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At least 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Implementing Software Resiliency in HPX for Extreme Scale Computing

The DOE Office of Science Exascale Computing Project (ECP) outlines the next milestones in the supercomputing domain. The target computing systems under the project will deliver 10x performance while keeping the power budget under 30 megawatts. With such large machines, the need to make applications resilient has become paramount. The benefits of adding resiliency to mission critical and scientific applications, includes the reduced cost of restarting the failed simulation both in terms of time and power. Most of the current implementation of resiliency at the software level makes use of a Coordinated Checkpoint and Restart (C/R). This technique of resiliency generates a consistent global snapshot, also called a checkpoint. Generating snapshots involves global communication and coordination and is achieved by synchronizing all running processes. The generated checkpoint is then stored in some form of persistent storage. On failure detection, the runtime initiates a global rollback to the most recent previously saved checkpoint. This involves aborting all running processes, rolling them back to the previous state and restarting them.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

IDEAL: Images Across Domains, Experiments, Algorithms and Learning

Research across science domains is increasingly reliant on image-centric data. Software tools are in high demand to uncover relevant, but hidden, information in digital images, such as those coming from faster next generation high-throughput imaging platforms. The challenge is to analyze the data torrent generated by the advanced instruments efficiently, and provide insights such as measurements for decision-making. In this article, we overview work performed by an interdisciplinary team of computational and materials scientists, aimed at designing software applications and coordinating research efforts connecting (1) emerging algorithms for dealing with large and complex datasets; (2) data analysis methods with emphasis in pattern recognition and machine learning; and (3) advances in evolving computer architectures. Engineering tools around these efforts accelerate the analyses of image-based recordings, improve reusability and reproducibility, scale scientific procedures by reducing time between experiments, increase efficiency, and open opportunities for more users of the imaging facilities. This paper describes our algorithms and software tools, showing results across image scales, demonstrating how our framework plays a role in improving image understanding for quality control of existent materials and discovery of new compounds.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2011

Wake Cycle Robustness of the Mars Science Laboratory Flight Software

The Mars Science Laboratory (MSL) is a spacecraft being developed by the Jet Propulsion Laboratory (JPL) for the purpose of in-situ exploration on the surface of Mars. The objective of MSL is to explore and quantitatively assess a local region on the Martian surface as a habitat for microbial life, past or present. This objective will be accomplished through the assessment of the biological potential of at least one target environment, the characterization of the geology and geochemistry of the landing region, an investigation of the planetary process relevant to past habitability, and a characterization of surface radiation. For this purpose, MSL incorporates a total of ten scientific instruments for which functions are to include, among others, atmospheric and descent imaging, chemical composition analysis, and radiation measurement. The Flight Software (FSW) system is responsible for all mission phases, including launch, cruise, entry-descent-landing, and surface operation of the rover. Because of the essential nature of flight software to project success, each of the software modules is undergoing extensive testing to identify and correct errors.

Whitehill, Robert↗
NASA NTRS2018

Challenges in Development of Online Visualization and Analysis Tools for Satellite Data

Over the years, various online visualization and analysis tools have been developed to facilitate satellite data access and help scientific users around the world to conduct research and develop applications (e.g., data product evaluation, what-if questions, etc.). For those who are new to satellite data products, using them can be a daunting task due to many obstacles in data processing such as data formats, complex data structures, special software packages, unfamiliar terminology, etc., especially when one is not sure whether a dataset is suitable for his/er research project. Even for experienced users, developing software for data processing and analysis can be a costly and time-consuming task. Online visualization tools can overcome many of these difficulties and allow users to focus on scientific questions. For example, Giovanni (the Geospatial Interactive Online Visualization and Analysis Infrastructure, https://giovanni.gsfc.nasa.gov), developed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), allows access over 1900 satellite and model variables in 82 measurement groups of 8 disciplines without downloading data and software. Main features include basic functions for data analysis and visualization, data provenance, output data in different formats (ASCII, NetCDF, GeoTIFF), and more. Over the years, ~1700 peer-reviewed publications in different disciplines have been benefited from Giovanni in research activities (e.g. initial investigation, what-if questions, product evaluation). Despite the success of online visualization and analysis tools, challenges and new opportunities still exist and more can be done with new requirements and technology. Examples are: a) how to increase the efficiency of dataset search by enhancing intuitive aspects; b) how to facilitate interdisciplinary research; c) how to provide data quality information; d) how to engage users to participate in data quality assessment; and more. NASA Earth Observing System Data and Information System (EOSDIS) satellite-based data products are processed at various levels ranging from Level 0 to Level 4. While most users use data products at higher levels (Level-3 and 4), products at lower levels are still important for case studies, algorithm development, ground validation, etc. In this presentation, we will use Giovanni as an example to present and discuss challenges and near-future opportunities for satellite data online visualization and analysis tools.

