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At least 1,081 records · Page 60

Using Computer Simulation for Neurolab 2 Mission Planning

This paper presents an overview of the procedure used in the creation of a computer simulation video generated by the Graphics Research and Analysis Facility at NASA/Johnson Space Center. The simulation was preceded by an analysis of anthropometric characteristics of crew members and workspace requirements for 13 experiments to be conducted on Neurolab 2 which is dedicated to neuroscience and behavioral research. Neurolab 2 is being carried out as a partnership among national domestic research institutes and international space agencies. The video is a tour of the Spacelab module as it will be configured for STS-90, scheduled for launch in the spring of 1998, and identifies experiments that can be conducted in parallel during that mission. Therefore, this paper will also address methods for using computer modeling to facilitate the mission planning activity.

Sanders, Betty M.↗

Roofline Analysis in the Intel® Advisor to Deliver Optimized Performance for applications on Intel® Xeon Phi™ Processor

In this session we show, in two case studies, how the roofline feature of Intel Advisor has been utilized to optimize the performance of kernels of the XGC1 and PICSAR codes in preparation for Intel Knights Landing architecture. The impact of the implemented optimizations and the benefits of using the automatic roofline feature of Intel Advisor to study performance of large applications will be presented. This demonstrates an effective optimization strategy that has enabled these science applications to achieve up to 4.6 times speed-up and prepare for future exascale architectures. # Goal/Relevance of Session The roofline model [1,2] is a powerful tool for analyzing the performance of applications with respect to the theoretical peak achievable on a given computer architecture. It allows one to graphically represent the performance of an application in terms of operational intensity, i.e. the ratio of flops performed and bytes moved from memory in order to guide optimization efforts. Given the scale and complexity of modern science applications, it can often be a tedious task for the user to perform the analysis on the level of functions or loops to identify where performance gains can be made. With new Intel tools, it is now possible to automate this task, as well as base the estimates of peak performance on measurements rather than vendor specifications. The goal of this session is to demonstrate how the roofline feature of Intel Advisor can be used to balance memory vs. computation related optimization efforts and effectively identify performance bottlenecks. A series of typical optimization techniques: cache blocking, structure refactoring, data alignment, and vectorization illustrated by the kernel cases will be addressed. # Description of the codes ## XGC1 The XGC1 code [3] is a magnetic fusion Particle-In-Cell code that uses an unstructured mesh for its Poisson solver that allows it to accurately resolve the edge plasma of a magnetic fusion device. After recent optimizations to its collision kernel [4], most of the computing time is spent in the electron push (pushe) kernel, where these optimization efforts have been focused. The kernel code scaled well with MPI+OpenMP but had almost no automatic compiler vectorization, in part due to indirect memory addresses and in part due to low trip counts of low-level loops that would be candidates for vectorization. Particle blocking and sorting have been implemented to increase trip counts of low-level loops and improve memory locality, and OpenMP directives have been added to vectorize compute-intensive loops that were identified by Advisor. The optimizations have improved the performance of the pushe kernel 2x on Haswell processors and 1.7x on KNL. The KNL node-for-node performance has been brought to within 30% of a NERSC Cori phase I Haswell node and we expect to bridge this gap by reducing the memory footprint of compute intensive routines to improve cache reuse. ## PICSAR is a Fortran/Python high-performance Particle-In-Cell library targeting at MIC architectures first designed to be coupled with the PIC code WARP for the simulation of laser-matter interaction and particle accelerators. PICSAR also contains a FORTRAN stand-alone kernel for performance studies and benchmarks. A MPI domain decomposition is used between NUMA domains and a tile decomposition (cache-blocking) handled by OpenMP has been added for shared-memory parallelism and better cache management. The so-called current deposition and field gathering steps that compose the PIC time loop constitute major hotspots that have been rewritten to enable more efficient vectorization. Particle communications between tiles and MPI domain has been merged and parallelized. All considered, these improvements provide speedups of 3.1 for order 1 and 4.6 for order 3 interpolation shape factors on KNL configured in SNC4 quadrant flat mode. Performance is similar between a node of cori phase 1 and KNL at order 1 and better on KNL by a factor 1.6 at order 3 with the considered test case (homogeneous thermal plasma).

