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At least 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

GSFC Technology Development Center Report

This report summarizes the activities of the GSFC Technology Development Center for 2003. The report forecasts activities planned for the year 2004. The GSFC Technology Development Center (TDC) develops station software including the Field System (FS), scheduling software (SKED), hardware including tools for station timing and meteorology, scheduling algorithms, operational procedures, and provides a pool of individuals to assist with station implementation, check-out, upgrades, and training.

Himwich, Ed↗
NASA NTRS2007

Advanced Reference Counting Pointers for Better Performance

A computer program implements reference counting pointers (RCPs) that are lock-free, thread-safe, async-safe, and operational on a multiprocessor computer. RCPs are powerful and convenient means of managing heap memory in C++ software. Most prior RCP programs use locks to ensure thread safety and manage concurrency. The present program was developed in a continuing effort to explore ways of using the C++ programming language to develop safety-critical and mission- critical software. This effort includes exploration of lock-free algorithms because they offer potential to avoid some costly and difficult verification problems. Unlike previously published RCP software, the present program does not use locks (meaning that no thread can block progress on another thread): Instead, this program implements algorithms that exploit capabilities of central-processing- unit hardware so as to avoid locks. Once locks are eliminated, it becomes possible to realize the other attributes mentioned in the first sentence. In addition to the abovementioned attributes, this program offers several advantages over other RCP programs that use locks: It is smaller (and, hence, is faster and uses less memory), it is immune to priority inversion, and there is no way for it to cause a C++ exception.

Reinholtz, William↗
NASA NTRS2013

GSFC Technology Development Center Report

This report summarizes the activities of the GSFC Technology Development Center (TDC) for 2012 and forecasts planned activities for 2013. The GSFC TDC develops station software including the Field System (FS), scheduling software (SKED), hardware including tools for station timing and meteorology, scheduling algorithms, and operational procedures. It provides a pool of individuals to assist with station implementation, check-out, upgrades, and training.

Himwich, Ed↗
NASA NTRS2019

Quantum Gate-Model Approaches to Exact and Approximate Optimization

Many of the most challenging computational problems arising in practical applications are tackled by heuristic algorithms which have not been rigorously proven to outperform other approaches but rather have been empirically demonstrated to be effective. While quantum heuristics have been proposed since the early days of quantum computing, true empirical evaluation of the real-world performance of these algorithms is only becoming possible now as increasingly powerful quantum gate-model devices continue to come online.In this talk, I will give an overview of the NASA QuAIL team's ongoing investigation into quantum gate-model heuristic algorithms for exact and approximate optimization. In particular, we consider the performance of the Quantum Approximate Optimization Algorithm on NP-hard optimization problems, and describe algorithm parameter setting strategies for real-world quantum hardware. We then show a generalization of QAOA circuits, the Quantum Alternating Operator Ansatz, especially suitable for low-resource implementations of QAOA for problems with hard (feasibility) constraints. The talk will conclude with a discussion of research challenges, particularly for optimization and sampling applications of QAOA, and the potential of more general quantum heuristics to give advantages over classical computers.

Hadfield, Stuart↗
DOE OSTI2025

Generic Discretization Library

The GenDiL library is a collection of C++ software abstractions designed to discretize and solve partial differential equations (PDEs) for high-performance computing (HPC) applications. Its primary focus is on modern C++ generic programming, which helps ensure portability across various hardware architectures. The central idea behind the library is to provide building blocks for numerical algorithms-such as discretization methods and iteration patterns-so that domain experts can focus on the math, rather than the low-level details of hardware or implementation. By defining abstractions for data types, iteration over computational grids, and scheduling of operations, the library isolates the high-level PDE algorithms from the platform-specific optimizations needed to achieve efficient performance.