Liu, Zhong↗
NASA NTRS2004

Developing Software for NASA Missions in the New Millennia

NASA is working on new mission concepts for exploration of the solar system. The concepts for these missions include swarms of hundreds of cooperating intelligent spacecraft which will be able to work in teams and gather more data than current single spacecraft missions. These spacecraft will not only have to operate independently for long periods of time on their own and in teams, but will also need to have autonomic properties of self healing, self configuring, self optimizing and self protecting for them to survive in the harsh space environment. Software for these types of missions has never been developed before and represents some of the challenges of software development in the new millennia. The Autonomous Nano Technology Swarm (ANTS) mission is an example of one of the swarm missions NASA is considering. The ANTS mission will use a swarm of one thousand pico-spacecraft that weigh less than five pounds. Using an insect colony analog, ANTS will explore the asteroid belt and catalog the mass, density, morphology, and chemical composition of the asteroids. Due to the size of the spacecraft, each will only carry a single miniaturized science instrument which will require them to cooperate in searching for asteroids that are of scientific interest. This article also discusses the ANTS mission, the properties the spacecraft will need and how that will effect future software development.

Truszkowski, Walt↗
NASA NTRS1993

The methodology of multi-viewpoint clustering analysis

One of the greatest challenges facing the software engineering community is the ability to produce large and complex computer systems, such as ground support systems for unmanned scientific missions, that are reliable and cost effective. In order to build and maintain these systems, it is important that the knowledge in the system be suitably abstracted, structured, and otherwise clustered in a manner which facilitates its understanding, manipulation, testing, and utilization. Development of complex mission-critical systems will require the ability to abstract overall concepts in the system at various levels of detail and to consider the system from different points of view. Multi-ViewPoint - Clustering Analysis MVP-CA methodology has been developed to provide multiple views of large, complicated systems. MVP-CA provides an ability to discover significant structures by providing an automated mechanism to structure both hierarchically (from detail to abstract) and orthogonally (from different perspectives). We propose to integrate MVP/CA into an overall software engineering life cycle to support the development and evolution of complex mission critical systems.

Mehrotra, Mala↗
DOE OSTI2017

ASCR Report on a Quantum Computing Testbed for Science

This report details the findings of the Quantum Testbed Stakeholder Workshop sponsored by the Department of Energy’s Advanced Scientific Computing Research Program to identify opportunities and challenges in establishing a quantum testbed to advance quantum computing hardware and software systems that will enable science investigations. The workshop was help on February 14 – 16, 2017 in Washington DC and served as a forum for individual stakeholders from academia, industry, national laboratories, and government to provide their perspectives and ideas on the overarching goals and objectives of a quantum testbed, technical considerations, and how a quantum testbed program would be synergistic with other nascent quantum computing efforts in the US and worldwide. This report summarizes discussions on best practices for management of various types of collaborative research activities, including topics such as workforce training and building strong relationships with the research community. It also reviews specific technologies that have been identified by the ASCR Program as being important for the success of a quantum testbed whose overall goal is advancing quantum computing for scientific applications in the next five years.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Remote operation of the DIII-D National Fusion Facility