97 MATHEMATICS AND COMPUTING↗

Speed in Information Processing with a Computer Driven Visual Display in a Real-time Digital Simulation

Information transfer between the operator and computer-generated display systems is an area where the human factors engineer discovers little useful design data relating human performance to system effectiveness. This study utilized a computer-driven, cathode-ray-tube graphic display to quantify human response speed in a sequential information processing task. The performance criteria was response time to sixteen cell elements of a square matrix display. A stimulus signal instruction specified selected cell locations by both row and column identification. An equal probable number code, from one to four, was assigned at random to the sixteen cells of the matrix and correspondingly required one of four, matched keyed-response alternatives. The display format corresponded to a sequence of diagnostic system maintenance events, that enable the operator to verify prime system status, engage backup redundancy for failed subsystem components, and exercise alternate decision-making judgements. The experimental task bypassed the skilled decision-making element and computer processing time, in order to determine a lower bound on the basic response speed for given stimulus/response hardware arrangement.

Kyle, R. G.↗

Multiple-Flat-Panel System Displays Multidimensional Data

The NASA Ames hyperwall is a display system designed to facilitate the visualization of sets of multivariate and multidimensional data like those generated in complex engineering and scientific computations. The hyperwall includes a 77 matrix of computer-driven flat-panel video display units, each presenting an image of 1,280 1,024 pixels. The term hyperwall reflects the fact that this system is a more capable successor to prior computer-driven multiple-flat-panel display systems known by names that include the generic term powerwall and the trade names PowerWall and Powerwall. Each of the 49 flat-panel displays is driven by a rack-mounted, dual-central-processing- unit, workstation-class personal computer equipped with a hig-hperformance graphical-display circuit card and with a hard-disk drive having a storage capacity of 100 GB. Each such computer is a slave node in a master/ slave computing/data-communication system (see Figure 1). The computer that acts as the master node is similar to the slave-node computers, except that it runs the master portion of the system software and is equipped with a keyboard and mouse for control by a human operator. The system utilizes commercially available master/slave software along with custom software that enables the human controller to interact simultaneously with any number of selected slave nodes. In a powerwall, a single rendering task is spread across multiple processors and then the multiple outputs are tiled into one seamless super-display. It must be noted that the hyperwall concept subsumes the powerwall concept in that a single scene could be rendered as a mosaic image on the hyperwall. However, the hyperwall offers a wider set of capabilities to serve a different purpose: The hyperwall concept is one of (1) simultaneously displaying multiple different but related images, and (2) providing means for composing and controlling such sets of images. In place of elaborate software or hardware crossbar switches, the hyperwall concept substitutes reliance on the human visual system for integration, synthesis, and discrimination of patterns in complex and high-dimensional data spaces represented by the multiple displayed images. The variety of multidimensional data sets that can be displayed on the hyperwall is practically unlimited. For example, Figure 2 shows a hyperwall display of surface pressures and streamlines from a computational simulation of airflow about an aerospacecraft at various Mach numbers and angles of attack. In this display, Mach numbers increase from left to right and angles of attack increase from bottom to top. That is, all images in the same column represent simulations at the same Mach number, while all images in the same row represent simulations at the same angle of attack. The same viewing transformations and the same mapping from surface pressure to colors were used in generating all the images.

Gundo, Daniel↗

A Graphical Model for Fusing Diverse Microbiome Data

This paper develops a Bayesian graphical model for fusing disparate types of count data. The motivating application is the study of bacterial communities from diverse high-dimensional features, in this case, transcripts, collected from different treatments. In such datasets, there are no explicit correspondences between the communities and each corresponds to different factors, making data fusion challenging. We introduce a flexible multinomial-Gaussian generative model for jointly modeling such count data. This latent variable model jointly characterizes the observed data through a common multivariate Gaussian latent space that parameterizes the set of multinomial probabilities of the transcriptome counts. The covariance matrix of the latent variables induces a covariance matrix of co-dependencies between all the transcripts, effectively fusing multiple data sources. We present a computationally scalable variational Expectation-Maximization (EM) algorithm for inferring the latent variables and the parameters of the model. Here, the inferred latent variables provide a common dimensionality reduction for visualizing the data and the inferred parameters provide a predictive posterior distribution. In addition to simulation studies that demonstrate the variational EM procedure, we apply our model to a bacterial microbiome dataset.

59 BASIC BIOLOGICAL SCIENCES↗

Criticality safety enhancements for SCALE 6.2 and beyond - 14648

SCALE is a widely used suite of tools for nuclear systems modeling and simulation that provides comprehensive, verified and validated, user-friendly capabilities for criticality safety, reactor physics, radiation shielding, and sensitivity and uncertainty analysis. Since 1980, regulators, industry, and research institutions around the world have relied on SCALE for nuclear safety analysis and design. SCALE 6.2 provides several new capabilities and significant improvements in many existing features for criticality safety analysis. Enhancements are realized for nuclear data; multigroup resonance self-shielding; continuous-energy Monte Carlo analysis for sensitivity/uncertainty analysis, radiation shielding, and depletion; and graphical user interfaces. An overview of these capabilities is provided in this paper, and additional details are provided in several companion papers. (authors)

42 ENGINEERING↗

Solving the "Hidden Line" Problem

David Hedgley Jr., a mathematician at Dryden Flight Research Center, has developed an accurate computer program that considers whether a line in a graphic model of a three dimensional object should or should not be visible. The Hidden Line Computer Code, program automatically removes superfluous lines and permits the computer to display an object from specific viewpoints, just as the human eye would see it. Users include Rowland Institute for Science in Cambridge, MA, several departments of Lockheed Georgia Co., and Nebraska Public Power District (NPPD).

