Search NASA⌕ Search

SEARCH · Search NASA

Results for “launch software”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Application-level regression testing framework using Jenkins

Monitoring and testing for regression of large-scale systems such as the NCSA's Blue Waters supercomputer are challenging tasks. In this paper, we describe the solution we came up with to perform those tasks. The goal was to find an automated solution for running user-level regression tests to evaluate system usability and performance. Jenkins, an automation server software, was chosen for its versatility, large user base, and multitude of plugins including collecting data and plotting test results over time. We also describe our Jenkins deployment to launch and monitor jobs on remote HPC system, perform authentication with one-time password, and integrate with our LDAP server for its authorization. We show some use cases and describe our best practices for successfully using Jenkins as a user-level system-wide regression testing and monitoring framework for large supercomputer systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

High performance sparse multifrontal solvers on modern GPUs

Here, we have ported the numerical factorization and triangular solve phases of the sparse direct solver STRUMPACK to GPU. STRUMPACK implements sparse LU factorization using the multifrontal algorithm, which performs most of its operations in dense linear algebra operations on so-called frontal matrices of various sizes. Our GPU implementation off-loads these dense linear algebra operations, as well as the sparse scatter–gather operations between frontal matrices. For the larger frontal matrices, our GPU implementation relies on vendor libraries such as cuBLAS and cuSOLVER for NVIDIA GPUs and rocBLAS and rocSOLVER for AMD GPUs. For the smaller frontal matrices we developed custom CUDA and HIP kernels to reduce kernel launch overhead. Overall, high performance is achieved by identifying submatrix factorizations corresponding to sub-trees of the multifrontal assembly tree which fit entirely in GPU memory. The multi-GPU setting uses SLATE (Software for Linear Algebra Targeting Exascale) as a modern GPU-aware replacement for ScaLAPACK. On 4 nodes of SUMMIT the code runs ~10X faster when using all 24 V100 GPUs compared to when it only uses the 168 POWER9 cores. On 8 SUMMIT nodes, using 48 V100 GPUs, the sparse solver reaches over 50TFlop/s. Compared to SuperLU, on a single V100, for a set of 17 matrices our implementation is faster for all but one matrix, and is on average 5X (median 4X) faster

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Modular space vehicle boards, control software, reprogramming, and failure recovery

A space vehicle may have a modular board configuration that commonly uses some or all components and a common operating system for at least some of the boards. Each modular board may have its own dedicated processing, and processing loads may be distributed. The space vehicle may be reprogrammable, and may be launched without code that enables all functionality and/or components. Code errors may be detected and the space vehicle may be reset to a working code version to prevent system failure.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2019

Modular space vehicle boards, control software, reprogramming, and failure recovery

A space vehicle may have a modular board configuration that commonly uses some or all components and a common operating system for at least some of the boards. Each modular board may have its own dedicated processing, and processing loads may be distributed. The space vehicle may be reprogrammable, and may be launched without code that enables all functionality and/or components. Code errors may be detected and the space vehicle may be reset to a working code version to prevent system failure.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Incipient Melting in AA7075

Incipient melting is a phenomenon that can occur in aluminum alloys where solute rich areas, such as grain boundaries, can melt before the rest of the material; incipient melting can degrade mechanical and corrosion properties and is irreversible, resulting in material scrapping. After detecting indications of incipient melting as the cause of failure in 7075 aluminum alloy parts (AA7075), a study was launched to determine threshold temperature for incipient melting. Samples of AA7075 were solution annealed using temperatures ranging from 870-1090F. A hardness profile was developed to demonstrate the loss of mechanical properties through the progression of incipient melting. Additionally, Zeiss software Zen Core Intellesis was utilized to more accurately quantify the changes in microstructural properties as AA7075 surpassed the onset of incipient melting. The results from this study were compared with previous AA7075 material that demonstrated incipient melting.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Influence of Magnetically Conjugate Fragments of Auroral Emission Images on the Accuracy of Determining E{sub av} of Precipitating Electrons

