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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 451 records · Page 25

Fast Image Texture Classification Using Decision Trees

Texture analysis would permit improved autonomous, onboard science data interpretation for adaptive navigation, sampling, and downlink decisions. These analyses would assist with terrain analysis and instrument placement in both macroscopic and microscopic image data products. Unfortunately, most state-of-the-art texture analysis demands computationally expensive convolutions of filters involving many floating-point operations. This makes them infeasible for radiation- hardened computers and spaceflight hardware. A new method approximates traditional texture classification of each image pixel with a fast decision-tree classifier. The classifier uses image features derived from simple filtering operations involving integer arithmetic. The texture analysis method is therefore amenable to implementation on FPGA (field-programmable gate array) hardware. Image features based on the "integral image" transform produce descriptive and efficient texture descriptors. Training the decision tree on a set of training data yields a classification scheme that produces reasonable approximations of optimal "texton" analysis at a fraction of the computational cost. A decision-tree learning algorithm employing the traditional k-means criterion of inter-cluster variance is used to learn tree structure from training data. The result is an efficient and accurate summary of surface morphology in images. This work is an evolutionary advance that unites several previous algorithms (k-means clustering, integral images, decision trees) and applies them to a new problem domain (morphology analysis for autonomous science during remote exploration). Advantages include order-of-magnitude improvements in runtime, feasibility for FPGA hardware, and significant improvements in texture classification accuracy.

Thompson, David R.↗

The X-38 Spacecraft Fault-Tolerant Avionics System

In 1995 NASA began an experimental program to develop a reusable crew return vehicle (CRV) for the International Space Station. The purpose of the CRV was threefold: (i) to bring home an injured or ill crewmember; (ii) to bring home the entire crew if the Shuttle fleet was grounded; and (iii) to evacuate the crew in the case of an imminent Station threat (i.e., fire, decompression, etc). Built at the Johnson Space Center, were two approach and landing prototypes and one spacecraft demonstrator (called V201). A series of increasingly complex ground subsystem tests were completed, and eight successful high-altitude drop tests were achieved to prove the design concept. In this program, an unprecedented amount of commercial-off-the-shelf technology was utilized in this first crewed spacecraft NASA has built since the Shuttle program. Unfortunately, in 2002 the program was canceled due to changing Agency priorities. The vehicle was 80% complete and the program was shut down in such a manner as to preserve design, development, test and engineering data. This paper describes the X-38 V201 fault-tolerant avionics system. Based on Draper Laboratory's Byzantine-resilient fault-tolerant parallel processing system and their "network element" hardware, each flight computer exchanges information on a strict timescale to process input data, compare results, and issue voted vehicle output commands. Major accomplishments achieved in this development include: (i) a space qualified two-fault tolerant design using mostly COTS (hardware and operating system); (ii) a single event upset tolerant network element board, (iii) on-the-fly recovery of a failed processor; (iv) use of synched cache; (v) realignment of memory to bring back a failed channel; (vi) flight code automatically generated from the master measurement list; and (vii) built in-house by a team of civil servants and support contractors. This paper will present an overview of the avionics system and the hardware implementation, as well as the system software and vehicle command & telemetry functions. Potential improvements and lessons learned on this program are also discussed.

Kouba,Coy↗

Surrogate Neural Architecture Codesign Package (SNAC-Pack)

