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NASA NTRS2018

Earth Science Deep Learning: Applications and Lessons Learned

Deep learning has revolutionized computer vision and natural language processing with various algorithms scaled using high-performance computing. At the NASA Marshall Space Flight Center (MSFC), the Data Science and Informatics Group (DSIG) has been using deep learning for a variety of Earth science applications. This paper provides examples of the applications and also addresses some of the challenges that were encountered.

Training↗

NASA NTRS1993

Space station static and dynamic analyses using parallel methods

Algorithms for high-performance parallel computers are applied to perform static analyses of large-scale Space Station finite-element models (FEMs). Several parallel-vector algorithms under development at NASA Langley are assessed. Sparse matrix solvers were found to be more efficient than banded symmetric or iterative solvers for the static analysis of large-scale applications. In addition, new sparse and 'out-of-core' solvers were found superior to substructure (superelement) techniques which require significant additional cost and time to perform static condensation during global FEM matrix generation as well as the subsequent recovery and expansion. A method to extend the fast parallel static solution techniques to reduce the computation time for dynamic analysis is also described. The resulting static and dynamic algorithms offer design economy for preliminary multidisciplinary design optimization and FEM validation against test modes. The algorithms are being optimized for parallel computers to solve one-million degrees-of-freedom (DOF) FEMs. The high-performance computers at NASA afforded effective software development, testing, efficient and accurate solution with timely system response and graphical interpretation of results rarely found in industry. Based on the author's experience, similar cooperation between industry and government should be encouraged for similar large-scale projects in the future.

Gupta, V.↗

NASA NTRSDate not supplied

Enabling Reliable, Fault-Tolerant Autonomous Lunar Habitats with High-Performance Spaceflight Computing

The lunar surface presents unfavorable constraints and harsh living conditions. To address these challenges, autonomous habitats will require complex integrated systems that combine advanced software, high-performance hardware, and cutting-edge sensors to ensure sustainability, safety, and operational efficiency. Consequently, maintaining a sustainable presence on the Moon requires reliable infrastructure and efficient development, precise monitoring, and utilization of resources within a lunar installation. These elements are essential not only to ensure that lunar settlement can be long-term, self-sustaining, and resource-efficient, but also to serve as a foundation for future missions and eventual human habitation on Mars. Humans are not native to the Moon; therefore, our survival and ability to thrive will depend on autonomous systems that can foster safety and resilience through high-availability architectures, graceful degradation, and highly fault-tolerant spaceflight hardware capable of continuing operation during failures. This requires advanced human-rated distributed systems architectures with specialized electronics, scalable capabilities, and an integrated design approach. Unlike current practices focused on short-term missions and regularly maintained components, permanent lunar compute systems must be designed for extended operations beyond mission durations. This paper explores the necessity of transitioning toward fault- tolerant, highly autonomous hardware systems designed for multi-year missions. It also identifies critical subsystems that require high levels of autonomy, supported by radiation-hardened processors and extreme thermal loads, which are essential to mitigate long-term degradation and ensure sustainable lunar habitation. Finally, the paper aligns with NASA’s identified Civil Space Shortfalls, particularly in high-performance onboard computing, advanced data acquisition, extreme-environment avionics, radiation monitoring and countermeasures, and autonomous health management. It proposes NASA’s new High-Performance Spaceflight Computing (HPSC) processor as a turnkey solution, delivering 100 times the performance-per-watt of legacy rad-hard CPUs and enabling onboard AI, edge computing, and fault-tolerant features essential for sustained lunar autonomy and beyond.

