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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Trigonometric continuous-variable gates and hybrid quantum simulations of the sine-Gordon model

Hybrid qubit-qumode quantum computing platforms provide a natural setting for simulating interacting bosonic quantum field theories. However, existing continuous-variable gate constructions rely predominantly on polynomial functions of canonical quadratures. In this work, we introduce a complementary universality paradigm based on trigonometric continuous-variable gates, which enable a Fourier-like representation of bosonic operators and are particularly well suited for periodic and non-perturbative interactions. We present an ancilla-based framework for implementing trigonometric gates with arguments given by arbitrary Hermitian functions of qumode quadratures. The protocol yields unitary gates deterministically, and non-unitary gates through probabilistic post-selection. As a concrete application, we develop a hybrid qubit-qumode quantum simulation of the lattice sine-Gordon model. Using these gates, we prepare ground states via quantum imaginary-time evolution, simulate real-time dynamics, compute time-dependent vertex two-point correlation functions, and extract quantum kink profiles under topological boundary conditions. Our results demonstrate that trigonometric continuous-variable gates provide a physically natural framework for simulating interacting field theories on near-term hybrid quantum hardware, while establishing a parallel route to universality beyond polynomial gate constructions. We expect that the trigonometric gates introduced here to find broader applications, including quantum simulations of condensed matter systems, quantum chemistry, and biological models.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

On fast simulation of dynamical system with neural vector enhanced numerical solver

The large-scale simulation of dynamical systems is critical in numerous scientific and engineering disciplines. However, traditional numerical solvers are limited by the choice of step sizes when estimating integration, resulting in a trade-off between accuracy and computational efficiency. To address this challenge, we introduce a deep learning-based corrector called Neural Vector (NeurVec), which can compensate for integration errors and enable larger time step sizes in simulations. Our extensive experiments on a variety of complex dynamical system benchmarks demonstrate that NeurVec exhibits remarkable generalization capability on a continuous phase space, even when trained using limited and discrete data. NeurVec significantly accelerates traditional solvers, achieving speeds tens to hundreds of times faster while maintaining high levels of accuracy and stability. Moreover, NeurVec’s simple-yet-effective design, combined with its ease of implementation, has the potential to establish a new paradigm for fast-solving differential equations based on deep learning.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1994

A software architecture for multidisciplinary applications: Integrating task and data parallelism

Data parallel languages such as Vienna Fortran and HPF can be successfully applied to a wide range of numerical applications. However, many advanced scientific and engineering applications are of a multidisciplinary and heterogeneous nature and thus do not fit well into the data parallel paradigm. In this paper we present new Fortran 90 language extensions to fill this gap. Tasks can be spawned as asynchronous activities in a homogeneous or heterogeneous computing environment; they interact by sharing access to Shared Data Abstractions (SDA's). SDA's are an extension of Fortran 90 modules, representing a pool of common data, together with a set of Methods for controlled access to these data and a mechanism for providing persistent storage. Our language supports the integration of data and task parallelism as well as nested task parallelism and thus can be used to express multidisciplinary applications in a natural and efficient way.

Chapman, Barbara↗
DOE OSTI2024

Toward digital design at the exascale: An overview of project ICECap

High performance computing has entered the Exascale Age. Capable of performing over 1018 floating point operations per second, exascale computers, such as El Capitan, the National Nuclear Security Administration's first, have the potential to revolutionize the detailed in-depth study of highly complex science and engineering systems. However, in addition to these kind of whole machine “hero” simulations, exascale systems could also enable new paradigms in digital design by making petascale hero runs routine. Currently, untenable problems in complex system design, optimization, model exploration, and scientific discovery could all become possible. Motivated by the challenge of uncovering the next generation of robust high-yield inertial confinement fusion (ICF) designs, project ICECap (Inertial Confinement on El Capitan) attempts to integrate multiple advances in machine learning (ML), scientific workflows, high performance computing, GPU-acceleration, and numerical optimization to prototype such a future. Built on a general framework, ICECap is exploring how these technologies could broadly accelerate scientific discovery on El Capitan. In addition to our requirements, system-level design, and challenges, we describe some of the key technologies in ICECap, including ML replacements for multiphysics packages, tools for human-machine teaming, and algorithms for multifidelity design optimization under uncertainty. As a test of our prototype pre-El Capitan system, we advance the state-of-the art for ICF hohlraum design by demonstrating the optimization of a 17-parameter National Ignition Facility experiment and show that our ML-assisted workflow makes design choices that are consistent with physics intuition, but in an automated, efficient, and mathematically rigorous fashion.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Understanding the metal-to-insulator transition in La1−xSrxCoO3−δ and its applications for neuromorphic computing