Abstract Full remote scientific operation of the DIII-D National Fusion Facility is now possible through significant advances in the computer science hardware and software infrastructure made over the last decade. Capabilities around information visualization, data movement, and communication have all been enhanced. The level of capability deployed to remotely operate DIII-D required an infrastructure advancement over what had previously been achieved in the fusion community. The large quantity of real-time data that is automatically displayed on DIII-D’s control room screens can now be visualized by remote participants via web-based applications. New audio/video solutions using the VoIP and instant messaging application Discord have been implemented to mimic the dynamic and ad-hoc scientific conversations that are critical in successfully operating an experimental campaign. Discord’s ability for a user to rapidly move between audio channels, text with images, and share screens is a significant enhancement over traditional videoconferencing tools. In addition, multiple combinations of broadcast audio are made available via a web-based application to allow remote participants to simultaneously listen to general announcements/sounds while conducting their own specific conversations. Secure methodologies have been put into place to allow remote control of hardware including DIII-D’s plasma control system application. Secure methods also included the ability of the on-site team to closely coordinate their work with remote team members which has been enhanced through extensions to the wireless network and the use of tablet computers for audio/video/screen sharing. However, no amount of software can fully replace the need for ‘hands on hardware.’ This infrastructure was severely stress tested during the COVID-19 pandemic where occupancy of the DIII-D control room was restricted. Operational efficiency during the pandemic, measured in discharges per hour, remained high (3.8 ± 0.8) compared to values obtained pre-pandemic (3.7 ± 0.8).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

IRIS-HEP Strategic Plan for the Next Phase of Software Upgrades for HL-LHC Physics

The quest to understand the fundamental building blocks of nature and their interactions is one of the oldest and most ambitious of human scientific endeavors. CERN's Large Hadron Collider (LHC) represents a huge step forward in this quest. The discovery of the Higgs boson, the observation of exceedingly rare decays of $B$ mesons, and stringent constraints on many viable theories of physics beyond the Standard Model (SM) demonstrate the great scientific value of the LHC physics program. The next phase of this global scientific project will be the High-Luminosity LHC (HL-LHC) which will collect data starting circa 2029 and continue through the 2030s. The primary science goal is to search for physics beyond the SM and, should it be discovered, to study its implications. In the HL-LHC era, the ATLAS and CMS experiments will record around 100 times as many collisions as were used to discover the Higgs boson (and at twice the energy). Both NSF and DOE are making large detector upgrade investments so the HL-LHC can operate in this high-rate environment. Similar investment in software R&D for acquiring, managing, processing and analyzing HL-LHC data is critical to maximize the return-on-investment in the upgraded accelerator and detectors. This report presents a strategic plan for a possible second 5-year funded phase (2023 through 2028) for the Institute for Research and Innovation in Software for High Energy Physics (IRIS-HEP) which will close remaining software and computing gaps to deliver HL-LHC science.

43 PARTICLE ACCELERATORS↗
DOE OSTI2016

RIKEN/RBRC Scientific Review Committee Meeting April 5-8, 2016. Proceedings of RIKEN BNL Research Center, Volume 126

Considerable progress in lattice gauge computing has been made by the RBRC Computing Group over the last 5 years. The lattice gauge community has recognized some of this work by awarding two Wilson prizes, in 2012 and in 2015. The Computing Group, in collaboration with RIKEN, BNL and the UKQCD collaboration, has focused on both physics simulations and technical developments, in both software and hardware. The physics output has been primarily in the area of fundamental physical quantities, e.g., in K and B mesons, nucleon form factors, g-2 of the muon, electric dipole moments and physics beyond the Standard Model. The software effort has produced new and/or more efficient algorithms, such as the all-mode averaging (AMA), and ensemble generation techniques. This proceedings records the 14th scientific evaluation of the RIKEN BNL Research Center (RBRC). In order to illustrate the breadth and scope of the RBRC program, each member of the Center made a presentation on his/her research efforts. This encompassed three major areas of investigation: theoretical, experimental and computational physics. In addition, the committee met privately with the fellows and postdocs to ascertain their opinions and concerns. Although the main purpose of this review is a report to RIKEN management on the health, scientific value, management and future prospects of the Center, the RBRC management felt that a compendium of the scientific presentations are of sufficient quality and interest that they warrant a wider distribution. Therefore we have made this compilation and present it to the community for its information and enlightenment.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Toward a smart data transfer node

Scientific computing systems are becoming significantly more complex, with distributed teams and complex workflows spanning resources from telescopes and light sources to fast networks and Internet of Things sensor systems. In such settings, no single, centralized administrative team and software stack can coordinate and manage all resources used by a single application. Indeed, we have reached a critical limit in manageability using current human-in-the-loop techniques. We therefore argue that resources must begin to respond automatically, adapting and tuning their behavior in response to observed properties of scientific workflows. Over time, machine learning methods can be used to identify effective strategies for autonomic, goal-driven management behaviors that can be applied end-to-end across the scientific computing landscape. Using the data transfer nodes that are widely deployed in modern research networks as an example, we explore the architecture, methods, and algorithms needed for a smart data transfer node to support future scientific computing systems that self-tune and self-manage.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2021