Results of magnetic conjugation of image fragments of auroral emissions at different altitudes along the magnetic field lines and preliminary results of evaluation of their influence on the accuracy of remote mapping of energy characteristics of precipitating electrons are presented. The results are obtained using the code of tracing being an integral part of the software Vector M intended for calculation of accompanying, geophysical, and astronomical information for the center of mass of a space vehicle (SV) and remote observation of aurora by means of Aurovisor-VIS/MP imager onboard the SV Meteor-MP to be launched.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

WIREFRAME: Supporting Data-dependent Parallelism through Dependency Graph Execution in GPUs

GPUs lack fundamental support for data-dependent parallelism and synchronization. While CUDA Dynamic Parallelism signals progress in this direction, many limitations and challenges still re-main. This paper introducesWireframe, a hardware-software solution that enables generalized support for data-dependent parallelism and synchronization. Wireframe enables applications to naturally express execution dependencies across different thread blocks through a dependency graph abstraction at run-time, which is sent to the GPU hardware at kernel launch. At run-time, the hardware enforces the dependencies specified in the dependency graph through a dependency-aware thread block scheduler. Overall, Wireframe is able to improve total execution time up to 65.20% with an average of 45.07%.

Abdolrashidi, AmirAli↗
DOE OSTI2020

Benchmark Modeling and Simulation of the FFTF LOFWOS Test #13 Using SAM

The Fast Flux Test Facility (FFTF) was a 400 MW thermal powered, oxide-fueled, liquid sodium cooled test reactor, built to assist development and testing of advanced fuels and materials for fast breeder reactors. In July 1986, a series of unprotected Loss of Flow Without Scram (LOFWOS) transients were performed in FFTF as part of the Passive Safety Testing (PST) program. The LOFWOS Test #13, which was initiated at 50% power and 100% flow with the pump pony motors left off, has been chosen as a benchmark case by IAEA to support collaborative efforts within international partnerships on the validation of simulation tools and models in the area of sodium fast reactor passive safety in an IAEA Coordinated Research Project (CRP), launched in October 2018. The System Analysis Module (SAM) is an advanced and modern system analysis tool under development at Argonne National Laboratory for advanced non-LWR safety analysis. It utilizes the object-oriented application framework MOOSE to leverage the modern software environment and advanced numerical methods. The capabilities of SAM are being extended to enable the transient modeling, analysis, and design of various advanced nuclear reactor systems. To participate the IAEA CRP and enhance the SAM validation base for advanced reactor transient safety analysis, benchmark simulations of the FFTF LOFWOS Test #13 are performed using the SAM code. In this first phase of the validation effort, the thermal-hydraulic behavior of the reactor system is the focus and the reactor kinetics is not considered in the SAM FFTF model. Instead, the results of Argonne’s neutronics calculations are directly used, including the power shape of the active core region and the power history during the transient. The simulation results of FFTF at steady state agreed well with the measured data from the test. During the transient, reasonably good agreement were also obtained. Future work to improve the model will focus on introducing the reactivity predictions into the model, as well as better understanding or resolving the current discrepancies with the measured data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2017

EnergyPlus™ [SWR-17-23]

Originally developed in 1999, an updated version 8.8.0 with bug fixes was released on September 30th, 2017. EnergyPlus™ is a whole building energy simulation program that engineers, architects, and researchers use to model both energy consumption—for heating, cooling, ventilation, lighting and plug and process loads—and water use in buildings. EnergyPlus is a console-based program that reads input and writes output to text files. It ships with a number of utilities including IDF-Editor for creating input files using a simple spreadsheet-like interface, EP-Launch for managing input and output files and performing batch simulations, and EP-Compare for graphically comparing the results of two or more simulations. Several comprehensive graphical interfaces for EnergyPlus are also available. DOE does most of its work with EnergyPlus using the OpenStudio® software development kit and suite of applications. DOE releases major updates to EnergyPlus twice annually.