Abstract Transition metal oxides that exhibit a metal-to-insulator transition (MIT) as a function of oxygen vacancy concentration are promising systems to realize energy-efficient platforms for neuromorphic computing. However, the current lack of understanding of the microscopic mechanism driving the MIT hinders the realization of effective and stable devices. Here we investigate defective cobaltites and we unravel the structural, electronic, and magnetic changes responsible for the MIT when oxygen vacancies are introduced in the material. We show that, contrary to accepted views, cooperative structural distortions instead of local bonding changes are responsible for the MIT, and we describe the subtle interdependence of structural and magnetic transitions. Finally, we present a model, based on first principles, to predict the required electric bias to drive the transition, showing good agreement with available measurements and providing a paradigm to establish design rules for low-energy cost devices.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Lie–Poisson Neural Networks (LPNets): Data-based computing of Hamiltonian systems with symmetries

An accurate data-based prediction of the long-term evolution of Hamiltonian systems requires a network that preserves the appropriate structure under each time step. Every Hamiltonian system contains two essential ingredients: the Poisson bracket and the Hamiltonian. Hamiltonian systems with symmetries, whose paradigm examples are the Lie–Poisson systems, have been shown to describe a broad category of physical phenomena, from satellite motion to underwater vehicles, fluids, geophysical applications, complex fluids, and plasma physics. The Poisson bracket in these systems comes from the symmetries, while the Hamiltonian comes from the underlying physics. We view the symmetry of the system as primary, hence the Lie–Poisson bracket is known exactly, whereas the Hamiltonian is regarded as coming from physics and is considered not known, or known approximately. Using this approach, we develop a network based on transformations that exactly preserve the Poisson bracket and the special functions of the Lie–Poisson systems (Casimirs) to machine precision. We present two flavors of such systems: one, where the parameters of transformations are computed from data using a dense neural network (LPNets), and another, where the composition of transformations is used as building blocks (G-LPNets). We also show how to adapt these methods to a larger class of Poisson brackets. We apply the resulting methods to several examples, such as rigid body (satellite) motion, underwater vehicles, a particle in a magnetic field, and others. The methods developed in this paper are important for the construction of accurate data-based methods for simulating the long-term dynamics of physical systems.

Data-based modeling↗
DOE OSTI2024

Assessment of Machine Learning Wall Modeling Approaches for Large Eddy Simulation of Gas Turbine Film Cooling Flows: An a Priori Study

Here, in this work, a priori analysis of machine learning (ML) strategies is carried out with the goal of data-driven wall modeling for large eddy simulation (LES) of gas turbine film cooling flows. High-fidelity flow datasets are extracted from wall-resolved LES (WRLES) of flow over a flat plate interacting with the coolant flow supplied by a single row of 7-7-7 shaped cooling holes inclined at 30 degrees with the flat plate at different blowing ratios (BR). The WRLES are performed using the high-order Nek5000 spectral element computational fluid dynamics (CFD) solver. Light gradient boosting machine (LightGBM) is employed as the ML algorithm for the data-driven wall model. Parametric tests are conducted to systematically assess the influence of a wide range of input flow features (velocity components, velocity gradients, pressure gradients, and fluid properties) on the accuracy of ML wall model with respect to prediction of wall shear stress. In addition, the use of spatial stencil and time delay is also explored within the ML wall modeling framework. It is shown that features associated with gradients of the streamwise and spanwise velocity components have a major impact on the prediction fidelity of wall model, while the effect of gradients of wall-normal velocity component is found to be negligible. Moreover, adding flow feature information from an x-y-z spatial stencil significantly improves the ML model accuracy and generalizability compared to just using local flow features from the matching location. Overall, highest prediction accuracy is achieved when both spatial stencil and time delay features are incorporated within the data-driven wall modeling paradigm.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1994

A software tool for dataflow graph scheduling

A graph-theoretic design process and software tool is presented for selecting a multiprocessing scheduling solution for a class of computational problems. The problems of interest are those that can be described using a dataflow graph and are intended to be executed repetitively on multiple processors. The dataflow paradigm is very useful in exposing the parallelism inherent in algorithms. It provides a graphical and mathematical model which describes a partial ordering of algorithm tasks based on data precedence.

