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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Development of a Multi-Disciplinary Computing Environment (MDICE)

The growing need for and importance of multi-component and multi-disciplinary engineering analysis has been understood for many years. For many applications, loose (or semi-implicit) coupling is optimal, and allows the use of various legacy codes without requiring major modifications. For this purpose, CFDRC and NASA LeRC have developed a computational environment to enable coupling between various flow analysis codes at several levels of fidelity. This has been referred to as the Visual Computing Environment (VCE), and is being successfully applied to the analysis of several aircraft engine components. Recently, CFDRC and AFRL/VAAC (WL) have extended the framework and scope of VCE to enable complex multi-disciplinary simulations. The chosen initial focus is on aeroelastic aircraft applications. The developed software is referred to as MDICE-AE, an extensible system suitable for integration of several engineering analysis disciplines. This paper describes the methodology, basic architecture, chosen software technologies, salient library modules, and the current status of and plans for MDICE. A fluid-structure interaction application is described in a separate companion paper.

Kingsley, Gerry↗
NASA NTRS2003

A Performance Evaluation of the Cray X1 for Scientific Applications

The last decade has witnessed a rapid proliferation of superscalar cache-based microprocessors to build high-end capability and capacity computers because of their generality, scalability, and cost effectiveness. However, the recent development of massively parallel vector systems is having a significant effect on the supercomputing landscape. In this paper, we compare the performance of the recently-released Cray X1 vector system with that of the cacheless NEC SX-6 vector machine, and the superscalar cache-based IBM Power3 and Power4 architectures for scientific applications. Overall results demonstrate that the X1 is quite promising, but performance improvements are expected as the hardware, systems software, and numerical libraries mature. Code reengineering to effectively utilize the complex architecture may also lead to significant efficiency enhancements.

Oliker, Leonid↗
NASA NTRS2004

A Performance Evaluation of the Cray X1 for Scientific Applications

The last decade has witnessed a rapid proliferation of superscalar cache-based microprocessors to build high-end capability and cost effectiveness. However, the recent development of massively parallel vector systems is having a significant effect on the supercomputing landscape. In this paper, we compare the performance of the recently released Cray X1 vector system with that of the cacheless NEC SX-6 vector machine, and the superscalar cache-based IBM Power3 and Power4 architectures for scientific applications. Overall results demonstrate that the X1 is quite promising, but performance improvements are expected as the hardware, systems software, and numerical libraries mature. Code reengineering to effectively utilize the complex architecture may also lead to significant efficiency enhancements.

Oliker, Leonid↗
NASA NTRS2011

Asynchronous Message Service Reference Implementation

This software provides a library of middleware functions with a simple application programming interface, enabling implementation of distributed applications in conformance with the CCSDS AMS (Consultative Committee for Space Data Systems Asynchronous Message Service) specification. The AMS service, and its protocols, implement an architectural concept under which the modules of mission systems may be designed as if they were to operate in isolation, each one producing and consuming mission information without explicit awareness of which other modules are currently operating. Communication relationships among such modules are self-configuring; this tends to minimize complexity in the development and operations of modular data systems. A system built on this model is a society of generally autonomous, inter-operating modules that may fluctuate freely over time in response to changing mission objectives, modules functional upgrades, and recovery from individual module failure. The purpose of AMS, then, is to reduce mission cost and risk by providing standard, reusable infrastructure for the exchange of information among data system modules in a manner that is simple to use, highly automated, flexible, robust, scalable, and efficient. The implementation is designed to spawn multiple threads of AMS functionality under the control of an AMS application program. These threads enable all members of an AMS-based, distributed application to discover one another in real time, subscribe to messages on specific topics, and to publish messages on specific topics. The query/reply (client/server) communication model is also supported. Message exchange is optionally subject to encryption (to support confidentiality) and authorization. Fault tolerance measures in the discovery protocol minimize the likelihood of overall application failure due to any single operational error anywhere in the system. The multi-threaded design simplifies processing while enabling application nodes to operate at high speeds; linked lists protected by mutex semaphores and condition variables are used for efficient, inter-thread communication. Applications may use a variety of transport protocols underlying AMS itself, including TCP (Transmission Control Protocol), UDP (User Datagram Protocol), and message queues.