Sarkis S Mikaelian↗

NASA NTRS1998

The SGI/Cray T3E: Experiences and Insights

The NASA Goddard Space Flight Center is home to the fifth most powerful supercomputer in the world, a 1024 processor SGI/Cray T3E-600. The original 512 processor system was placed at Goddard in March, 1997 as part of a cooperative agreement between the High Performance Computing and Communications Program's Earth and Space Sciences Project (ESS) and SGI/Cray Research. The goal of this system is to facilitate achievement of the Project milestones of 10, 50 and 100 GFLOPS sustained performance on selected Earth and space science application codes. The additional 512 processors were purchased in March, 1998 by the NASA Earth Science Enterprise for the NASA Seasonal to Interannual Prediction Project (NSIPP). These two "halves" still operate as a single system, and must satisfy the unique requirements of both aforementioned groups, as well as guest researchers from the Earth, space, microgravity, manned space flight and aeronautics communities. Few large scalable parallel systems are configured for capability computing, so models are hard to find. This unique environment has created a challenging system administration task, and has yielded some insights into the supercomputing needs of the various NASA Enterprises, as well as insights into the strengths and weaknesses of the T3E architecture and software. The T3E is a distributed memory system in which the processing elements (PE's) are connected by a low latency, high bandwidth bidirectional 3-D torus. Due to the focus on high speed communication between PE's, the T3E requires PE's to be allocated contiguously per job. Further, jobs will only execute on the user specified number of PE's and PE timesharing is possible but impractical. With a highly varied job mix in both size and runtime of jobs, the resulting scenario is PE fragmentation and an inability to achieve near 100% utilization. SGI/Cray has provided several scheduling and configuration tools to minimize the impact of fragmentation. These tools include PScheD (the political scheduler), GRM (the global resource manager) and NQE (the Network Queuing Environment). Features and impact of these tools will be discussed, as will resulting performance and utilization data. As a distributed memory system, the T3E is designed to be programmed through explicit message passing. Consequently, certain assumptions related to code design are made by the operating system (UNICOS/mk) and its scheduling tools. With the exception of HPF, which does run on the T3E, however poorly, alternative programming styles have the potential to impact the T3E in unexpected and undesirable ways. Several examples will be presented (preceeded with the disclaimer, "Don't try this at home! Violators will be prosecuted!")

Bernard, Lisa Hamet↗

NASA NTRS1999

The SGI/CRAY T3E: Experiences and Insights

The focus of the HPCC Earth and Space Sciences (ESS) Project is capability computing - pushing highly scalable computing testbeds to their performance limits. The drivers of this focus are the Grand Challenge problems in Earth and space science: those that could not be addressed in a capacity computing environment where large jobs must continually compete for resources. These Grand Challenge codes require a high degree of communication, large memory, and very large I/O (throughout the duration of the processing, not just in loading initial conditions and saving final results). This set of parameters led to the selection of an SGI/Cray T3E as the current ESS Computing Testbed. The T3E at the Goddard Space Flight Center is a unique computational resource within NASA. As such, it must be managed to effectively support the diverse research efforts across the NASA research community yet still enable the ESS Grand Challenge Investigator teams to achieve their performance milestones, for which the system was intended. To date, all Grand Challenge Investigator teams have achieved the 10 GFLOPS milestone, eight of nine have achieved the 50 GFLOPS milestone, and three have achieved the 100 GFLOPS milestone. In addition, many technical papers have been published highlighting results achieved on the NASA T3E, including some at this Workshop. The successes enabled by the NASA T3E computing environment are best illustrated by the 512 PE upgrade funded by the NASA Earth Science Enterprise earlier this year. Never before has an HPCC computing testbed been so well received by the general NASA science community that it was deemed critical to the success of a core NASA science effort. NASA looks forward to many more success stories before the conclusion of the NASA-SGI/Cray cooperative agreement in June 1999.