Dudouit, Yohann [Lawrence Livermore National Labor↗
NASA NTRS2010

Advanced Wavefront Sensing and Control Testbed (AWCT)

The Advanced Wavefront Sensing and Control Testbed (AWCT) is built as a versatile facility for developing and demonstrating, in hardware, the future technologies of wave front sensing and control algorithms for active optical systems. The testbed includes a source projector for a broadband point-source and a suite of extended scene targets, a dispersed fringe sensor, a Shack-Hartmann camera, and an imaging camera capable of phase retrieval wavefront sensing. The testbed also provides two easily accessible conjugated pupil planes which can accommodate the active optical devices such as fast steering mirror, deformable mirror, and segmented mirrors. In this paper, we describe the testbed optical design, testbed configurations and capabilities, as well as the initial results from the testbed hardware integrations and tests.

active optics↗
NASA NTRS1993

Cooperative GN&C development in a rapid prototyping environment

The Navigation, Control and Aeronautics Division (NCAD) at NASA-JSC is exploring ways of producing Guidance, Navigation and Control (GN&C) flight software faster, better, and cheaper. To achieve these goals NCAD established two hardware/software facilities that take an avionics design project from initial inception through high fidelity real-time hardware-in-the-loop testing. Commercially available software products are used to develop the GN&C algorithms in block diagram form and then automatically generate source code from these diagrams. A high fidelity real-time hardware-in-the-loop laboratory provides users with the capability to analyze mass memory usage within the targeted flight computer, verify hardware interfaces, conduct system level verification, performance, acceptance testing, as well as mission verification using reconfigurable and mission unique data. To evaluate these concepts and tools, NCAD embarked on a project to build a real-time 6 DOF simulation of the Soyuz Assured Crew Return Vehicle flight software. To date, a productivity increase of 185 percent has been seen over traditional NASA methods for developing flight software.

Bordano, Aldo↗
NASA NTRS2014

Dynamically Reconfigurable Systolic Array Accelorators

A polymorphic systolic array framework that works in conjunction with an embedded microprocessor on an FPGA, that allows for dynamic and complimentary scaling of acceleration levels of two algorithms active concurrently on the FPGA. Use is made of systolic arrays and hardware-software co-design to obtain an efficient multi-application acceleration system. The flexible and simple framework allows hosting of a broader range of algorithms and extendable to more complex applications in the area of aerospace embedded systems.

Dasu, Aravind↗
NASA NTRS1972

Simulation results for the Viterbi decoding algorithm

Concepts involved in determining the performance of coded digital communications systems are introduced. The basic concepts of convolutional encoding and decoding are summarized, and hardware implementations of sequential and maximum likelihood decoders are described briefly. Results of parametric studies of the Viterbi decoding algorithm are summarized. Bit error probability is chosen as the measure of performance and is calculated, by using digital computer simulations, for various encoder and decoder parameters. Results are presented for code rates of one-half and one-third, for constraint lengths of 4 to 8, for both hard-decision and soft-decision bit detectors, and for several important systematic and nonsystematic codes. The effect of decoder block length on bit error rate also is considered, so that a more complete estimate of the relationship between performance and decoder complexity can be made.

Batson, B. H.↗
NASA NTRS1992

System for Anomaly and Failure Detection (SAFD) system development

This task specified developing the hardware and software necessary to implement the System for Anomaly and Failure Detection (SAFD) algorithm, developed under Technology Test Bed (TTB) Task 21, on the TTB engine stand. This effort involved building two units; one unit to be installed in the Block II Space Shuttle Main Engine (SSME) Hardware Simulation Lab (HSL) at Marshall Space Flight Center (MSFC), and one unit to be installed at the TTB engine stand. Rocketdyne personnel from the HSL performed the task. The SAFD algorithm was developed as an improvement over the current redline system used in the Space Shuttle Main Engine Controller (SSMEC). Simulation tests and execution against previous hot fire tests demonstrated that the SAFD algorithm can detect engine failure as much as tens of seconds before the redline system recognized the failure. Although the current algorithm only operates during steady state conditions (engine not throttling), work is underway to expand the algorithm to work during transient condition.

