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Research conducted at the Institute for Computer Applications in Science and Engineering in applied mathematics, numerical analysis and computer science is summarized.
Research conducted at the Institute for Computer Applications in Science and Engineering in applied mathematics, numerical analysis and computer science during the period April 1, 1983 through September 30, 1983 is summarized.
Research conducted at the Institute for Computer Applications in Science and Engineering in applied mathematics, numerical analysis, and computer science during the period October 1, 1984 through March 31, 1985 is summarized.
The current Life Sciences Laboratory Equipment (LSLE) microcomputer for life sciences experiment data acquisition is now obsolete. Among the weaknesses of the current microcomputer are small memory size, relatively slow analog data sampling rates, and the lack of a bulk data storage device. While life science investigators normally prefer data to be transmitted to Earth as it is taken, this is not always possible. No down-link exists for experiments performed in the Shuttle middeck region. One important aspect of a replacement microcomputer is provision for in-flight storage of experimental data. The Write Once, Read Many (WORM) optical disk was studied because of its high storage density, data integrity, and the availability of a space-qualified unit. In keeping with the goals for a replacement microcomputer based upon commercially available components and standard interfaces, the system studied includes a Small Computer System Interface (SCSI) for interfacing the WORM drive. The system itself is designed around the STD bus, using readily available boards. Configurations examined were: (1) master processor board and slave processor board with the SCSI interface; (2) master processor with SCSI interface; (3) master processor with SCSI and Direct Memory Access (DMA); (4) master processor controlling a separate STD bus SCSI board; and (5) master processor controlling a separate STD bus SCSI board with DMA.
Abstract Motivation Molecule representation learning (MRL) translates molecules into a real vector space, serving as input to downstream tasks in biology, chemistry, and computer science. This article introduces a chemical synthesis graph learning (CSGL) framework, which enhances MRL by considering both the atomic structures of molecules and their roles in chemical reactions through a hierarchical graph representation. Specifically, molecules are first modeled based on their molecular graphs, which capture atomic-level structural information. They are then further refined using a chemical synthesis graph, where nodes represent reactant and product molecule sets, and edges encode chemical transformations between reactants and products (e.g. changes in molecular structures). CSGL optimizes molecular embeddings of reactant and product nodes in a fashion that ensures the embeddings conform to a chemical balance constraint. Results Experimental results show that our method CSGL achieves strong performance on a variety of tasks, including product prediction, reaction classification, and molecular property prediction. Availability and implementation https://github.com/li-2023/CSGL.
The Institute conducts unclassified basic research in applied mathematics, numerical analysis, and computer science in order to extend and improve problem-solving capabilities in science and engineering, particularly in aeronautics and space. The major categories of the current Institute for Computer Applications in Science and Engineering (ICASE) research program are: (1) numerical methods, with particular emphasis on the development and analysis of basic numerical algorithms; (2) control and parameter identification problems, with emphasis on effective numerical methods; (3) computational problems in engineering and the physical sciences, particularly fluid dynamics, acoustics, and structural analysis; and (4) computer systems and software, especially vector and parallel computers. ICASE reports are considered to be primarily preprints of manuscripts that have been submitted to appropriate research journals or that are to appear in conference proceedings.
This report summarizes research conducted at the Institute for Computer Applications in Science and Engineering in applied mathematics, numerical analysis, and computer science during the period April 1, 1987 through October 1, 1987.
This report summarizes research conducted at the Institute for Computer Applications in Science and Engineering in applied mathematics, fluid mechanics, and computer science during the period 1 Oct. 1996 - 31 Mar. 1997.
This report summarizes research conducted at the Institute for Computer Applications in Science and Engineering in applied mathematics, fluid mechanics, and computer science.
This report summarizes research conducted at ICASE in applied mathematics, fluid mechanics, computer science, and structures and material sciences during the period April 1, 2000 through September 30, 2000.
Hydrodynamics And Radiation Diffusion (HARD) is an open-source application for high-performance simulations of compressible hydrodynamics with radiation-diffusion coupling. Built on the FleCSI (Bergen et al., 2021 [1]) (Flexible Computational Science Infrastructure) framework, HARD expresses its computational units as tasks whose execution can be orchestrated by multiple back-end runtimes, including Legion (Bauer et al., 2012 [2]), MPI (Forum, 1994 [3]), and HPX (Kaiser et al., 2020 [4]). Node-level parallelism is handled through Kokkos (Edwards et al., 2014 [5]), providing a single-source, portable code base that runs efficiently on laptops, small homogeneous clusters, and the largest heterogeneous supercomputers currently available. To ensure scientific reliability, HARD includes a regression test suite that automatically reproduces canonical verification problems such as the Sod and LeBlanc shock tubes, and the Sedov blast wave, comparing numerical solutions against known analytical results. The project is distributed under an OSI-approved license, hosted on GitHub, and accompanied by reproducible build scripts and continuous integration workflows. This combination of performance portability, verification infrastructure, and community-focused development makes HARD a sustainable platform for advancing radiation hydrodynamics research across multiple domains.
This report summarizes research conducted at the Institute for Computer Applications in Science and Engineering in applied mathematics. fluid mechanics, and computer science during the period April 1, 1999 through September 30. 1999.