Source record↗

Evaluation of Droplet Splashing Algorithm in LEWICE 3.0

The Icing Branch at NASA Glenn Research has developed a computer program to simulate ice formation on the leading edge of an aircraft wing during flight through cold, moist air. As part of the branch's current research, members have developed software known as LEWICE. This program is capable of predicting the formation of ice under designated weather conditions. The success of LEWICE is an asset to airplane manufacturers, ice protection system manufacturers, and the airline industry. Simulations of ice formation conducted in the tunnel and in flight is costly and time consuming. However, the danger of in-flight icing continues to be a concern for both commercial and military pilots. The LEWICE software is a step towards inexpensive and time efficient prediction of ice collection. In the most recent version of the program, LEWICE contains an algorithm for droplet splashing. Droplet splashing is a natural occurrence that causes accumulation of ice on aircraft surfaces. At impingement water droplets lose a portion of their mass to splashing. With part of each droplet joining the airflow and failing to freeze, early versions of LEWICE without the splashing algorithm over-predicted the collection of ice on the leading edge. The objective of my project was to determine whether the revised version of LEWICE accurately reflected the ice collection data obtained from the Icing Research Tunnel (IRT). The experimental data from the IRT was collected by Mark Potapczuk in January, March and July of 2001 and April and December of 2002. Experimental data points were the result of ice tracings conducted shortly after testing in the tunnel. Run sheets, which included a record of velocity, temperature, liquid water content and droplet diameter, served as the input of the LEWICE computer program. Parameters identical to the tunnel conditions were used to run LEWICE 2.0 and LEWICE 3.0. The results from IRT and versions of LEWICE were compared graphically. After entering the raw experimental data and computer output into a spread sheet, I mapped each ice formation onto a clean airfoil. The LEWICE output provided the data points to graphically depict ice formations developed by the program. weather conditions of runs conducted in January 2001, it was evident that the splashing algorithm of LEWICE 3.0 predicts ice formations more accurately than LEWICE 2.0. Especially at conditions with droplet size between 80 and 160 microns, the splashing algorithm of the new LEWICE version compensated for the loss of droplet mass as a result of splashing. In contrast, LEWICE 2.0 consistently over-predicted the mass of the ice in conditions with droplet size exceeding 80 microns. This evidence confirms that changes made to algorithms of LEWICE 3.0 have increased the accuracy of predicting ice collection.

Homenko, Hilary N.↗

Dynamic graph system for a semantic database

A method and system in a computer system for dynamically providing a graphical representation of a data store of entries via a matrix interface is disclosed. A dynamic graph system provides a matrix interface that exposes to an application program a graphical representation of data stored in a data store such as a semantic database storing triples. To the application program, the matrix interface represents the graph as a sparse adjacency matrix that is stored in compressed form. Each entry of the data store is considered to represent a link between nodes of the graph. Each entry has a first field and a second field identifying the nodes connected by the link and a third field with a value for the link that connects the identified nodes. The first, second, and third fields represent the rows, column, and elements of the adjacency matrix.

97 MATHEMATICS AND COMPUTING↗

Dynamic graph system for a semantic database

A method and system in a computer system for dynamically providing a graphical representation of a data store of entries via a matrix interface is disclosed. A dynamic graph system provides a matrix interface that exposes to an application program a graphical representation of data stored in a data store such as a semantic database storing triples. To the application program, the matrix interface represents the graph as a sparse adjacency matrix that is stored in compressed form. Each entry of the data store is considered to represent a link between nodes of the graph. Each entry has a first field and a second field identifying the nodes connected by the link and a third field with a value for the link that connects the identified nodes. The first, second, and third fields represent the rows, column, and elements of the adjacency matrix.