Jones, Robert L., III↗
NASA NTRS1999

NASA/NOAA: Earth Science Electronic Theater 1999

The Electronic Theater (E-theater) presents visualizations which span the period from the original Suomi/Hasler animations of the first ATS-1 GEO weather satellite images in 1966 to the latest 1999 NASA Earth Science Vision for the next 25 years. Hot off the SGI-Onyx Graphics-Supercomputer are NASA's visualizations of Hurricanes Mitch, Georges, Fran and Linda. These storms have been recently featured on the covers of National Geographic, Time, Newsweek and Popular Science. Highlights will be shown from the NASA hurricane visualization resource video tape that has been used repeatedly this season on National and International network TV. Results will be presented from a new paper on automatic wind measurements in Hurricane Luis from 1-min GOES images that appeared in the November BAMS. The visualizations are produced by the NASA Goddard Visualization and Analysis Laboratory (VAL/912), and Scientific Visualization Studio (SVS/930), as well as other Goddard and NASA groups using NASA, NOAA, ESA, and NASDA Earth science datasets. Visualizations will be shown from the Earth Science E-Theater 1999 recently presented in Tokyo, Paris, Munich, Sydney, Melbourne, Honolulu, Washington, New York, and Dallas. The presentation Jan 11-14 at the AMS meeting in Dallas used a 4-CPU SGI/CRAY Onyx Infinite Reality Super Graphics Workstation with 8 GB RAM and a Terabyte Disk at 3840 X 1024 resolution with triple synchronized BarcoReality 9200 projectors on a 60ft wide screen. Visualizations will also be featured from the new Earth Today Exhibit which was opened by Vice President Gore on July 2, 1998 at the Smithsonian Air & Space museum in Washington, as well as those presented for possible use at the American Museum of Natural History (NYC), Disney EPCOT, and other venues. New methods are demonstrated for visualizing, interpreting, comparing, organizing and analyzing immense HyperImage remote sensing datasets and three dimensional numerical model results. We call the data from many new Earth sensing satellites, HyperImage datasets, because they have such high resolution in the spectral, temporal, spatial, and dynamic range domains. The traditional numerical spreadsheet paradigm has been extended to develop a scientific visualization approach for processing HyperImage datasets and 3D model results interactively. The advantages of extending the powerful spreadsheet style of computation to multiple sets of images and organizing image processing were demonstrated using the Distributed image SpreadSheet (DISS). The DISS is being used as a high performance testbed Next Generation Internet (NGI) VisAnalysis of: 1) El Nino SSTs and NDVI response 2) Latest GOES 10 5-min rapid Scans of 26 day 5000 frame movie of March & April '98 weather and tornadic storms 3) TRMM rainfall and lightning 4)GOES 9 satellite images/winds and NOAA aircraft radar of hurricane Luis, 5) lightning detector data merged with GOES image sequences, 6) Japanese GMS, TRMM, & ADEOS data 7) Chinese FY2 data 8) Meteosat & ERS/ATSR data 9) synchronized manipulation of multiple 3D numerical model views; and others will be illustrated. The Image SpreadSheet has been highly successful in producing Earth science visualizations for public outreach. Many of these visualizations have been widely disseminated through the world wide web pages of the HPCC/LTP/RSD program which can be found at http://rsd.gsfc.nasa.gov/rsd The one min interval animations of Hurricane Luis on ABC Nightline and the color perspective rendering of Hurricane Fran published by TIME, LIFE, Newsweek, Popular Science, National Geographic, Scientific American, and the "Weekly Reader" are some of the examples which will be shown.

Hasler, A. Fritz↗
NASA NTRS1999

NASA/NOAA: Earth Science Electronic Theater 1999. Earth Science Observations, Analysis and Visualization: Roots in the 60s - Vision for the Next Millennium