Bernard, Lisa Hamet↗

NASA NTRS2022

SpaceVPX Interoperability Assessment

The existing VMEbus (VersaModular Eurocard bus) International Trade Association (VITA)-78 industry standard, also known as SpaceVPX, is an avionics board- and chassis-level standard derived from the OpenVPX standard as defined in VITA-65. While VITA-65 defines backplane and board-level profiles from COTS vendors to ensure interoperability of products used in developing systems and subsystems, the VITA-78 standard defines SpaceVPX to incorporate fault tolerance features that are required by many spaceflight systems. However, VITA-78 allows so much flexibility that interoperability between modules cannot be assured. This assessment provides guidelines on the use of, and extensions to, the VITA-78 standard to enable avionics interoperability for future NASA missions. The assessment team was comprised of subject matter experts (SMEs) from Goddard Space Flight Center (GSFC), the Jet Propulsion Laboratory (JPL), Johnson Space Center (JSC), and Langley Research Center (LaRC). The team included valuable external consulting support from a SME who was a key participant in the development of the VITA-78 standard. The team had extensive collaboration with the NASA Space Technology Mission Directorate (STMD) High Performance Spaceflight Computing (HPSC) project, specifically in the development of SpaceVPX interconnect findings, observations, and NESC recommendations. To provide an understanding of the breadth of implementations that SpaceVPX must accommodate, multiple NASA use cases were analyzed to assess the requirements for SpaceVPX implementations across a wide range of NASA missions (Appendix C). Applications included crewed missions, science missions, and orbital and surface robotic systems. Product surveys were conducted to assess the level of industry support for SpaceVPX, applications, and the variations in their implementations (Appendix D). In-depth analysis was conducted in the areas of: (a) power management and distribution, (b) form factors and daughtercards, (c) interconnect, and (d) fault tolerance. Leveraging the use cases, product surveys, and SMEs from multiple NASA Centers, these areas were analyzed to determine the range of implementations permitted by the VITA-78 standard and potential interoperability issues. Applicable findings and NESC recommendations were provided for each area. During this assessment, there were multiple opportunities to engage with other agencies to learn about their interest in SpaceVPX, their strategies for implementing SpaceVPX-based systems, and their internal development efforts. These engagements also generated findings and NESC recommendations. Based on this assessment analysis, NESC recommendations were made regarding the feature set and module profiles to support NASA SpaceVPX implementations. This feature set includes restrictions on features in VITA-78, and extensions to the standard. Key recommendations in this area include the use of 10 Gigabit Ethernet and Peripheral Component Interconnect Express (PCIe) as high bandwidth interconnect on the backplane, the retention of SpaceWire interconnect for control functions, and support for 3U (unit) and 6U, form factors for NASA systems. Restrictions were proposed on the usage of user-defined signals to promote interoperability, and specific power managements and distribution schemes for 3U systems. Beyond the technical implementation of SpaceVPX, recommendations were made on areas that warrant further investigation. Primary among these is the recommendation for NASA to collaborate with other space-going agencies and industry to incorporate recommendations into a future ‘dot spec’ of VITA-78. This would ensure wide adoption and availability of the modules that comply with the specification. The assessment includes appendices with candidate module profiles that can be considered as a starting point for this activity, and example systems based on the recommendations. Follow-on studies are recommended for architectures beyond SpaceVPX to address potential enhancements including condensed set of interconnect, software required to implement protocol layers on the interconnect (and other features), alternative power architectures, and system-level testability.

SpaceVPX↗

NASA NTRS2007

High Performance Processors for Space Environments: A Subproject of the NASA Exploration Missions Systems Directorate "Radiation Hardened Electronics for Space Environments" Technology Development Program

Implementation of challenging Exploration Systems Missions Directorate objectives and strategies can be constrained by onboard computing capabilities and power efficiencies. The Radiation Hardened Electronics for Space Environments (RHESE) High Performance Processors for Space Environments project will address this challenge by significantly advancing the sustained throughput and processing efficiency of high-per$ormance radiation-hardened processors, targeting delivery of products by the end of FY12.

Johnson, M.↗

NASA NTRS1999

Configuration Management of an Optimization Application in a Research Environment

Multidisciplinary design optimization (MDO) research aims to increase interdisciplinary communication and reduce design cycle time by combining system analyses (simulations) with design space search and decision making. The High Performance Computing and Communication Program's current High Speed Civil Transport application, HSCT4.0, at NASA Langley Research Center involves a highly complex analysis process with high-fidelity analyses that are more realistic than previous efforts at the Center. The multidisciplinary processes have been integrated to form a distributed application by using the Java language and Common Object Request Broker Architecture (CORBA) software techniques. HSCT4.0 is a research project in which both the application problem and the implementation strategy have evolved as the MDO and integration issues became better understood. Whereas earlier versions of the application and integrated system were developed with a simple, manual software configuration management (SCM) process, it was evident that this larger project required a more formal SCM procedure. This report briefly describes the HSCT4.0 analysis and its CORBA implementation and then discusses some SCM concepts and their application to this project. In anticipation that SCM will prove beneficial for other large research projects, the report concludes with some lessons learned in overcoming SCM implementation problems for HSCT4.0.