97 MATHEMATICS AND COMPUTING↗

A new efficient grain growth model using a random Gaussian-sampled mode filter

This paper presents the use of a Gaussian neighborhood mode filter for predicting grain growth in a manner similar to the solutions obtained by a Monte Carlo Potts model. This flexible grain growth model can quickly utilize modern, computationally optimized data science strategies on graphics processing units to simulate grain growth up to 100 times faster than the state-of-the-art, publicly available Monte Carlo Potts model. We show that, given the correct neighborhood, the mode filter can replicate normal grain growth in two or three dimensions. In addition, the paper briefly demonstrates the ability to model limited anisotropic in grain boundary energy and mobility. Anisotropic grain boundary energy is modeled by defining a weighted mode filter operation. Anisotropic grain boundary mobility is modeled by scaling and orienting the Gaussian neighborhood in a particular direction.

Anisotropy↗

Real-time graphics for the Space Station Freedom cupola, developed in the Systems Engineering Simulator

Among the Lyndon B. Johnson Space Center's responsibilities for Space Station Freedom is the cupola. Attached to the resource node, the cupola is a windowed structure that will serve as the space station's secondary control center. From the cupola, operations involving the mobile service center and orbital maneuvering vehicle will be conducted. The Systems Engineering Simulator (SES), located in building 16, activated a real-time man-in-the-loop cupola simulator in November 1987. The SES cupola is an engineering tool with the flexibility to evolve in both hardware and software as the final cupola design matures. Two workstations are simulated with closed-circuit television monitors, rotational and translational hand controllers, programmable display pushbuttons, and graphics display with trackball and keyboard. The displays and controls of the SES cupola are driven by a Silicon Graphics Integrated Raster Imaging System (IRIS) 4D/70 GT computer. Through the use of an interactive display builder program, SES, cupola display pages consisting of two dimensional and three dimensional graphics are constructed. These display pages interact with the SES via the IRIS real-time graphics interface. The focus is on the real-time graphics interface applications software developed on the IRIS.

Red, Michael T.↗

microMS: A Python Platform for Image-Guided Mass Spectrometry Profiling

Image-guided mass spectrometry (MS) profiling provides a facile framework for analyzing samples ranging from single cells to tissue sections. The fundamental workflow utilizes a whole-slide microscopy image to select targets of interest, determine their spatial locations, and subsequently perform MS analysis at those locations. Improving upon prior reported methodology, a software package was developed for working with microscopy images. microMS, for microscopy-guided mass spectrometry, allows the user to select and profile diverse samples using a variety of target patterns and mass analyzers. Written in Python, the program provides an intuitive graphical user interface to simplify image-guided MS for novice users. The class hierarchy of instrument interactions permits integration of new MS systems while retaining the feature-rich image analysis framework. microMS is a versatile platform for performing targeted profiling experiments using a series of mass spectrometers. The flexibility in mass analyzers greatly simplifies serial analyses of the same targets by different instruments. The current capabilities of microMS are presented, and its application for off-line analysis of single cells on three distinct instruments is demonstrated. The software has been made freely available for research purposes. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Intelligent Command and Control Systems for Satellite Ground Operations

This grant, Intelligent Command and Control Systems for Satellite Ground Operations, funded by NASA Goddard Space Flight Center, has spanned almost a decade. During this time, it has supported a broad range of research addressing the changing needs of NASA operations. It is important to note that many of NASA's evolving needs, for example, use of automation to drastically reduce (e.g., 70%) operations costs, are similar requirements in both government and private sectors. Initially the research addressed the appropriate use of emerging and inexpensive computational technologies, such as X Windows, graphics, and color, together with COTS (commercial-off-the-shelf) hardware and software such as standard Unix workstations to re-engineer satellite operations centers. The first phase of research supported by this grant explored the development of principled design methodologies to make effective use of emerging and inexpensive technologies. The ultimate performance measures for new designs were whether or not they increased system effectiveness while decreasing costs. GT-MOCA (The Georgia Tech Mission Operations Cooperative Associate) and GT-VITA (Georgia Tech Visual and Inspectable Tutor and Assistant), whose latter stages were supported by this research, explored model-based design of collaborative operations teams and the design of intelligent tutoring systems, respectively. Implemented in proof-of-concept form for satellite operations, empirical evaluations of both, using satellite operators for the former and personnel involved in satellite control operations for the latter, demonstrated unequivocally the feasibility and effectiveness of the proposed modeling and design strategy underlying both research efforts. The proof-of-concept implementation of GT-MOCA showed that the methodology could specify software requirements that enabled a human-computer operations team to perform without any significant performance differences from the standard two-person satellite operations team. GT-VITA, using the same underlying methodology, the operator function model (OFM), and its computational implementation, OFMspert, successfully taught satellite control knowledge required by flight operations team members. The tutor structured knowledge in three ways: declarative knowledge (e.g., What is this? What does it do?), procedural knowledge, and operational skill. Operational skill is essential in real-time operations. It combines the two former knowledge types, assisting a student to use them effectively in a dynamic, multi-tasking, real-time operations environment. A high-fidelity simulator of the operator interface to the ground control system, including an almost full replication of both the human-computer interface and human interaction with the dynamic system, was used in the GT-MOCA and GT-VITA evaluations. The GT-VITA empirical evaluation, conducted with a range of'novices' that included GSFC operations management, GSFC operations software developers, and new flight operations team members, demonstrated that GT-VITA effectively taught a wide range of knowledge in a succinct and engaging manner.