Source record↗
DOE OSTI2026

MADA: Multi-Agent Design Assistant

MADA (Multi-Agent Design Assistant) is a Large Language Model (LLM) powered multi-agent framework that coordinates specialized agents for complex design workflows. The system was designed for HPC workflows with the following agents in mind: 1) A Job Management Agent (JMA) launches and manages ensemble simulations on HPC systems, 2) a Geometry Agent (GA) generates meshes, and 3) an Inverse Design Agent (IDA) proposes new designs informed by simulation outcomes. Our framework reduces cumbersome manual workflow setup, and enables automated design exploration at scale. However, the software also enables users to rapidly create new multi-agent systems. Simply define new agents in a configuration file, giving each their own set of tools (via MCP), and then chat and prompt your new multi-agent system. Is

Gunnarson, BrianS [Lawrence Livermore National Lab↗
DOE OSTI2017

EnergyPlus™

Originally developed in 1999, an updated version 8.8.0 with bug fixes was released on September 30th, 2017. EnergyPlus™ is a whole building energy simulation program that engineers, architects, and researchers use to model both energy consumption—for heating, cooling, ventilation, lighting and plug and process loads—and water use in buildings. EnergyPlus is a console-based program that reads input and writes output to text files. It ships with a number of utilities including IDF-Editor for creating input files using a simple spreadsheet-like interface, EP-Launch for managing input and output files and performing batch simulations, and EP-Compare for graphically comparing the results of two or more simulations. Several comprehensive graphical interfaces for EnergyPlus are also available. DOE does most of its work with EnergyPlus using the OpenStudio® software development kit and suite of applications. DOE releases major updates to EnergyPlus twice annually.

Source record↗
DOE OSTI2021

Added Value for Integrated Marine Energy Data Systems (February 2021)

Launched in 2019, the Portal and Repository for Information on Marine Renewable Energy (PRIMRE) provides centralized access, standardization, community building, and integration of United States (U.S.) databases, tools and codes, and other resources that cover a range of marine energy information. The PRIMRE universe contains a series of Knowledge Hubs that represent data and information on testing of marine energy devices (MHKDR); environmental effects (Tethys); engineering and technical papers (Tethys Engineering); descriptions of marine energy companies and technologies (Marine Energy Projects Database); codes and models (Marine Energy Software); and guidance on testing and measurements (Telesto). Content is added to PRIMRE by applying a set of Guidelines and Best Practices (PRIMRE Guidelines). An aggregate search across the PRIMRE site enables users to find data and information from all the PRIMRE Knowledge Hubs simultaneously, using a single entry-point (PRIMRE Search). In addition to providing access to a range of data and information on marine energy development, testing, and effects, PRIMRE allows for the development of valueadded products and processes that will help move the marine energy industry forward. The PRIMRE team has recently launched two key initiatives in the U.S.-Signature Projects and Lessons Learned. Outputs and outcomes from these two initiatives will be highlighted in this paper. The Signature Projects initiative is intended to bring focus to a selection of ongoing and completed marine energy projects funded by the U.S. Department of Energy's Water Power Technologies Office (WPTO), and to inform the marine energy community of what investigations have been undertaken, what tools are available, and where gaps in information persist. Each Signature Project tags papers, reports, and data from large marine energy research projects, providing easy access and attention to all the output and associated products from each project. The Lessons Learned initiative is intended to ensure that hard-won achievements are recognized and available for those who come later, that missteps and unfortunate outcomes can be prevented in future, and that efficiencies and effective shortcuts can be publicized and used as the marine energy industry moves forward. This initiative builds off the Knowledge Hubs and reaches out to members of the marine energy community, particularly technology developers and researchers, to integrate experience in the development, deployment, assessment, success, challenges while creating this new industry and field of study.