Townsend, James C.↗

NASA NTRS2001

An overview of flight computer technologies for future NASA

In this paper, we present an overview of current developments by several US Government Agencies and associated programs, towards high-performance single board computers for use in space. Three separate projects will be described; two that are based on the Power PC processor, and one based on the Pentium processor.

space exploration flight computers↗

NASA NTRS1994

CESDIS

CESDIS, the Center of Excellence in Space Data and Information Sciences was developed jointly by NASA, Universities Space Research Association (USRA), and the University of Maryland in 1988 to focus on the design of advanced computing techniques and data systems to support NASA Earth and space science research programs. CESDIS is operated by USRA under contract to NASA. The Director, Associate Director, Staff Scientists, and administrative staff are located on-site at NASA's Goddard Space Flight Center in Greenbelt, Maryland. The primary CESDIS mission is to increase the connection between computer science and engineering research programs at colleges and universities and NASA groups working with computer applications in Earth and space science. Research areas of primary interest at CESDIS include: 1) High performance computing, especially software design and performance evaluation for massively parallel machines; 2) Parallel input/output and data storage systems for high performance parallel computers; 3) Data base and intelligent data management systems for parallel computers; 4) Image processing; 5) Digital libraries; and 6) Data compression. CESDIS funds multiyear projects at U. S. universities and colleges. Proposals are accepted in response to calls for proposals and are selected on the basis of peer reviews. Funds are provided to support faculty and graduate students working at their home institutions. Project personnel visit Goddard during academic recess periods to attend workshops, present seminars, and collaborate with NASA scientists on research projects. Additionally, CESDIS takes on specific research tasks of shorter duration for computer science research requested by NASA Goddard scientists.

Source record↗

NASA NTRS2021

NASA SpaceCube Edge TPU SmallSat Card for Autonomous Operations and Onboard Science-Data Analysis

Using state-of-the-art artificial intelligence (AI)frameworks onboard spacecraft is challenging because common spacecraft processors cannot provide comparable performance to datacenters with server-grade CPUs and GPUs available for terrestrial applications and advanced deep-learning networks. This limitation makes small, lo w-p o we r AI microchip architectures, such as the Google Coral Edge Tensor Processing Unit (TPU), attractive for space missions where the application-specific design enables both high-performance and power-efficient computing for AI applications. To address these challenging considerations for space deployment, this research introduces the design and capabilities of a CubeSat-sized Edge TPU-based co-processor card, known as the SpaceCube Low-power Ed g e Artificial Intelligence Resilient Node (SC-LEARN). This design conforms to NASA’s CubeSat Card Specification (CS2) for integration into next-generation SmallSat and CubeSat systems. This paper describes the overarching architecture and design of the SC-LEARN, as well as, the supporting test card designed for rapid prototyping and evaluation. The SC-LEARN was developed with three operational modes: (1) a high-performance parallel-processing mode,(2)a fault-tolerant mode for onboard resilience, and (3) a power-saving mode with cold spares. Importantly, this research also elaborates on both training and quantization of Tensor Flow models for the SC-LEARN for use onboard with representative, open-source datasets. Lastly, we describe future research plans, including radiation-beam testing and flight demonstration.

Advanced avionics↗

NASA NTRS1989

Tools for 3D scientific visualization in computational aerodynamics

The purpose is to describe the tools and techniques in use at the NASA Ames Research Center for performing visualization of computational aerodynamics, for example visualization of flow fields from computer simulations of fluid dynamics about vehicles such as the Space Shuttle. The hardware used for visualization is a high-performance graphics workstation connected to a super computer with a high speed channel. At present, the workstation is a Silicon Graphics IRIS 3130, the supercomputer is a CRAY2, and the high speed channel is a hyperchannel. The three techniques used for visualization are post-processing, tracking, and steering. Post-processing analysis is done after the simulation. Tracking analysis is done during a simulation but is not interactive, whereas steering analysis involves modifying the simulation interactively during the simulation. Using post-processing methods, a flow simulation is executed on a supercomputer and, after the simulation is complete, the results of the simulation are processed for viewing. The software in use and under development at NASA Ames Research Center for performing these types of tasks in computational aerodynamics is described. Workstation performance issues, benchmarking, and high-performance networks for this purpose are also discussed as well as descriptions of other hardware for digital video and film recording.