InSight Mars Lander Instrument Deployment Arm Flight Software

The Interior Exploration using Seismic Investigations, Geodesy and Heat Transport (InSight) lander landed on Mars on November 26, 2018 and continues to investigate the internal structure of the planet two years later. The Instrument Deployment Arm (IDA), a robotic arm on the lander, was used to deploy the science instrument payloads from the lander deck to the surface of Mars and to take images of the lander and the surrounding environment. This was the first precision deployment and release by a robotic arm on another planet. After deploying the instruments, the IDA has been used for instrument commissioning, scientific data gathering, and to assist with troubleshooting one of the science instruments. This paper provides a high-level summary of the flight software that controls the IDA. The paper provides an overview of the IDA software interfaces, task structure, command handling strategy, motion specification, motion planning, motor control, grapple control, fault protection, and telemetry.

Ali, Khaled S.↗
DOE OSTI2016

Uncertainty Quantification in Climate Modeling and Projection

The projection of future climate is one of the most complex problems undertaken by the scientific community. Although scientists have been striving to better understand the physical basis of the climate system and to improve climate models, the overall uncertainty in projections of future climate has not been significantly reduced (e.g., from the IPCC AR4 to AR5). With the rapid increase of complexity in Earth system models, reducing uncertainties in climate projections becomes extremely challenging. Since uncertainties always exist in climate models, interpreting the strengths and limitations of future climate projections is key to evaluating risks, and climate change information for use in Vulnerability, Impact, and Adaptation (VIA) studies should be provided with both well-characterized and well-quantified uncertainty. The workshop reported herein aimed at providing participants, many of them from developing countries, information on strategies to quantify the uncertainty in climate model projections and assess the reliability of climate change information for decision-making. The program included a mixture of lectures on fundamental concepts in Bayesian inference and sampling, applications, and hands-on computer laboratory exercises employing software packages for Bayesian inference, Markov Chain Monte Carlo methods, and global sensitivity analyses. The lectures covered a range of scientific issues underlying the evaluation of uncertainties in climate projections, such as the effects of uncertain initial and boundary conditions, uncertain physics, and limitations of observational records. Progress in quantitatively estimating uncertainties in hydrologic, land surface, and atmospheric models at both regional and global scales was also reviewed. The application of Uncertainty Quantification (UQ) concepts to coupled climate system models is still in its infancy. The Coupled Model Intercomparison Project (CMIP) multi-model ensemble currently represents the primary data for assessing reliability and uncertainties of climate change information. An alternative approach is to generate similar ensembles by perturbing parameters within a single-model framework. One of workshop’s objectives was to give participants a deeper understanding of these approaches within a Bayesian statistical framework. However, there remain significant challenges still to be resolved before UQ can be applied in a convincing way to climate models and their projections.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

SU-F-J-72: A Clinical Usable Integrated Contouring Quality Evaluation Software for Radiotherapy

Purpose: To introduce the Auto Contour Evaluation (ACE) software, which is the clinical usable, user friendly, efficient and all-in-one toolbox for automatically identify common contouring errors in radiotherapy treatment planning using supervised machine learning techniques. Methods: ACE is developed with C# using Microsoft .Net framework and Windows Presentation Foundation (WPF) for elegant GUI design and smooth GUI transition animations through the integration of graphics engines and high dots per inch (DPI) settings on modern high resolution monitors. The industrial standard software design pattern, Model-View-ViewModel (MVVM) pattern, is chosen to be the major architecture of ACE for neat coding structure, deep modularization, easy maintainability and seamless communication with other clinical software. ACE consists of 1) a patient data importing module integrated with clinical patient database server, 2) a 2D DICOM image and RT structure simultaneously displaying module, 3) a 3D RT structure visualization module using Visualization Toolkit or VTK library and 4) a contour evaluation module using supervised pattern recognition algorithms to detect contouring errors and display detection results. ACE relies on supervised learning algorithms to handle all image processing and data processing jobs. Implementations of related algorithms are powered by Accord.Net scientific computing library for better efficiency and effectiveness. Results: ACE can take patient’s CT images and RT structures from commercial treatment planning software via direct user input or from patients’ database. All functionalities including 2D and 3D image visualization and RT contours error detection have been demonstrated with real clinical patient cases. Conclusion: ACE implements supervised learning algorithms and combines image processing and graphical visualization modules for RT contours verification. ACE has great potential for automated radiotherapy contouring quality verification. Structured with MVVM pattern, it is highly maintainable and extensible, and support smooth connections with other clinical software tools.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