Neural architecture search (NAS) is a powerful approach for automating model design, but existing methods often optimize for accuracy alone or rely on proxy metrics such as bit operations (BOPs) that correlate poorly with hardware cost. This gap is particularly large for FPGA deployment, where cost is dominated by a multi-dimensional budget of lookup tables, DSPs, flip-flops, BRAM, and latency. We present the Surrogate Neural Architecture Codesign Package (SNAC-Pack), an open-source AutoML framework for hardware-aware neural architecture codesign and end-to-end FPGA deployment. SNAC-Pack runs a multi-objective global search with Optuna and NSGA-II, loading trials to a shared SQLite store that enables parallel workers across compute nodes. A hardware surrogate model outputs per-trial resource and latency estimates, avoiding the synthesis cost that would otherwise dominate the search loop. A local search stage then applies quantization-aware training (QAT) together with iterative magnitude pruning in a combined compression loop, after which the final model is synthesized to FPGA firmware via the hls4ml Python library. A YAML configuration and an optional agentic frontend let users run the pipeline on new datasets without modifying the framework. We demonstrate SNAC-Pack on jet classification at the Large Hadron Collider and superconducting qubit readout, discovering compact architectures that match or exceed strong baselines on the task metric while reducing FPGA resource utilization and, in the qubit readout case, reducing the design space exploration process from months of manual fine-tuning to hours of automated search.

Weitz, Jason [UC, San Diego]↗

Gigaflop architecture, a hardware perspective

Any super computer built in the early 1980s will use components that are available by fall 1978. The architecture of such a system cannot depart radically from current super computers if the software experience painfully acquired from these computers in the 70's is to apply. Given the above constraints, 10 billion floating point operations per second (BFLOPS) are attainable and a problem memory of 512 million (64 bit) words could be supported by the technology of the time. In contrast to this, industry is likely to respond with commercially available machines with a performance of less than 150 MFLOPS. This is due to self-imposed constraints on the manufacturers to provide upward compatible architectures (same instruction set) and systems which can be sold in significant volumes. Since this computing speed is inadequate to meet the demands of computational fluid dynamics, a special processor is required. Issues which are felt to be significant in the pursuit of maximum compute capability in this special processor are discussed.

Feierbach, G. F.↗

A New Look at NASA: Strategic Research In Information Technology

This viewgraph presentation provides information on research undertaken by NASA to facilitate the development of information technologies. Specific ideas covered here include: 1) Bio/nano technologies: biomolecular and nanoscale systems and tools for assembly and computing; 2) Evolvable hardware: autonomous self-improving, self-repairing hardware and software for survivable space systems in extreme environments; 3) High Confidence Software Technologies: formal methods, high-assurance software design, and program synthesis; 4) Intelligent Controls and Diagnostics: Next generation machine learning, adaptive control, and health management technologies; 5) Revolutionary computing: New computational models to increase capability and robustness to enable future NASA space missions.

Alfano, David↗

Computational and experimental investigation of subsonic internal reversing flows

The flow inside a model exhaust configuration was studied using both experimental and computational techniques. The hardware was tested at the NASA Lewis Research Center's Powered Lift Facility at tailpipe total pressure to ambient static pressure ratios ranging from 1.0 to 5.0. The flow simulations were obtained using the two 3-D Navier-Stokes CFD codes run on the Lewis Cray Y-MP computer. Both codes produced oscillatory solutions due to the inflow boundary condition reflecting acoustic waves. The CFD solutions correctly predicted the flow separation along the inside elbow of the takeoff and also along the walls of the ventral duct. Mass flow rates were overpredicted due to underprediction of the turbulent energy dissipation and subsequent total pressure loss.

Rhodes, James A.↗

Technical Challenges and Lessons from the Migration of the GLOBE Data and Information System to Utilize Cloud Computing Service

The Global Learning and Observation to Benefit the Environment (GLOBE) Data and Information System supports an international science and education program with capabilities to accept local environment observations, archive, display and visualize them along with global satellite observations. Since its inception twenty years ago, the Web and database system has been upgraded periodically to accommodate the changes in technology and the steady growth of GLOBEs education community and collection of observations. Recently, near the end-of-life of the system hardware, new commercial computer platform options were explored and a decision made to utilize Cloud services. Now the GLOBE DIS has been fully deployed and maintained using Amazon Cloud services for over two years now. This paper reviews the early risks, actual challenges, and some unexpected findings as a result of the GLOBE DIS migration. We describe the plans, cost drivers and estimates, highlight adjustments that were made and suggest improvements. We present the trade studies for provisioning, for load balancing, networks, processing, storage, as well as production, staging and backup systems. We outline the migration teams skills and required level of effort for transition, and resulting changes in the overall maintenance and operations activities. Examples include incremental adjustments to processing capacity and frequency of backups, and efforts previously expended on hardware maintenance that were refocused onto application-specific enhancements.