Burleigh, Scott C.↗
NASA NTRSDate not supplied

Assessing Alaskan boreal forest landcover affected by climate-wildfire interactions from ground truth surveys and NASA airborne remote sensing

Alaska’s boreal forest is facing unprecedented challenges under rapid climate warming (increasingly severe fires, droughts, pest/disease outbreaks) that may destabilize its function as a global carbon sink. Forests near Fairbanks may be especially vulnerable, impacting air quality and ecosystem services. We combined GT (ground truthing) with Airborne Visible InfraRed Imaging Spectrometer (AVIRIS-NG) images collected by the NASA Arctic-Boreal Vulnerability Experiment (ABoVE) program (2017-2019) to assess landcover change at five recently burned sites (2001-2019) of different fire severities and moisture regimes within 30 miles of Fairbanks. GT included tree seedling counts, understory % cover and >50% leaf canopy color assessment. 36 circular plots (1/30 ha radius) including 6 moderate to severely burned plots were selected across sites. 31 additional sites including 12 burned sites were geotagged in photos. AVIRIS images were processed from 29 spectral bands selected to identify changes in chlorophyll and water content. Images were segmented into natural boundaries (polygons) using ENVI 5.5 software. A spectral library of 8 AVIRIS bands with high between-class/low within-class variation was used in two random forest models to predict vegetation classes (model 1: 12 classes, model 2: 14 classes) in each AVIRIS scene, using 20% of the data as training data. Model 2 classified 20% more polygons overall, but only 42% of GT/geotagged polygons were correctly classified by both models. More forest sites were correctly classified (63%) than open vegetation (32%) or post-fire sites (46%). 50% of aspen forest and post-fire polygons were misclassified as shrubland. GT revealed that post-fire plots supported 134,000 (± 48,000) tree seedlings and saplings ha-1 (0.2 - 4 m height, 64% deciduous) versus 2500 (± 2100) shrubs ha-1 (1-6 m height). > 50% canopy browning was observed in conifer forest (8 plots) with no signs of insect infestation. Canopy herbivory > 50% (leaf miner, leaf beetle) and moose herbivory of tree bark was seen across aspen sites. Our study suggests: 1) low canopy vegetation presents challenges for improved landcover classification, and 2) aspen forest should be differentiated in vegetation maps which would aid in tracking herbivory.

Alaska↗
NASA NTRSDate not supplied

Mission Operations, Cubed: NASA Marshall Operations Support for SmallSats

SmallSats have come a long way since the Huntsville Operations Support Center (HOSC) at NASA’s Marshall Space Flight Center supported its first “minisatellite” mission in 2010. And just as SmallSats themselves have evolved in those 12 years, so too has the HOSC’s mission support for SmallSats. Marshall Space Flight Center has a long history with payload and mission operations, including support for the Apollo missions to the moon, the Space Shuttle program, and 21 years of continuous around-the-clock science operations support for research aboard the International Space Station. Today, the HOSC is a multi-tenant facility, supporting not only ISS, but also NASA’s Commercial Crew program, the Space Launch System, the Hubble and Chandra observatories and others – including multiple SmallSat missions. Two SmallSat solar sail missions will be among those taking advantage of the HOSC’s resources for planning, training for and executing mission operations – the Near Earth Asteroid (NEA) Scout and Solar Cruiser missions. One of 10 6U CubeSats manifest on the Artemis I launch of NASA’s Space Launch System rocket this year, NEA Scout’s three-year mission will be supported through a more traditional operations concept, with a dedicated Flight Controller staff operating within the HOSC. Scheduled to launch as part of the Interstellar Mapping and Acceleration Probe (IMAP) in February 2025, Solar Cruiser’s 11-month mission will take a next-generation approach to operations by utilizing a multi-mission flight controller concept, as well as Marshall’s Telescience Resource Kit (TreK). TreK provides a suite of software applications and libraries that allow the Mission Operations Center to serve as an in-house ground system which incorporates remote and automation capability options for engineers and scientists. This presentation will compare the approaches the HOSC will use to support these two missions as a way of demonstrating the array of options NASA MSFC offers for operations support for CubeSat and SmallSat missions.