Oreilly, D.↗
DOE OSTI2025

Quantum Simulation of Molecular Dynamics Processes─A Benchmark Study Using a Classical Simulator and Present-Day Quantum Hardware

Here, we explore how the fundamental problems in quantum molecular dynamics can be modeled using classical simulators (emulators) of quantum computers and the actual quantum hardware available to us today. The list of problems we tackle includes propagation of a free wave packet, vibration of a harmonic oscillator, and tunneling through a barrier. Each of these problems starts with the initial wave packet setup. Although Qiskit provides a general method for initializing wave functions, in most cases it generates deep quantum circuits. While these circuits perform well on noiseless simulators, they suffer from excessive noise on quantum hardware. To overcome this issue, we designed a shallower quantum circuit for preparing a Gaussian-like initial wave packet, which improves the performance of real hardware. Next, quantum circuits are implemented to apply the kinetic and potential energy operators for the evolution of a wave function over time. The results of our modeling on classical emulators of quantum hardware agree perfectly with the results obtained using the traditional (classical) methods. This serves as a benchmark and demonstrates that the quantum algorithms and Qiskit codes we developed are accurate. However, the results obtained on the actual quantum hardware available today, such as IBM’s superconducting qubits and IonQ’s trapped ions, indicate large discrepancies due to hardware limitations. This work highlights both the potential and challenges of using quantum computers to solve fundamental quantum molecular dynamics problems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1991

Accuracy and speed in computing the Chebyshev collocation derivative

We studied several algorithms for computing the Chebyshev spectral derivative and compare their roundoff error. For a large number of collocation points, the elements of the Chebyshev differentiation matrix, if constructed in the usual way, are not computed accurately. A subtle cause is is found to account for the poor accuracy when computing the derivative by the matrix-vector multiplication method. Methods for accurately computing the elements of the matrix are presented, and we find that if the entities of the matrix are computed accurately, the roundoff error of the matrix-vector multiplication is as small as that of the transform-recursion algorithm. Results of CPU time usage are shown for several different algorithms for computing the derivative by the Chebyshev collocation method for a wide variety of two-dimensional grid sizes on both an IBM and a Cray 2 computer. We found that which algorithm is fastest on a particular machine depends not only on the grid size, but also on small details of the computer hardware as well. For most practical grid sizes used in computation, the even-odd decomposition algorithm is found to be faster than the transform-recursion method.

Don, Wai-Sun↗
NASA NTRS2009

Hardware Implementation of Lossless Adaptive and Scalable Hyperspectral Data Compression for Space

On-board lossless hyperspectral data compression reduces data volume in order to meet NASA and DoD limited downlink capabilities. The technique also improves signature extraction, object recognition and feature classification capabilities by providing exact reconstructed data on constrained downlink resources. At JPL a novel, adaptive and predictive technique for lossless compression of hyperspectral data was recently developed. This technique uses an adaptive filtering method and achieves a combination of low complexity and compression effectiveness that far exceeds state-of-the-art techniques currently in use. The JPL-developed 'Fast Lossless' algorithm requires no training data or other specific information about the nature of the spectral bands for a fixed instrument dynamic range. It is of low computational complexity and thus well-suited for implementation in hardware. A modified form of the algorithm that is better suited for data from pushbroom instruments is generally appropriate for flight implementation. A scalable field programmable gate array (FPGA) hardware implementation was developed. The FPGA implementation achieves a throughput performance of 58 Msamples/sec, which can be increased to over 100 Msamples/sec in a parallel implementation that uses twice the hardware resources This paper describes the hardware implementation of the 'Modified Fast Lossless' compression algorithm on an FPGA. The FPGA implementation targets the current state-of-the-art FPGAs (Xilinx Virtex IV and V families) and compresses one sample every clock cycle to provide a fast and practical real-time solution for space applications.

FPGA implementation↗
DOE OSTI2020

Decomposition Algorithms for Solving NP-hard Problems on a Quantum Annealer

NP-hard problems such as the maximum clique or minimum vertex cover problems, two of Karp’s 21 NP-hard problems, have several applications in computational chemistry, biochemistry and computer network security. Adiabatic quantum annealers can search for the optimum value of such NP-hard optimization problems, given the problem can be embedded on their hardware. However, this is often not possible due to certain limitations of the hardware connectivity structure of the annealer. This paper studies a general framework for a decomposition algorithm for NP-hard graph problems aiming to identify an optimal set of vertices. Our generic algorithm allows us to recursively divide an instance until the generated subproblems can be embedded on the quantum annealer hardware and subsequently solved. Furthermore, the framework is applied to the maximum clique and minimum vertex cover problems, and we propose several pruning and reduction techniques to speed up the recursive decomposition. The performance of both algorithms is assessed in a detailed simulation study.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1987

Evaluation of on-line pulse control for vibration suppression in flexible spacecraft