data sharing↗
DOE OSTI2021

Added value for integrated marine energy data systems

Launched in 2019, the Portal and Repository for Information on Marine Renewable Energy (PRIMRE) provides centralized access, standardization, community building, and integration of United States (U.S.) databases, tools and codes, and other resources that cover a range of marine energy information. The PRIMRE universe contains a series of Knowledge Hubs that represent data and information on testing of marine energy devices (MHKDR); environmental effects (Tethys); engineering and technical papers (Tethys Engineering); descriptions of marine energy companies and technologies (Marine Energy Projects Database); codes and models (Marine Energy Software); and guidance on testing and measurements (Telesto). Content is added to PRIMRE by applying a set of Guidelines and Best Practices (PRIMRE Guidelines). An aggregate search across the PRIMRE site enables users to find data and information from all the PRIMRE Knowledge Hubs simultaneously, using a single entry-point (PRIMRE Search). In addition to providing access to a range of data and information on marine energy development, testing, and effects, PRIMRE allows for the development of value added products and processes that will help move the marine energy industry forward. The PRIMRE team has recently launched two key initiatives in the U.S.—Signature Projects and Lessons Learned. Outputs and outcomes from these two initiatives will be highlighted in this paper. The Signature Projects initiative is intended to bring focus to a selection of ongoing and completed marine energy projects funded by the U.S. Department of Energy’s Water Power Technologies Office (WPTO), and to inform the marine energy community of what investigations have been undertaken, what tools are available, and where gaps in information persist. Each Signature Project tags papers, reports, and data from large marine energy research projects, providing easy access and attention to all the output and associated products from each project. The Lessons Learned initiative is intended to ensure that hard-won achievements are recognized and available for those who come later, that missteps and unfortunate outcomes can be prevented in future, and that efficiencies and effective shortcuts can be publicized and used as the marine energy industry moves forward. This initiative builds off the Knowledge Hubs and reaches out to members of the marine energy community, particularly technology developers and researchers, to integrate experience in the development, deployment, assessment, success, and challenges while creating this new industry and field of study.

Copping, Andrea E.↗
DOE OSTI2021

Added value for integrated marine energy data systems

Launched in 2019, the Portal and Repository for Information on Marine Renewable Energy (PRIMRE) provides centralized access, standardization, community building, and integration of United States (U.S.) databases, tools and codes, and other resources that cover a range of marine energy information. The PRIMRE universe contains a series of Knowledge Hubs that represent data and information on testing of marine energy devices (MHKDR); environmental effects (Tethys); engineering and technical papers (Tethys Engineering); descriptions of marine energy companies and technologies (Marine Energy Projects Database); codes and models (Marine Energy Software); and guidance on testing and measurements (Telesto). Content is added to PRIMRE by applying a set of Guidelines and Best Practices (PRIMRE Guidelines). An aggregate search across the PRIMRE site enables users to find data and information from all the PRIMRE Knowledge Hubs simultaneously, using a single entry-point (PRIMRE Search). In addition to providing access to a range of data and information on marine energy development, testing, and effects, PRIMRE allows for the development of value added products and processes that will help move the marine energy industry forward. The PRIMRE team has recently launched two key initiatives in the U.S.—Signature Projects and Lessons Learned. Outputs and outcomes from these two initiatives will be highlighted in this paper. The Signature Projects initiative is intended to bring focus to a selection of ongoing and completed marine energy projects funded by the U.S. Department of Energy’s Water Power Technologies Office (WPTO), and to inform the marine energy community of what investigations have been undertaken, what tools are available, and where gaps in information persist. Each Signature Project tags papers, reports, and data from large marine energy research projects, providing easy access and attention to all the output and associated products from each project. The Lessons Learned initiative is intended to ensure that hard-won achievements are recognized and available for those who come later, that missteps and unfortunate outcomes can be prevented in future, and that efficiencies and effective shortcuts can be publicized and used as the marine energy industry moves forward. This initiative builds off the Knowledge Hubs and reaches out to members of the marine energy community, particularly technology developers and researchers, to integrate experience in the development, deployment, assessment, success, and challenges while creating this new industry and field of study.