Darren S Wallace↗
DOE OSTI2016

Universal Number Library

This floating-point arithmetic library contains a software implementation of Universal Numbers (unums) as described by John Gustafson [1]. The unum format is a superset of IEEE 754 floating point with several advantages. Computing with unums provides more accurate answers without rounding errors, underflow or overflow. In contrast to fixed-sized IEEE numbers, a variable number of bits can be used to encode unums. This all allows number with only a few significant digits or with a small dynamic range to be represented more compactly.

Lloyd, G. Scott↗
NASA NTRS2005

Data-Acquisition Software for PSP/TSP Wind-Tunnel Cameras

Wing-Viewer is a computer program for acquisition and reduction of image data acquired by any of five different scientificgrade commercial electronic cameras used at Langley Research center to observe wind-tunnel models coated with pressure or temperature-sensitive paints (PSP/TSP). Wing-Viewer provides full automation of camera operation and acquisition of image data, and has limited data-preprocessing capability for quick viewing of the results of PSP/TSP test images. Wing- Viewer satisfies a requirement for a standard interface between all the cameras and a single personal computer: Written by use of Microsoft Visual C++ and the Microsoft Foundation Class Library as a framework, Wing-Viewer has the ability to communicate with the C/C++ software libraries that run on the controller circuit cards of all five cameras.

Amer, Tahani R.↗
NASA NTRS1989

AdaNET services

MountainNet is a small firm which serves as a distribution center for AdaNET Services. These services include providing host systems and telecommunications for AdaNET, developing and supporting AdaNET Information Services, and developing a dynamic software inventory. AdaNET hosts are a Data General MV8000II and DEC VAX. Telecommunications are provided via the MountainNet private network and the Telenet public access dial network. Initially, the AdaNET Information Services will include software repositories, user communications and forums, software engineering information, bibliographic and library services, and an educational directory. The dynamic software inventory, which will become available in January 1990, will contain software engineering code and parts.

Digman, Michael↗
DOE OSTI2017

xSDK Foundations: Toward an Extreme-scale Scientific Software Development Kit

Here, extreme-scale computational science increasingly demands multiscale and multiphysics formulations. Combining software developed by independent groups is imperative: no single team has resources for all predictive science and decision support capabilities. Scientific libraries provide high-quality, reusable software components for constructing applications with improved robustness and portability. However, without coordination, many libraries cannot be easily composed. Namespace collisions, inconsistent arguments, lack of third-party software versioning, and additional difficulties make composition costly. The Extreme-scale Scientific Software Development Kit (xSDK) defines community policies to improve code quality and compatibility across independently developed packages (hypre, PETSc, SuperLU, Trilinos, and Alquimia) and provides a foundation for addressing broader issues in software interoperability, performance portability, and sustainability. The xSDK provides turnkey installation of member software and seamless combination of aggregate capabilities, and it marks first steps toward extreme-scale scientific software ecosystems from which future applications can be composed rapidly with assured quality and scalability.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

The Minos Computing Library: Efficient Parallel Programming for Extremely Heterogeneous Systems

Hardware specialization has become the silver bullet to achieve efficient high performance, from Systems-on-Chip systems, where hardware specialization can be ``extreme'', to large-scale HPC systems. As the complexity of the systems increases, so does the complexity of programming such architectures in a portable way. This work introduces the Minos Computing Library (MCL), as system software, programming model, and programming model runtime that facilitate programming extremely heterogeneous systems. MCL supports the execution of several multi-threaded applications within the same compute node, performs asynchronous execution of application tasks, efficiently balances computation across hardware resources, and provides performance portability. We show that code developed on a personal desktop automatically scales up to fully utilize powerful workstations with 8 GPUs and down to power-efficient embedded systems. MCL provides up to 17.5x speedup over OpenCL on NVIDIA DGX-1 systems and up to 1.88x speedup on single-GPU systems. In multi-application workloads, MCL dynamically resource allocation provides up to 2.43x performance improvement over manual, static allocation of computing resources.