The Etheater presents visualizations which span the period from the original Suomi/Hasler animations of the first ATS-1 GEO weather satellite images in 1966, to the latest 1999 NASA Earth Science Vision for the next 25 years. Hot off the SGI-Onyx Graphics-Supercomputer are NASA''s visualizations of Hurricanes Mitch, Georges, Fran and Linda. These storms have been recently featured on the covers of National Geographic, Time, Newsweek and Popular Science. Highlights will be shown from the NASA hurricane visualization resource video tape that has been used repeatedly this season on National and International network TV. Results will be presented from a new paper on automatic wind measurements in Hurricane Luis from 1-min GOES images that appeared in the November BAMS. The visualizations are produced by the NASA Goddard Visualization & Analysis Laboratory, and Scientific Visualization Studio, as well as other Goddard and NASA groups using NASA, NOAA, ESA, and NASDA Earth science datasets. Visualizations will be shown from the Earth Science ETheater 1999 recently presented in Tokyo, Paris, Munich, Sydney, Melbourne, Honolulu, Washington, New York, and Dallas. The presentation Jan 11-14 at the AMS meeting in Dallas used a 4-CPU SGI/CRAY Onyx Infinite Reality Super Graphics Workstation with 8 GB RAM and a Terabyte Disk at 3840 X 1024 resolution with triple synchronized BarcoReality 9200 projectors on a 60ft wide screen. Visualizations will also be featured from the new Earth Today Exhibit which was opened by Vice President Gore on July 2, 1998 at the Smithsonian Air & Space Museum in Washington, as well as those presented for possible use at the American Museum of Natural History (NYC), Disney EPCOT, and other venues. New methods are demonstrated for visualizing, interpreting, comparing, organizing and analyzing immense HyperImage remote sensing datasets and three dimensional numerical model results. We call the data from many new Earth sensing satellites, HyperImage datasets, because they have such high resolution in the spectral, temporal, spatial, and dynamic range domains. The traditional numerical spreadsheet paradigm has been extended to develop a scientific visualization approach for processing HyperImage datasets and 3D model results interactively. The advantages of extending the powerful spreadsheet style of computation to multiple sets of images and organizing image processing were demonstrated using the Distributed Image SpreadSheet (DISS). The DISS is being used as a high performance testbed Next Generation Internet (NGI) VisAnalysis of: 1) El Nino SSTs and NDVI response 2) Latest GOES 10 5-min rapid Scans of 26 day 5000 frame movie of March & April 198 weather and tornadic storms 3) TRMM rainfall and lightning 4)GOES 9 satellite images/winds and NOAA aircraft radar of hurricane Luis, 5) lightning detector data merged with GOES image sequences, 6) Japanese GMS, TRMM, & ADEOS data 7) Chinese FY2 data 8) Meteosat & ERS/ATSR data 9) synchronized manipulation of multiple 3D numerical model views; etc. will be illustrated. The Image SpreadSheet has been highly successful in producing Earth science visualizations for public outreach.

Hasler, A. Fritz↗
NASA NTRS1998

Earth Science Multimedia Theater

The presentation will begin with the latest 1998 NASA Earth Science Vision for the next 25 years. A compilation of the 10 days of animations of Hurricane Georges which were supplied daily on NASA to Network television will be shown. NASA's visualizations of Hurricane Bonnie which appeared in the Sept 7 1998 issue of TIME magazine. Highlights will be shown from the NASA hurricane visualization resource video tape that has been used repeatedly this season on network TV. Results will be presented from a new paper on automatic wind measurements in Hurricane Luis from 1 -min GOES images that will appear in the October BAMS. The visualizations are produced by the Goddard Visualization & Analysis Laboratory, and Scientific Visualization Studio, as well as other Goddard and NASA groups using NASA, NOAA, ESA, and NASDA Earth science datasets. Visualizations will be shown from the "Digital-HyperRes-Panorama" Earth Science ETheater'98 recently presented in Tokyo, Paris and Phoenix. The presentation in Paris used a SGI/CRAY Onyx Infinite Reality Super Graphics Workstation at 2560 X 1024 resolution with dual synchronized video Epson 71 00 projectors on a 20ft wide screen. Earth Science Electronic Theater '999 is being prepared for a December 1 st showing at NASA HQ in Washington and January presentation at the AMS meetings in Dallas. The 1999 version of the Etheater will be triple wide with at resolution of 3840 X 1024 on a 60 ft wide screen. Visualizations will also be featured from the new Earth Today Exhibit which was opened by Vice President Gore on July 2, 1998 at the Smithsonian Air & Space Museum in Washington, as well as those presented for possible use at the American Museum of Natural History (NYC), Disney EPCOT, and other venues. New methods are demonstrated for visualizing, interpreting, comparing, organizing and analyzing immense Hyperimage remote sensing datasets and three dimensional numerical model results. We call the data from many new Earth sensing satellites, Hyperimage datasets, because they have such high resolution in the spectral, temporal, spatial, and dynamic range domains. The traditional numerical spreadsheet paradigm has been extended to develop a scientific visualization approach for processing Hyperimage datasets and 3D model results interactively. The advantages of extending the powerful spreadsheet style of computation to multiple sets of images and organizing image processing were demonstrated using the Distributed Image SpreadSheet (DISS).