Copping, Andrea E.↗
DOE OSTI2025

MPACT Safeguards Modeling: FY25 Update

Sandia National Laboratories develops and maintains several open-source software packages to support material accountancy analyses. This includes the Material Accountancy Performance Indicator Toolkit (MAPIT), the Fissile Facility Flow Modeler (F3M) and the Separation and Safeguards Performance Model Library (SSPM-L). MAPIT is responsible for performing statistical safeguards analyses on bulk and itemized data from nuclear fuel cycle facilities and can operate on real or synthetic data. MAPIT is the only open-source software for such analyses. F3M is a library of modules, built in MATLAB Simulink, that contain pre made blocks to represent different generic fuel cycle processes. These blocks can be used together in a modular fashion to represent and simulate nuclear fuel cycle processes with the goal of improving facility-level accountancy during the design phase. F3M is also an open-source library. Finally, the SSPM-L library is a series of completed models built from F3M. The library includes facility models such as a generic PUREX facility and a fuel fabrication facility. The SSPM-L library is not open source, but is available to collaborators with a relevant use case. These tools include modeling and simulation pipelines to simulate nuclear fuel cycle facilities and the underlying software needed to simulate measurement uncertainty and perform statistical analyses. Together, these tools can perform end-to-end nuclear material accountancy analyses. This report documents the various improvements made to these tools in FY25. Specifically, we added new statistical test, new statistical modeling capabilities, new fuel cycle facility models, and launched a new open-source model component library.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

High-throughput ab initio reaction mechanism exploration in the cloud with automated multi-reference validation

Quantum chemical calculations on atomistic systems have evolved into a standard approach to studying molecular matter. These calculations often involve a significant amount of manual input and expertise, although most of this effort could be automated, which would alleviate the need for expertise in software and hardware accessibility. Here, we present the AutoRXN workflow, an automated workflow for exploratory high-throughput electronic structure calculations of molecular systems, in which (i) density functional theory methods are exploited to deliver minimum and transition-state structures and corresponding energies and properties, (ii) coupled cluster calculations are then launched for optimized structures to provide more accurate energy and property estimates, and (iii) multi-reference diagnostics are evaluated to back check the coupled cluster results and subject them to automated multi-configurational calculations for potential multi-configurational cases. All calculations are carried out in a cloud environment and support massive computational campaigns. Key features of all components of the AutoRXN workflow are autonomy, stability, and minimum operator interference. We highlight the AutoRXN workflow with the example of an autonomous reaction mechanism exploration of the mode of action of a homogeneous catalyst for the asymmetric reduction of ketones.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

A Need for Better Management of Heterogenous HPC Resources

Achieving computational rates beyond the petascale requires an increasing amount of heterogeneity in our highperformance computing (HPC) hardware. This heterogeneity, in turn, means that a node of an HPC system can no longer be considered a monolithic resource. Rather, a node has many individual components such as processors, cores, SMT threads, accelerators, and tierd memories that must be further allocated and managed by... something. Currently, that something is an ad-hoc mix of arguments and environments when launching jobs. We follow the same process used on prior HPC systems with nodes of uniform components; unfortunately, the shims introduced to provide the additional specification of node-level components are inconsistent and unwieldy. As we shall see, even at our current moderate level of heterogeneity our effective utilization of HPC software is hampered by poor resource management. Future systems will continue to grow in heterogeneity both in number and type of resources. Our current approach to resource management cannot scale. We need a more cohesive approach to managing heterogeneous resources in HPC systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Accelerated data-driven materials science with the Materials Project

The Materials Project was launched formally in 2011 to drive materials discovery forwards through high-throughput computation and open data. More than a decade later, the Materials Project has become an indispensable tool used by more than 600,000 materials researchers around the world. This Perspective describes how the Materials Project, as a data platform and a software ecosystem, has helped to shape research in data-driven materials science. We cover how sustainable software and computational methods have accelerated materials design while becoming more open source and collaborative in nature. Next, we present cases where the Materials Project was used to understand and discover functional materials. We then describe our efforts to meet the needs of an expanding user base, through technical infrastructure updates ranging from data architecture and cloud resources to interactive web applications. Finally, we discuss opportunities to better aid the research community, with the vision that more accessible and easy-to-understand materials data will result in democratized materials knowledge and an increasingly collaborative community.

Horton, Matthew K↗