Gioiosa, Roberto↗
DOE OSTI2020

Better together: Elements of successful scientific software development in a distributed collaborative community

Many scientific disciplines rely on computational methods for data analysis, model generation, and prediction. Implementing these methods is often accomplished by researchers with domain expertise but without formal training in software engineering or computer science. This arrangement has led to underappreciation of sustainability and maintainability of scientific software tools developed in academic environments. Some software tools have avoided this fate, including the scientific library Rosetta. We use this software and its community as a case study to show how modern software development can be accomplished successfully, irrespective of subject area. Rosetta is one of the largest software suites for macromolecular modeling, with 3.1 million lines of code and many state-of-the-art applications. Since the mid 1990s, the software has been developed collaboratively by the RosettaCommons, a community of academics from over 60 institutions worldwide with diverse backgrounds including chemistry, biology, physiology, physics, engineering, mathematics, and computer science. Developing this software suite has provided us with more than two decades of experience in how to effectively develop advanced scientific software in a global community with hundreds of contributors. Here we illustrate the functioning of this development community by addressing technical aspects (like version control, testing, and maintenance), community-building strategies, diversity efforts, software dissemination, and user support. We demonstrate how modern computational research can thrive in a distributed collaborative community. The practices described here are independent of subject area and can be readily adopted by other software development communities

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

PROTEUS: Machine Learning Driven Resilience for Extreme-scale Systems

The objective of this project is to design, develop, and evaluate scalable software to enhance resilience, data checkpointing, program restart, and analysis. The proposed tasks are to 1) develop scalable machine learning techniques to learn temporal change patterns in a scalable and in-situ manner, and to minimize data movement and maximize learning locally closest to data; 2) design a concise data representation and indexing mechanism to capture the distribution of changes in data that can guarantee point-wise user-defined tolerable errors while reducing the data storage requirements by an order of magnitude or more; 3) develop data reduction techniques as library modules; 4) exploit local SSD for minimizing data movement in storage hierarchy; 5) develop anomaly detection algorithms that can predict corruptions based on learning of emerging patterns; 6) develop software libraries to be incorporated within widely used data formats and APIs; and 7) evaluate the proposed software using DOE scientific applications. The outcomes of the proposed work are to satisfy many synergistic data reduction and resilience requirements for large-scale data intensive applications executed on extreme-scale computing systems. The developed mechanism for error-bound data approximation is directly applicable to existing scientific applications. Through machine learning from historical events and change distribution, this work will enable anomaly detection for DOE computer facility.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

HDF5 in the exascale era: Delivering efficient and scalable parallel I/O for exascale applications

Accurately modeling real-world systems requires scientific applications at exascale to generate massive amounts of data and manage data storage efficiently. However, parallel input and output (I/O) faces challenges due to new application workflows and the state-of-the-art memory, interconnect, and storage architectures considered in exascale designs. The storage hierarchy has expanded with node-local persistent memory, solid-state storage, and traditional disk and tape-based storage, thus requiring efficiency at each layer and much more efficient data movement among these layers. This paper discusses how the ExaHDF5 project improved the I/O performance and data management for exascale architectures by enhancing HDF5, a widely used parallel I/O library. The team developed an Asynchronous I/O Virtual Object Layer (VOL) connector that allowed overlapping I/O with computation. They also created a Cache VOL to complement asynchronous I/O by incorporating fast storage layers, such as burst buffer and node-local storage, into the parallel I/O workflow through caching and staging data. Additionally, the team enabled data aggregation and I/O at the node level by using a Subfiling Virtual File Driver (VFD). To demonstrate superior I/O performance with HDF5 at exascale, the ExaHDF5 team collaborated with several exascale applications. In this paper, we show I/O performance improvements for three applications: Cabana (a particle-based simulation library), EQSIM (a regional earthquake simulation software), and E3SM (a climate system modeling library).