Hasler, A. F.↗
NASA NTRS2003

Generic Divide and Conquer Internet-Based Computing

The growth of Internet-based applications and the proliferation of networking technologies have been transforming traditional commercial application areas as well as computer and computational sciences and engineering. This growth stimulates the exploration of Peer to Peer (P2P) software technologies that can open new research and application opportunities not only for the commercial world, but also for the scientific and high-performance computing applications community. The general goal of this project is to achieve better understanding of the transition to Internet-based high-performance computing and to develop solutions for some of the technical challenges of this transition. In particular, we are interested in creating long-term motivation for end users to provide their idle processor time to support computationally intensive tasks. We believe that a practical P2P architecture should provide useful service to both clients with high-performance computing needs and contributors of lower-end computing resources. To achieve this, we are designing dual -service architecture for P2P high-performance divide-and conquer computing; we are also experimenting with a prototype implementation. Our proposed architecture incorporates a master server, utilizes dual satellite servers, and operates on the Internet in a dynamically changing large configuration of lower-end nodes provided by volunteer contributors. A dual satellite server comprises a high-performance computing engine and a lower-end contributor service engine. The computing engine provides generic support for divide and conquer computations. The service engine is intended to provide free useful HTTP-based services to contributors of lower-end computing resources. Our proposed architecture is complementary to and accessible from computational grids, such as Globus, Legion, and Condor. Grids provide remote access to existing higher-end computing resources; in contrast, our goal is to utilize idle processor time of lower-end Internet nodes. Our project is focused on a generic divide and conquer paradigm and on mobile applications of this paradigm that can operate on a loose and ever changing pool of lower-end Internet nodes.

Follen, Gregory J.↗
NASA NTRS2011

Accelerated Adaptive MGS Phase Retrieval

The Modified Gerchberg-Saxton (MGS) algorithm is an image-based wavefront-sensing method that can turn any science instrument focal plane into a wavefront sensor. MGS characterizes optical systems by estimating the wavefront errors in the exit pupil using only intensity images of a star or other point source of light. This innovative implementation of MGS significantly accelerates the MGS phase retrieval algorithm by using stream-processing hardware on conventional graphics cards. Stream processing is a relatively new, yet powerful, paradigm to allow parallel processing of certain applications that apply single instructions to multiple data (SIMD). These stream processors are designed specifically to support large-scale parallel computing on a single graphics chip. Computationally intensive algorithms, such as the Fast Fourier Transform (FFT), are particularly well suited for this computing environment. This high-speed version of MGS exploits commercially available hardware to accomplish the same objective in a fraction of the original time. The exploit involves performing matrix calculations in nVidia graphic cards. The graphical processor unit (GPU) is hardware that is specialized for computationally intensive, highly parallel computation. From the software perspective, a parallel programming model is used, called CUDA, to transparently scale multicore parallelism in hardware. This technology gives computationally intensive applications access to the processing power of the nVidia GPUs through a C/C++ programming interface. The AAMGS (Accelerated Adaptive MGS) software takes advantage of these advanced technologies, to accelerate the optical phase error characterization. With a single PC that contains four nVidia GTX-280 graphic cards, the new implementation can process four images simultaneously to produce a JWST (James Webb Space Telescope) wavefront measurement 60 times faster than the previous code.

Lam, Raymond K.↗
DOE OSTI2025

Finch: Toxicity Dose Response Curve Prediction of Chemical Compounds and Mixtures

A paradigm shift in chemical risk assessment is emphasizing mixture testing over single compound analysis, eliminating animal testing, and adopting advanced modeling approaches to understand mixture activity profiles. However, existing computational models largely focus on single chemicals, with few effective solutions for modeling complex mixtures that account for synergistic or antagonistic effects and multiple Modes of Action (MoA). Conventional methods like concentration addition (CA) and independent action (IA) are insufficient for this task as they are designed for simplistic interactions and struggle to account for the dynamic and multifaceted nature of chemical mixtures, such as overlapping MoA and non-linear interactions. Finch offers a novel approach utilizing deep learning (DL) embeddings and multi-task quantitative structure-activity relationship (QSAR) models to improve chemical exposure prediction. By leveraging molecular descriptors, physiochemical properties, and large language model (LLM) embeddings from SMILES inputs, Finch preserves critical information in a latent space thereby enhancing predictive accuracy. The multi-task learning aspect of Finch is highly advantageous, as it simultaneously optimizes multiple loss functions, leveraging all available data across tasks to develop generalized representations that effectively capture complex ingredient interactions within mixtures.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