Mitchell, Christine M.↗

A semi-automated system for plotting and computer cataloging of remote sensing imagery

Description of a computer-assisted system for plotting and descriptor-cataloging of aerial imagery - an ingredient of the aerial image data handling system of the NASA Earth Resources Aircraft Project (ERAP). The system under consideration uses two graphic tablets linked interactively with a digital computer as input devices for deriving frame coordinates by correlating image points to map points. The various software programs and operating modes facilitate a semiautomatic plotting of an image by selecting two or more points within the image for matching with map details. The computer performs the scaling and orientation transformations for the calculation of the center and corner coordinates of the frame. Twenty five other descriptors for each frame are fed into a computerized data base requiring a minimum operator's time for verification and correction.

Gnauck, G. E.↗

ATLAS, an integrated structural analysis and design system. Volume 3: User's manual, input and execution data

The input data and execution control statements for the ATLAS integrated structural analysis and design system are described. It is operational on the Control Data Corporation (CDC) 6600/CYBER computers in a batch mode or in a time-shared mode via interactive graphic or text terminals. ATLAS is a modular system of computer codes with common executive and data base management components. The system provides an extensive set of general-purpose technical programs with analytical capabilities including stiffness, stress, loads, mass, substructuring, strength design, unsteady aerodynamics, vibration, and flutter analyses. The sequence and mode of execution of selected program modules are controlled via a common user-oriented language.

Dreisbach, R. L.↗

Developing Digital Twin Visualizations: A Methodology and Case Study on Chemical Separation Processing

As advances in digital engineering continue to push the technological boundaries, digital twin (DT) visualizations for diagnostics and safeguards advancement become much more feasible and practical. DTs generate large and complex data streams that require effective user interfaces to provide monitoring and diagnostic capabilities. Unfortunately, while these frameworks exist, there is not much research on the systematic documentation of human–computer interaction (HCI) for DT visualization. This work presents a dual-mode visualization methodology (two dimensional [2D] graphical user interface dashboard and 3D mixed reality) designed to support diagnostic tasks in DT systems and building on a validated framework and applying established HCI principles. The methodology is demonstrated through a case study of aqueous processing at Idaho National Laboratory, using experimental data from the chemical solvent extraction runs. Our interfaces display real-time alerts and monitoring to inform users of safeguards anomalies. The interfaces use immersive 3D mixed-reality visualization for further system and experiment investigation. This work demonstrates how the systematic application of HCI principles can inform DT visualization design for diagnostic and safeguards applications. While formal user evaluation studies remain as future work, this paper documents the systematic design methodology and demonstrates a proof-of-concept implementation.

3D visualization↗

Legato: Personal Computer Software for Analyzing Pressure-Sensitive Paint Data

'Legato' is personal computer software for analyzing radiometric pressure-sensitive paint (PSP) data. The software is written in the C programming language and executes under Windows 95/98/NT operating systems. It includes all operations normally required to convert pressure-paint image intensities to normalized pressure distributions mapped to physical coordinates of the test article. The program can analyze data from both single- and bi-luminophore paints and provides for both in situ and a priori paint calibration. In addition, there are functions for determining paint calibration coefficients from calibration-chamber data. The software is designed as a self-contained, interactive research tool that requires as input only the bare minimum of information needed to accomplish each function, e.g., images, model geometry, and paint calibration coefficients (for a priori calibration) or pressure-tap data (for in situ calibration). The program includes functions that can be used to generate needed model geometry files for simple model geometries (e.g., airfoils, trapezoidal wings, rotor blades) based on the model planform and airfoil section. All data files except images are in ASCII format and thus are easily created, read, and edited. The program does not use database files. This simplifies setup but makes the program inappropriate for analyzing massive amounts of data from production wind tunnels. Program output consists of Cartesian plots, false-colored real and virtual images, pressure distributions mapped to the surface of the model, assorted ASCII data files, and a text file of tabulated results. Graphical output is displayed on the computer screen and can be saved as publication-quality (PostScript) files.

Schairer, Edward T.↗