A numerical simulation was performed, by means of a large-scale finite element code capable of handling large deformations and/or nonlinear behavior, to investigate the suitability of the nonlinear pulse-control algorithm to suppress the vibrations induced in the Spacecraft Control Laboratory Experiment (SCOLE) components under realistic maneuvers. Among the topics investigated were the effects of various control parameters on the efficiency and robustness of the vibration control algorithm. Advanced nonlinear control techniques were applied to an idealized model of some of the SCOLE components to develop an efficient algorithm to determine the optimal locations of point actuators, considering the hardware on the SCOLE project as distributed in nature. The control was obtained from a quadratic optimization criterion, given in terms of the state variables of the distributed system. An experimental investigation was performed on a model flexible structure resembling the essential features of the SCOLE components, and electrodynamic and electrohydraulic actuators were used to investigate the applicability of the control algorithm with such devices in addition to mass-ejection pulse generators using compressed air.

Masri, Sami F.↗
NASA NTRS2003

Software for Simulating a Complex Robot

RoboSim (Robot Simulation) is a computer program that simulates the poses and motions of the Robonaut a developmental anthropomorphic robot that has a complex system of joints with 43 degrees of freedom and multiple modes of operation and control. RoboSim performs a full kinematic simulation of all degrees of freedom. It also includes interface components that duplicate the functionality of the real Robonaut interface with control software and human operators. Basically, users see no difference between the real Robonaut and the simulation. Consequently, new control algorithms can be tested by computational simulation, without risk to the Robonaut hardware, and without using excessive Robonaut-hardware experimental time, which is always at a premium. Previously developed software incorporated into RoboSim includes Enigma (for graphical displays), OSCAR (for kinematical computations), and NDDS (for communication between the Robonaut and external software). In addition, RoboSim incorporates unique inverse-kinematical algorithms for chains of joints that have fewer than six degrees of freedom (e.g., finger joints). In comparison with the algorithms of OSCAR, these algorithms are more readily adaptable and provide better results when using equivalent sets of data.

Goza, S. Michael↗
DOE OSTI2022

From fault-detection to automated fault correction: A field study

A fault detection and diagnostics (FDD) tool, as addressed by this study, is a tool that continuously identifies the presence of faults and efficiency improvement opportunities through a one-way interface to the building automation system and the application of automated analytics. Although FDD tools can inform operators of building operational faults, currently an action is always required to correct the faults to generate energy savings. Fault auto-correction integrating with commercial FDD technology offerings can close the loop between the passive diagnostics and active control, increase the savings generated by FDD tools, and reduce the reliance on human intervention. This paper presents the field study of seven fault auto-correction algorithms implemented in commercial FDD platforms. Implementation includes software changes in the FDD tools and additional controls hardware or software changes in the BAS that were required to enable the execution of different types of auto-correction algorithms in real buildings. The routines successfully and automatically correct faults and improve the operation of large built-up Heating, Ventilation, and Air Conditioning (HVAC) systems, common in most commercial buildings. The auto-correction algorithms are tested across four buildings and three different building automation systems, following a rigorous procedure to make sure they work properly and do not negatively impact the system and building occupants. Finally, technology benefits, market drivers, and scalability changes are drawn from the implementation effort and test results, to drive future research and industry engagement.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Compute-Efficient Deep Learning: Algorithmic Trends and Opportunities

Although deep learning has made great progress in recent years, the exploding economic and environmental costs of training neural networks are becoming unsustainable. To address this problem, there has been a great deal of research on algorithmically-efficient deep learning, which seeks to reduce training costs not at the hardware or implementation level, but through changes in the semantics of the training program. In this paper, we present a structured and comprehensive overview of the research in this field. First, we formalize the algorithmic speedup problem, then we use fundamental building blocks of algorithmically efficient training to develop a taxonomy. Our taxonomy highlights commonalities of seemingly disparate methods and reveals current research gaps. Next, we present evaluation best practices to enable comprehensive, fair, and reliable comparisons of speedup techniques. To further aid research and applications, we discuss common bottlenecks in the training pipeline (illustrated via experiments) and offer taxonomic mitigation strategies for them. Finally, we highlight some unsolved research challenges and present promising future directions.

97 MATHEMATICS AND COMPUTING↗