Bancroft, Gordon↗

NASA NTRS2002

ISS Radiation Shielding and Acoustic Simulation Using an Immersive Environment

The International Space Station Environment Simulator (ISSES) is a virtual reality application that uses high-performance computing, graphics, and audio rendering to simulate the radiation and acoustic environments of the International Space Station (ISS). This CAVE application allows the user to maneuver to different locations inside or outside of the ISS and interactively compute and display the radiation dose at a point. The directional dose data is displayed as a color-mapped sphere that indicates the relative levels of radiation from all directions about the center of the sphere. The noise environment is rendered in real time over headphones or speakers and includes non-spatial background noise, such as air-handling equipment, and spatial sounds associated with specific equipment racks, such as compressors or fans. Changes can be made to equipment rack locations that produce changes in both the radiation shielding and system noise. The ISSES application allows for interactive investigation and collaborative trade studies between radiation shielding and noise for crew safety and comfort.

Verhage, Joshua E.↗

NASA NTRS1994

Performance evaluation of the Engineering Analysis and Data Systems (EADS) 2

The Engineering Analysis and Data System (EADS)II (1) was installed in March 1993 to provide high performance computing for science and engineering at Marshall Space Flight Center (MSFC). EADS II increased the computing capabilities over the existing EADS facility in the areas of throughput and mass storage. EADS II includes a Vector Processor Compute System (VPCS), a Virtual Memory Compute System (CFS), a Common Output System (COS), as well as Image Processing Station, Mini Super Computers, and Intelligent Workstations. These facilities are interconnected by a sophisticated network system. This work considers only the performance of the VPCS and the CFS. The VPCS is a Cray YMP. The CFS is implemented on an RS 6000 using the UniTree Mass Storage System. To better meet the science and engineering computing requirements, EADS II must be monitored, its performance analyzed, and appropriate modifications for performance improvement made. Implementing this approach requires tool(s) to assist in performance monitoring and analysis. In Spring 1994, PerfStat 2.0 was purchased to meet these needs for the VPCS and the CFS. PerfStat(2) is a set of tools that can be used to analyze both historical and real-time performance data. Its flexible design allows significant user customization. The user identifies what data is collected, how it is classified, and how it is displayed for evaluation. Both graphical and tabular displays are supported. The capability of the PerfStat tool was evaluated, appropriate modifications to EADS II to optimize throughput and enhance productivity were suggested and implemented, and the effects of these modifications on the systems performance were observed. In this paper, the PerfStat tool is described, then its use with EADS II is outlined briefly. Next, the evaluation of the VPCS, as well as the modifications made to the system are described. Finally, conclusions are drawn and recommendations for future worked are outlined.

Debrunner, Linda S.↗

NASA NTRSDate not supplied

Robotic Manipulation Testbeds with HPSC

Interoperability and scalability of robotic manipulators will be key to develop and sustain a lunar surface and cislunar ecosystem. From in-space servicing, assembly, and manufacturing (ISAM) to logistics, maintenance, and science operations, robotic manipulation is a critical NASA capability need and the demand for high-performance spaceflight computing will only rise as robotic tasks become more autonomous. With increased complexity, testbeds for research, feasibility studies, and technology demonstrations will be essential. The Dexterous Robotics Team at NASA Johnson Space Center has established multiple robotic manipulation testbeds taking a supervised autonomous remote operations approach and plans to infuse High-Performance Spaceflight Computing (HPSC) to emulate the flight environment and close the gap between space technology development and flight operations.

Alex Sowell↗

NASA NTRS1992

A simple modern correctness condition for a space-based high-performance multiprocessor

A number of U.S. national programs, including space-based detection of ballistic missile launches, envisage putting significant computing power into space. Given sufficient progress in low-power VLSI, multichip-module packaging and liquid-cooling technologies, we will see design of high-performance multiprocessors for individual satellites. In very high speed implementations, performance depends critically on tolerating large latencies in interprocessor communication; without latency tolerance, performance is limited by the vastly differing time scales in processor and data-memory modules, including interconnect times. The modern approach to tolerating remote-communication cost in scalable, shared-memory multiprocessors is to use a multithreaded architecture, and alter the semantics of shared memory slightly, at the price of forcing the programmer either to reason about program correctness in a relaxed consistency model or to agree to program in a constrained style. The literature on multiprocessor correctness conditions has become increasingly complex, and sometimes confusing, which may hinder its practical application. We propose a simple modern correctness condition for a high-performance, shared-memory multiprocessor; the correctness condition is based on a simple interface between the multiprocessor architecture and a high-performance, shared-memory multiprocessor; the correctness condition is based on a simple interface between the multiprocessor architecture and the parallel programming system.