GLOBE↗

Technical Challenges and Lessons from the Migration of the GLOBE Data and Information System to Utilize Cloud Computing Service

The Global Learning and Observation to Benefit the Environment (GLOBE) Data and Information System supports an international science and education program with capabilities to accept local environment observations, archive, display and visualize them along with global satellite observations. Since its inception twenty years ago, the Web and database system has been upgraded periodically to accommodate the changes in technology and the steady growth of GLOBEs education community and collection of observations. Recently, near the end-of-life of the system hardware, new commercial computer platform options were explored and a decision made to utilize Cloud services. Now the GLOBE DIS has been fully deployed and maintained using Amazon Cloud services for over two years now. This paper reviews the early risks, actual challenges, and some unexpected findings as a result of the GLOBE DIS migration. We describe the plans, cost drivers and estimates, highlight adjustments that were made and suggest improvements. We present the trade studies for provisioning, for load balancing, networks, processing, storage, as well as production, staging and backup systems. We outline the migration teams skills and required level of effort for transition, and resulting changes in the overall maintenance and operations activities. Examples include incremental adjustments to processing capacity and frequency of backups, and efforts previously expended on hardware maintenance that were refocused onto application-specific enhancements.

GLOBE Data↗

NASA ERA Integrated CFD for Wind Tunnel Testing of Hybrid Wing-Body Configuration

The NASA Environmentally Responsible Aviation (ERA) Project explored enabling technologies to reduce impact of aviation on the environment. One project research challenge area was the study of advanced airframe and engine integration concepts to reduce community noise and fuel burn. To address this challenge, complex wind tunnel experiments at both the NASA Langley Research Center's (LaRC) 14'x22' and the Ames Research Center's 40'x80' low-speed wind tunnel facilities were conducted on a BOEING Hybrid Wing Body (HWB) configuration. These wind tunnel tests entailed various entries to evaluate the propulsion-airframe interference effects, including aerodynamic performance and aeroacoustics. In order to assist these tests in producing high quality data with minimal hardware interference, extensive Computational Fluid Dynamic (CFD) simulations were performed for everything from sting design and placement for both the wing body and powered ejector nacelle systems to the placement of aeroacoustic arrays to minimize its impact on vehicle aerodynamics. This paper presents a high-level summary of the CFD simulations that NASA performed in support of the model integration hardware design as well as the development of some CFD simulation guidelines based on post-test aerodynamic data. In addition, the paper includes details on how multiple CFD codes (OVERFLOW, STAR-CCM+, USM3D, and FUN3D) were efficiently used to provide timely insight into the wind tunnel experimental setup and execution.

Computational Fluid Dynamics↗

NASA ERA Integrated CFD for Wind Tunnel Testing of Hybrid Wing-Body Configuration

NASAs Environmentally Responsible Aviation (ERA) Project explores enabling technologies to reduce aviations impact on the environment. One research challenge area for the project has been to study advanced airframe and engine integration concepts to reduce community noise and fuel burn. In order to achieve this, complex wind tunnel experiments at both the NASA Langley Research Centers (LaRC) 14x22 and the Ames Research Centers 40x80 low-speed wind tunnel facilities were conducted on a Boeing Hybrid Wing Body (HWB) configuration. These wind tunnel tests entailed various entries to evaluate the propulsion airframe interference effects including aerodynamic performance and aeroacoustics. In order to assist these tests in producing high quality data with minimal hardware interference, extensive Computational Fluid Dynamic (CFD) simulations were performed for everything from sting design and placement for both the wing body and powered ejector nacelle systems to the placement of aeroacoustic arrays to minimize its impact on the vehicles aerodynamics. This paper will provide a high level summary of the CFD simulations that NASA performed in support of the model integration hardware design as well as some simulation guideline development based on post-test aerodynamic data. In addition, the paper includes details on how multiple CFD codes (OVERFLOW, STAR-CCM+, USM3D, and FUN3D) were efficiently used to provide timely insight into the wind tunnel experimental setup and execution.