Asynchronous I/Ol↗
NASA NTRS1996

Evolving the Reuse Process at the Flight Dynamics Division (FDD) Goddard Space Flight Center

This paper presents the interim results from the Software Engineering Laboratory's (SEL) Reuse Study. The team conducting this study has, over the past few months, been studying the Generalized Support Software (GSS) domain asset library and architecture, and the various processes associated with it. In particular, we have characterized the process used to configure GSS-based attitude ground support systems (AGSS) to support satellite missions at NASA's Goddard Space Flight Center. To do this, we built detailed models of the tasks involved, the people who perform these tasks, and the interdependencies and information flows among these people. These models were based on information gleaned from numerous interviews with people involved in this process at various levels. We also analyzed effort data in order to determine the cost savings in moving from actual development of AGSSs to support each mission (which was necessary before GSS was available) to configuring AGSS software from the domain asset library. While characterizing the GSS process, we became aware of several interesting factors which affect the successful continued use of GSS. Many of these issues fall under the subject of evolving technologies, which were not available at the inception of GSS, but are now. Some of these technologies could be incorporated into the GSS process, thus making the whole asset library more usable. Other technologies are being considered as an alternative to the GSS process altogether. In this paper, we outline some of issues we will be considering in our continued study of GSS and the impact of evolving technologies.

Condon, S.↗
DOE OSTI2021

Productive Programming of Distributed Systems with the SHAD C++ Library

High-performance computing (HPC) is often perceived as a matter of making large-scale systems (e.g., clusters) run as fast as possible, regardless the required programming effort. However, the idea of "bringing HPC to the masses" has recently emerged. Inspired by this vision, we have designed SHAD, the Scalable High-performance Algorithms and Data-structures library. SHAD is open source software, written in C++, for C++ developers. Unlike other HPC libraries for distributed systems, which rely on SPMD models, SHAD adopts a shared-memory programming abstraction, to make C++ programmers feel at home. Underneath, SHAD manages tasking and data-movements, moving the computation where data resides and taking advantage of asynchrony to tolerate network latency. At the bottom of his stack, SHAD can interface with multiple runtime systems: this not only improves developer’s productivity, by hiding the complexity of such software and of the underlying hardware, but also greatly enhance code portability. Thanks to its abstraction layers, SHAD can indeed target different systems, ranging from laptops to HPC clusters, without any need for modifying the user-level code. We have prototyped and open-sourced the implementation of (a subset of) the C++ standard library (STL) targeting multi-node HPC clusters. Our work allows plain STL-based C++ code to scale on HPC systems, with no need for rewriting the code to exploit the complex hardware. SHAD is available under Apache v2 License at https://github.com/pnnl/SHAD. In this paper we overview the design of the SHAD library, depicting its main components: runtime systems abstractions for tasking; parallel and distributed data-structures; STL-compliant interfaces and algorithms.

Castellana, Vito G.↗
DOE OSTI2017

A data model of the Climate and Forecast metadata conventions (CF-1.6) with a software implementation (cf-python v2.1)

Abstract. The CF (Climate and Forecast) metadata conventions are designed to promote the creation, processing, and sharing of climate and forecasting data using Network Common Data Form (netCDF) files and libraries. The CF conventions provide a description of the physical meaning of data and of their spatial and temporal properties, but they depend on the netCDF file encoding which can currently only be fully understood and interpreted by someone familiar with the rules and relationships specified in the conventions documentation. To aid in development of CF-compliant software and to capture with a minimal set of elements all of the information contained in the CF conventions, we propose a formal data model for CF which is independent of netCDF and describes all possible CF-compliant data. Because such data will often be analysed and visualised using software based on other data models, we compare our CF data model with the ISO 19123 coverage model, the Open Geospatial Consortium CF netCDF standard, and the Unidata Common Data Model. To demonstrate that this CF data model can in fact be implemented, we present cf-python, a Python software library that conforms to the model and can manipulate any CF-compliant dataset.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

SynBio QC-Library QC (LibQC) v2.0.0

This software is a pipeline used to identify the distribution of user-specified sequences in oligo pools that have been sequenced on the MiSeq platform for quality control purposes. The software counts instances of user-specified sequences (inserts or spacers) identified in sequencing data, returning the distribution of sequences in each pool and the length distribution of all the sequences. Among other types similar types of projects, this can be used to assess the quality of a guideRNA library once it has been inserted into the vector of choice to ensure that there is an even distribution of all the individual protospacers in the pool. This pipeline uses many freely available open source libraries, the value added is that in our application the steps of the pipeline are defined in Workflow Description Language (WDL) and run through the Cromwell workflow engine in Docker containers, for easy distribution and set up.

Simirenko, Lisa↗