Probst, David K.↗

NASA NTRS2002

Numerical Propulsion System Simulation (NPSS): An Award Winning Propulsion System Simulation Tool

The Numerical Propulsion System Simulation (NPSS) is a full propulsion system simulation tool used by aerospace engineers to predict and analyze the aerothermodynamic behavior of commercial jet aircraft, military applications, and space transportation. The NPSS framework was developed to support aerospace, but other applications are already leveraging the initial capabilities, such as aviation safety, ground-based power, and alternative energy conversion devices such as fuel cells. By using the framework and developing the necessary components, future applications that NPSS could support include nuclear power, water treatment, biomedicine, chemical processing, and marine propulsion. NPSS will dramatically reduce the time, effort, and expense necessary to design and test jet engines. It accomplishes that by generating sophisticated computer simulations of an aerospace object or system, thus enabling engineers to "test" various design options without having to conduct costly, time-consuming real-life tests. The ultimate goal of NPSS is to create a numerical "test cell" that enables engineers to create complete engine simulations overnight on cost-effective computing platforms. Using NPSS, engine designers will be able to analyze different parts of the engine simultaneously, perform different types of analysis simultaneously (e.g., aerodynamic and structural), and perform analysis in a more efficient and less costly manner. NPSS will cut the development time of a new engine in half, from 10 years to 5 years. And NPSS will have a similar effect on the cost of development: new jet engines will cost about a billion dollars to develop rather than two billion. NPSS is also being applied to the development of space transportation technologies, and it is expected that similar efficiencies and cost savings will result. Advancements of NPSS in fiscal year 2001 included enhancing the NPSS Developer's Kit to easily integrate external components of varying fidelities, providing the initial Visual-Based Syntax (VBS) capability, and developing additional capabilities to support space transportation. NPSS was supported under NASA's High Performance Computing and Communications Program. Through the NASA/Industry Cooperative Effort agreement, NASA Glenn and its industry and Government partners are developing NPSS. The NPSS team consists of propulsion experts and software engineers from GE Aircraft Engines, Pratt & Whitney, The Boeing Company, Honeywell, Rolls-Royce Corporation, Williams International, Teledyne Continental Motors, Arnold Engineering Development Center, Wright Patterson Air Force Base, and the NASA Glenn Research Center. Glenn is leading the way in developing NPSS--a method for solving complex design problems that's faster, better, and cheaper.

Stauber, Laurel J.↗

NASA NTRS2014

CSP: A Multifaceted Hybrid Architecture for Space Computing

Research on the CHREC Space Processor (CSP) takes a multifaceted hybrid approach to embedded space computing. Working closely with the NASA Goddard SpaceCube team, researchers at the National Science Foundation (NSF) Center for High-Performance Reconfigurable Computing (CHREC) at the University of Florida and Brigham Young University are developing hybrid space computers that feature an innovative combination of three technologies: commercial-off-the-shelf (COTS) devices, radiation-hardened (RadHard) devices, and fault-tolerant computing. Modern COTS processors provide the utmost in performance and energy-efficiency but are susceptible to ionizing radiation in space, whereas RadHard processors are virtually immune to this radiation but are more expensive, larger, less energy-efficient, and generations behind in speed and functionality. By featuring COTS devices to perform the critical data processing, supported by simpler RadHard devices that monitor and manage the COTS devices, and augmented with novel uses of fault-tolerant hardware, software, information, and networking within and between COTS devices, the resulting system can maximize performance and reliability while minimizing energy consumption and cost. NASA Goddard has adopted the CSP concept and technology with plans underway to feature flight-ready CSP boards on two upcoming space missions.

Reconfigurable↗