GASNet-EX RMA Communication Performance on Recent Supercomputing Systems

Partitioned Global Address Space (PGAS) programming models, typified by systems such as Unified Parallel C (UPC) and Fortran coarrays, expose one-sided Remote Memory Access (RMA) communication as a key building block for High Performance Computing (HPC) applications. Architectural trends in supercomputing make such programming models increasingly attractive, and newer, more sophisticated models such as UPC++, Legion and Chapel that rely upon similar communication paradigms are gaining popularity. GASNet-EX is a portable, open-source, high-performance communication library designed to efficiently support the networking requirements of PGAS runtime systems and other alternative models in emerging exascale machines. The library is an evolution of the popular GASNet communication system, building upon 20 years of lessons learned. We present microbenchmark results which demonstrate the RMA performance of GASNet-EX is competitive with MPI implementations on four recent, high-impact, production HPC systems. These results are an update relative to previously published results on older systems. The networks measured here are representative of hardware currently used in six of the top ten fastest supercomputers in the world, and all of the exascale systems on the U.S. DOE road map.

Hargrove, Paul H↗
NASA NTRS1983

The future of space - Space tomorrow: The Antarctica model

The exploration and settling of Antarctica with permanent bases are used as illustrative points for establishing a permanent human presence in near-earth space. NASA activities since 1958 have spawned the computer science, solid-state electronics, medical electronics, and communications satellites industries, which are also rapidly expanding in other countries, as are space-faring capabilities. Antarctica is a paradigm for space exploration in that it is hard to reach, hostile to human life, and a great amount of planning is necessary to arrive at the destination and survive. Aircraft made permanent settlements possible on Antarctica, just as the Shuttle does for space. A space station would provide the remote base from which exploration of other planets and settling on the moon could proceed.

Beggs, J.↗
NASA NTRS2001

Generic Divide and Conquer Internet-Based Computing

The rapid growth of internet-based applications and the proliferation of networking technologies have been transforming traditional commercial application areas as well as computer and computational sciences and engineering. This growth stimulates the exploration of new, internet-oriented software technologies that can open new research and application opportunities not only for the commercial world, but also for the scientific and high -performance computing applications community. The general goal of this research project is to contribute to better understanding of the transition to internet-based high -performance computing and to develop solutions for some of the difficulties of this transition. More specifically, our goal is to design an architecture for generic divide and conquer internet-based computing, to develop a portable implementation of this architecture, to create an example library of high-performance divide-and-conquer computing agents that run on top of this architecture, and to evaluate the performance of these agents. We have been designing an architecture that incorporates a master task-pool server and utilizes satellite computational servers that operate on the Internet in a dynamically changing large configuration of lower-end nodes provided by volunteer contributors. Our designed architecture is intended to be complementary to and accessible from computational grids such as Globus, Legion, and Condor. Grids provide remote access to existing high-end computing resources; in contrast, our goal is to utilize idle processor time of lower-end internet nodes. Our project is focused on a generic divide-and-conquer paradigm and its applications that operate on a loose and ever changing pool of lower-end internet nodes.

Radenski, Atanas↗
NASA NTRS2005

Autonomic Computing: Panacea or Poppycock?

Autonomic Computing arose out of a need for a means to cope with rapidly growing complexity of integrating, managing, and operating computer-based systems as well as a need to reduce the total cost of ownership of today's systems. Autonomic Computing (AC) as a discipline was proposed by IBM in 2001, with the vision to develop self-managing systems. As the name implies, the influence for the new paradigm is the human body's autonomic system, which regulates vital bodily functions such as the control of heart rate, the body's temperature and blood flow-all without conscious effort. The vision is to create selfivare through self-* properties. The initial set of properties, in terms of objectives, were self-configuring, self-healing, self-optimizing and self-protecting, along with attributes of self-awareness, self-monitoring and self-adjusting. This self-* list has grown: self-anticipating, self-critical, self-defining, self-destructing, self-diagnosis, self-governing, self-organized, self-reflecting, and self-simulation, for instance.

Sterritt, Roy↗