This report summarizes the range of computer science related activities undertaken by CESDIS(Center of Excellence in Space Data and Information Sciences) for NASA in the twelve months from July 1, 1996 through June 30, 1997. These activities address issues related to accessing, processing, and analyzing data from space observing systems through collaborative efforts with university, industry, and NASA space and Earth scientists.
NREL's computational sciences center hosts the largest high performance computing (HPC) capabilities dedicated to energy research while functioning as a living laboratory for energy-efficient computing. NREL's HPC capabilities support the research needs of the Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE). In ten years of operation, HPC use in EERE-sponsored research has grown by a factor of 30, including work in electricity generation, energy efficiency, transportation, and energy system modeling. This paper analyzes this research portfolio, providing examples of individual use cases. The paper documents NREL's history of operating one of the world's most energy-efficient data centers while examining pathways to reduce economic and environmental impact beyond reduction of Power Usage Efficiency (PUE). This paper concludes by examining the unique opportunities created for accelerating improvements in data center efficiency created by combining an HPC system dedicated to energy research and a research program in energy-efficient computing.
We consider the problem of computing a sparse binary representation of an image. Given an image and an overcomplete, non-orthonormal basis, we aim to find a sparse binary vector indicating the minimal set of basis vectors that when added together best reconstruct the given input. We formulate this problem with an L 2 loss on the reconstruction error, and an L 0 loss on the binary vector enforcing sparsity. First, we solve the sparse representation QUBOs by solving them both on a D-Wave quantum annealer with Pegasus chip connectivity, as well as on the Intel Loihi 2 spiking neuromorphic processor using a stochastic Non-equilibrium Boltzmann Machine (NEBM). Second, using Quantum Evolution Monte Carlo with Reverse Annealing and iterated warm starting on Loihi 2 to evolve the solution quality from the respective machines. We demonstrate that both quantum annealing and neuromorphic computing are suitable for solving binary sparse coding QUBOs.
"(Only Talk/No Publication) NASA’s Advanced Information Systems Technology (AIST) Program identifies, develops, and supports adoption of software and information systems, as well as novel computer science technologies expected to be needed by the Earth Science Division in the 5-10-year timeframe. This presentation gives an overview of the AIST Program. AIST’s previous thrusts have been New Observing Strategies (NOS) and Analytic Collaborative Frameworks (ACF). The current vision is to connect these two thrusts and integrate them into the larger concept of Earth System Digital Twins (ESDT). To implement this new vision, the AIST Program is focusing on technologies and innovative concepts with three main objectives: O1. Enable new observation measurements and new observing systems design and operations through intelligent, timely, dynamic, and coordinated distributed sensing; O2. Enable agile science investigations that fully utilize the large amount of diverse observations using advanced analytic tools, visualizations, and computing environments, and that interact seamlessly with relevant observing systems; O3. Enable the development of integrated Earth Science frameworks that mirror the Earth with state-of-the-art models (Earth system models and others), timely and relevant observations, and analytic tools. This thrust will provide technology for enabling near- and long-term science and policy decisions (“science decisions” including planning for the acquisition of new measurements; the development of new models or science analysis; the integration of Earth observations in novel ways; applications to inform choices, support decisions, and guide actions for societal benefit; etc.)."
This report summarizes research conducted at the Institute for Computer Applications in Science and Engineering in applied mathematics, computer science, fluid mechanics, and structures and materials during the period October 1, 1999 through March 31, 2000.
Computed Tomography (CT) has proved to be of inestimable use in providing a rapid evaluation of a variety of samples from Mechanics of Granular Materials (MGM) to electronic materials (Ge-Si alloys) to space grown materials such as meteorites. The system at Kennedy Space Center (KSC), because of its convenient geographical location, is ideal for examining samples immediately after returning to Earth. It also has the advantage of the choice of fluxes, and in particular the use of a radioactive cobalt source, which is basically monochromatic. This permits a reasonable measurement of density to be made from which chemical composition can be determined. Due to the current dearth of long duration space grown materials, the CT instrument has been used to characterize materials in preparation for flight, to determine thermal expansion values, and to examine long duration space grown materials, i.e. meteorites. The work will first describe the establishment of the protocol for obtaining the optimum density readings for any material. This will include both the effects of the hardware or instrumental parameters that can be controlled, and the techniques used to process the CT data. Examples will be given of the compositional variation along single crystals of germanium-silicon alloys. Density variation with temperature has been measured in preparation for future materials science experiments; this involved the fabrication and installation of a single zone furnace incorporating a heat pipe to ensure of high temperature uniformity. At the time of writing the thermal expansion of lead has been measured from room temperature to 900 C. Three methods are available. Digital radiography enable length changes to be determined. Prior to melting the sample is small than the container and the diameter change can be measured. Most critical, however, is the density change in solid, through the melting region, and in the liquid state. These data are needed for engineering purposes to aid in the design of containment cartridges, and for enabling fluid flow calculations. A second sample, with the lead alloyed with antimony is ready for scanning. This corresponds to the planned composition of Dr. Poirier's flight experiment. Finally, three-dimensional results will be shown of the structure of a two-phase metallic meteorite of metal and sulfide, in which the iron-nickel phase has coarsened during slow cooling over hundreds of millions of years.