiber sensing in structurally dynamic environments.

Harb, Salah [Lawrence Berkeley National Laboratory↗

NASA NTRS1993

Opto-electronic morphological processor

The opto-electronic morphological processor of the present invention is capable of receiving optical inputs and emitting optical outputs. The use of optics allows implementation of parallel input/output, thereby overcoming a major bottleneck in prior art image processing systems. The processor consists of three components, namely, detectors, morphological operators and modulators. The detectors and operators are fabricated on a silicon VLSI chip and implement the optical input and morphological operations. A layer of ferro-electric liquid crystals is integrated with a silicon chip to provide the optical modulation. The implementation of the image processing operators in electronics leads to a wide range of applications and the use of optical connections allows cascadability of these parallel opto-electronic image processing components and high speed operation. Such an opto-electronic morphological processor may be used as the pre-processing stage in an image recognition system. In one example disclosed herein, the optical input/optical output morphological processor of the invention is interfaced with a binary phase-only correlator to produce an image recognition system.

Yu, Jeffrey W.↗

NASA NTRS1988

Overview and extensions of a system for routing directed graphs on SIMD architectures

Many problems can be described in terms of directed graphs that contain a large number of vertices where simple computations occur using data from adjacent vertices. A method is given for parallelizing such problems on an SIMD machine model that uses only nearest neighbor connections for communication, and has no facility for local indirect addressing. Each vertex of the graph will be assigned to a processor in the machine. Rules for a labeling are introduced that support the use of a simple algorithm for movement of data along the edges of the graph. Additional algorithms are defined for addition and deletion of edges. Modifying or adding a new edge takes the same time as parallel traversal. This combination of architecture and algorithms defines a system that is relatively simple to build and can do fast graph processing. All edges can be traversed in parallel in time O(T), where T is empirically proportional to the average path length in the embedding times the average degree of the graph. Additionally, researchers present an extension to the above method which allows for enhanced performance by allowing some broadcasting capabilities.

Tomboulian, Sherryl↗

DOE OSTI2024

Development of algorithms for augmenting and replacing conventional process control using reinforcement learning

Here, this work seeks to allow for the online operation and training of model-free reinforcement learning (RL) agents but limit the risk to system equipment and personnel. The parallel implementation of RL alongside more conventional process control (CPC) allows for the RL algorithm to learn from CPC. The past performance of both methods are assessed on a continuous basis allowing for a transition from CPC to RL and, if needed, transitioning back to CPC from RL. This allows for the RL algorithm to slowly and safely assume control of the process without significant degradation in control performance. It is shown that the RL can derive a near optimal policy even when coupled with a suboptimal CPC. It is also demonstrated that the coupled RL-CPC algorithm learns at a faster rate than traditional RL methods of exploration while the algorithm’s performance does not deteriorate below CPC, even when exposed to an unknown operating condition.

30 DIRECT ENERGY CONVERSION↗

NASA NTRS1988

Adaptive parallel logic networks

Adaptive, self-organizing concurrent systems (ASOCS) that combine self-organization with massive parallelism for such applications as adaptive logic devices, robotics, process control, and system malfunction management, are presently discussed. In ASOCS, an adaptive network composed of many simple computing elements operating in combinational and asynchronous fashion is used and problems are specified by presenting if-then rules to the system in the form of Boolean conjunctions. During data processing, which is a different operational phase from adaptation, the network acts as a parallel hardware circuit.

Martinez, Tony R.↗

NASA NTRS1994

Analysis of DE-1 PWI electric field data

The measurement of low frequency electric field oscillations may be accomplished with the Plasma Wave Instrument (PWI) on DE 1. Oscillations at a frequency around 1 Hz are below the range of the conventional plasma wave receivers, but they can be detected by using a special processing of the quasi-static electric field data. With this processing it is also possible to determine if the electric field oscillations are predominately parallel or perpendicular to the ambient magnetic field. The quasi-static electric field in the DE 1 spin/orbit plane is measured with a long-wire 'double probe'. This antenna is perpendicular to the satellite spin axis, which in turn is approximately perpendicular to the geomagnetic field in the polar magnetosphere. The electric field data are digitally sampled at a frequency of 16 Hz. The measured electric field signal, which has had phase reversals introduced by the rotating antenna, is multiplied by the sine of the rotation angle between the antenna and the magnetic field. This is called the 'perpendicular' signal. The measured time series is also multiplied with the cosine of the angle to produce a separate 'parallel' signal. These two separate time series are then processed to determine the frequency power spectrum.

Weimer, Daniel↗

NASA NTRS1981

A model for simulation and processing of radar images

A model for recording, processing, presentation, and analysis of radar images in digital form is presented. The observed image is represented as having two random components, one which models the variation due to the coherent addition of electromagnetic energy scattered from different objects in the illuminated areas. This component is referred to as fading. The other component is a representation of the terrain variation which can be described as the actual signal which the radar is attempting to measure. The combination of these two components provides a description of radar images as being the output of a linear space-variant filter operating on the product of the fading and terrain random processes. In addition, the model is applied to a digital image processing problem using the design and implementation of enhancement scene. Finally, parallel approaches are being employed as possible means of solving other processing problems such as SAR image map-matching, data compression, and pattern recognition.

Stiles, J. A.↗

DOE OSTI2026

A Parallel Kinetic Model for Surface and Bulk Charge Storage in ε -MnO 2 Pseudocapacitors

Pseudocapacitive materials such as manganese dioxide (MnO 2 ) are attractive for energy storage applications due to their ability to combine the fast kinetics of capacitors with the higher energy density of battery-type systems. However, the electrochemical behavior of MnO 2 remains difficult to interpret mechanistically, in part because existing models often fail to distinguish between surface-based redox processes and bulk intercalation mechanisms. In this work, we develop a physics-based model that represents MnO 2 pseudocapacitance as a linear combination of two independent, parallel electrochemical processes: (i) the surface or near-surface redox storage and (ii) lithium ion intercalation into the bulk material. These two processes are treated with distinct kinetic and thermodynamic parameters and are assumed to proceed independently. The total measured current is assumed to be the sum of these two partial currents. We validate the model using rate-dependent cyclic voltammetry experiments, demonstrating that it captures key trends and provides physically interpretable parameters reflecting the relative contributions of surface and bulk processes. By enabling a clear separation between these mechanisms, the model offers a useful framework for analyzing pseudocapacitive materials and can guide the rational design of high-performance energy storage electrodes.

Energy - Storage↗

NASA NTRS1994

An Advanced Simulation Framework for Parallel Discrete-Event Simulation

Discrete-event simulation (DEVS) users have long been faced with a three-way trade-off of balancing execution time, model fidelity, and number of objects simulated. Because of the limits of computer processing power the analyst is often forced to settle for less than desired performances in one or more of these areas.

parallel processing technologies DEVS (PDEVS) ssto↗