A scalable matrix-free spectral element approach for unsteady PDE constrained optimization using PETSc/TAO

In this work, we provide a new approach for the efficient matrix-free application of the transpose of the Jacobian for the spectral element method for the adjoint-based solution of partial differential equation (PDE) constrained optimization. This results in optimizations of nonlinear PDEs using explicit integrators where the integration of the adjoint problem is not more expensive than the forward simulation. Solving PDE constrained optimization problems entails combining expertise from multiple areas, including simulation, computation of derivatives, and optimization. The Portable, Extensible Toolkit for Scientific computation (PETSc) together with its companion package, the Toolkit for Advanced Optimization (TAO), is an integrated numerical software library that contains an algorithmic/software stack for solving linear systems, nonlinear systems, ordinary differential equations, differential algebraic equations, and large-scale optimization problems and, as such, is an ideal tool for performing PDE-constrained optimization. This paper describes an efficient approach in which the software stack provided by PETSc/TAO can be used for large-scale nonlinear time-dependent problems. Time integration can involve a range of high-order methods, both implicit and explicit. The PDE-constrained optimization algorithm used is gradient-based and seamlessly integrated with the simulation of the physical problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Reliable edge machine learning hardware for scientific applications

Extreme data rate scientific experiments create massive amounts of data that require efficient ML edge processing. This leads to unique validation challenges for VLSI implementations of ML algorithms: enabling bit-accurate functional simulations for performance validation in experimental software frameworks, verifying those ML models are robust under extreme quantization and pruning, and enabling ultra-fine-grained model inspection for efficient fault tolerance. We discuss approaches to developing and validating reliable algorithms at the scientific edge under such strict latency, resource, power, and area requirements in extreme experimental environments. We study metrics for developing robust algorithms, present preliminary results and mitigation strategies, and conclude with an outlook of these and future directions of research towards the longer-term goal of developing autonomous scientific experimentation methods for accelerated scientific discovery.

Baldi, Tommaso↗
DOE OSTI2018

BCS (Beamline Control System) v2

The software is a flexible architecture used to integrate motors, analog data, digital signals, and instruments together to control scientific experiments and collect data during an experiment. The architecture supports features needed by scientists to quickly add new hardware to an experiment and to take and view data in a meaningful way. It does not perform analysis of the data, but provides basic visualization needed to evaluate the quality of the data as well as the calibration of the system.

Cornell, Earl↗
DOE OSTI2024

Electronic Visualization Laboratory's 50th Anniversary Retrospective: Look to the Future, Build on the Past

September 2023 marks the 50th anniversary of the Electronic Visualization Laboratory (EVL) at University of Illinois Chicago (UIC). EVL's introduction of the CAVE Automatic Virtual Environment in 1992, the first widely replicated, projection-based, walk-in, virtual-reality (VR) system in the world, put EVL at the forefront of collaborative, immersive data exploration and analytics. However, the journey did not begin then. Since its founding in 1973, EVL has been developing tools and techniques for real-time, interactive visualizations—pillars of VR. But EVL's culture is also relevant to its successes, as it has always been an interdisciplinary lab that fosters teamwork, where each person's expertise contributes to the development of the necessary tools, hardware, system software, applications, and human interface models to solve problems. Over the years, as multidisciplinary collaborations evolved and advanced scientific instruments and data resources were distributed globally, the need to access and share data and visualizations while working with colleagues, local and remote, synchronous and asynchronous, also became important fields of study. This paper is a retrospective of EVL's past 50 years that surveys the many networked, immersive, collaborative visualization and VR systems and applications it developed and deployed, as well as lessons learned and future plans.

Johnson, Andrew E.↗