Computational Fluid Dynamics↗

R-Hope: Development Approach to Extreme Non-volatile Memory Reuse Onboard the Curiosity Rover

The MSL Curiosity rover landed on Mars on August~5, 2012. Over time, one of its two computers experienced critical hardware memory failure. This non-volatile NAND flash memory held file system partitions and tunable parameters needed for running rover flight software. The project assembled a design and development team to re-purpose a NOR flash memory hardware chip, only 1.5\% of the size of the NAND, to hold the file systems and parameters. The usable NOR memory required major software changes to accommodate the new limitations of slower access speeds, vastly different physical layout, and smaller size. This presentation discusses the approach, challenges, and outcomes of restoring function to the computer so it can act as a ``lifeboat'' in event of problems with the primary computer.

Peper, Nick↗

Bringing wings of change - NASA's airfoil research program

A review is presented of progress in attaining technical objectives in three areas of semiautomatic airfoil development: software, hardware, and applications. Software objectives seek improved mathematical models and computer codes for flow analysis and design optimization for a variety of conditions. The 17-step iterative computer model used in designing the GA (W)-1 airfoil is effective but not yet fully automated; with present methods only single-point computer optimization is possible. Hardware objectives calling for improvement in test facilities and techniques are met in part by the introduction of the Langley (F-3C) wind tunnel for independent evaluation of transonic Mach number and Reynolds effects up to 12-16 million, and by a two-dimensional test section for the Langley 1/3 transonic cryogenic tunnel which will extend the Reynolds number to 50 million. The current status of low-speed, thin, and rotorcraft airfoil development programs is discussed.

Pierpont, P. K.↗

Advanced information processing system: Local system services

The Advanced Information Processing System (AIPS) is a multi-computer architecture composed of hardware and software building blocks that can be configured to meet a broad range of application requirements. The hardware building blocks are fault-tolerant, general-purpose computers, fault-and damage-tolerant networks (both computer and input/output), and interfaces between the networks and the computers. The software building blocks are the major software functions: local system services, input/output, system services, inter-computer system services, and the system manager. The foundation of the local system services is an operating system with the functions required for a traditional real-time multi-tasking computer, such as task scheduling, inter-task communication, memory management, interrupt handling, and time maintenance. Resting on this foundation are the redundancy management functions necessary in a redundant computer and the status reporting functions required for an operator interface. The functional requirements, functional design and detailed specifications for all the local system services are documented.

Burkhardt, Laura↗

Introduction to Quantum Computing

Quantum computing offers the potential to revolutionize high-performance computing by providing a means to solve certain computational problems asymptotically faster than any classical computer. Quantum computing has advanced recently from merely a theoretical possibility to engineered reality, including commercial entities offering early prototype quantum processors, both special-purpose quantum annealers and general-purpose gate-model processors. The media have been showcasing each new development and implicitly conveying the message that quantum-computing ubiquity is nigh. Here, we will respond to this hype and provide an overview of the exciting but still early state of the field. In this tutorial, we introduce participants to the computational models that give quantum computing its immense computational power. We examine the thought processes that programmers need to map problems to quantum computers. And we discuss hardware and algorithmic challenges that must be overcome before quantum computing becomes a component of every software developer's repertoire.

Quantum computing↗

Introduction to Quantum Computing

Quantum computing offers the potential to revolutionize high-performance computing by providing a means to solve certain computational problems asymptotically faster than any classical computer. Quantum computing has advanced recently from merely a theoretical possibility to engineered reality, including commercial entities offering early prototype quantum processors, both special-purpose quantum annealers and general-purpose gate-model processors. The media have been showcasing each new development and implicitly conveying the message that quantum-computing ubiquity is nigh. Here, we will respond to this hype and provide an overview of the exciting but still early state of the field. In this tutorial, we introduce participants to the computational models that give quantum computing its immense computational power. We examine the thought processes that programmers need to map problems to quantum computers. And we discuss hardware and algorithmic challenges that must be overcome before quantum computing becomes a component of every software developer's repertoire. (Update of 2022 slides)

Quantum computing↗

Transparent Ada rendezvous in a fault tolerant distributed system

There are many problems associated with distributing an Ada program over a loosely coupled communication network. Some of these problems involve the various aspects of the distributed rendezvous. The problems addressed involve supporting the delay statement in a selective call and supporting the else clause in a selective call. Most of these difficulties are compounded by the need for an efficient communication system. The difficulties are compounded even more by considering the possibility of hardware faults occurring while the program is running. With a hardware fault tolerant computer system, it is possible to design a distribution scheme and communication software which is efficient and allows Ada semantics to be preserved. An Ada design for the communications software of one such system will be presented, including a description of the services provided in the seven layers of an International Standards Organization (ISO) Open System Interconnect (OSI) model communications system. The system capabilities (hardware and software) that allow this communication system will also be described.

Racine, Roger↗

Sentinel

Network intrusion detection systems (NIDS) are commonplace in network security but they frequently employ algorithms that are computational demanding requiring hardware and software with significant power requirements. Two examples of such resource-intensive algorithms used for network security are regular expression matching and broader signature pattern matching which are commonly used in deep packet inspection (DPI). Network security algorithms that have large power requirements may be a challenge for low-power internet-of-things (IoT) environments, which generally lack the power resources to implement complex security measures like computationally expensive DPI at the edge. Furthermore, IoT environments incorporating 5G standalone networks have network latency constraints beyond just power that make DPI at the edge even more difficult. Programmable logic is ideally suited for machine learning inference for DPI because of its deep instruction level parallelism and single-cycle memory access. Machine learning approaches for DPI have been explored before using the programmable logic of field programmable gate arrays (FPGA) as a potential solution for NIDS approaches that would be power-suitable for IoT. However, those previous programmable logic NIDS approaches utilize either a supervised or unsupervised learning model. Sentinel utilizes the ensemble of these two machine learning approaches known as a semi-supervised approach which has shown promise in NIDS implementations. Sentinel provides a programmable logic implementation of a semi-supervised approach for DPI which operates at much lower power and latency than a GPU implementation with negligible loss of accuracy due to quantization through a logistic regressor.

Anderson, MatthewW [Idaho National Laboratory (INL↗

LuGo: An enhanced quantum phase estimation implementation

Quantum Phase Estimation (QPE) is a cardinal algorithm in quantum computing that plays a crucial role in various applications, including cryptography, molecular simulation, and solving systems of linear equations. However, the standard implementation of QPE faces challenges related to time complexity and circuit depth, which limit its practicality for large-scale computations. We introduce LuGo, a novel framework designed to enhance the performance of QPE by reducing circuit duplication, as well as using parallelization techniques to achieve faster generation of the QPE circuit and gate reduction. We validate the effectiveness of our framework by generating quantum linear solver circuits, which require both QPE and inverse QPE, to solve linear systems of equations. LuGo achieves significant improvements in both computational efficiency and hardware requirements without compromising on accuracy. Compared to a standard QPE implementation, LuGo reduces time consumption to generate a circuit that solves a 2 6 × 2 6 system matrix by a factor of 50.68 and over 31× reduction of quantum gates and circuit depth, with no fidelity loss on an ideal quantum simulator. Furthermore, we demonstrated the versatility and scalability of LuGo enabled HHL algorithm by simulating a canonical Hele-Shaw fluid problem using a quantum simulator. With these advantages, LuGo paves the way for more efficient implementations of QPE, enabling broader applications across several quantum computing domains.

Quantum algorithm↗