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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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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Supercomputing systems - A projection to 2000

Advances in computer architecture, computer science, computational methods, and constituent technologies are expected to lead to significant advances in the performance of scientific supercomputing system capabilities over the next decade. By the year 2000, single 1-in-sq dies are projected to incorporate four processors, each of which would be operating faster than 750 million instructions per second (MIPS) for a total on-chip processing performance in excess of 2000 MIPS. Scalable parallel processors can be expected to contain thousands of such multiple processor chips. In general, semiconductor performance advances appear to change about one order of magnitude every five years. Rotating magnetic memory and communications technology are not advancing as rapidly, with the result that the allocation of functions within the system configurations fo future supercomputer systems will require important changes. Availability of massively parallel heterogeneous processing capabilities should be a catalyst leading to new approaches for applications.

Lundstrom, S. F.↗
NASA NTRS1988

Computer sciences

The Computer Science Program provides advanced concepts, techniques, system architectures, algorithms, and software for both space and aeronautics information sciences and computer systems. The overall goal is to provide the technical foundation within NASA for the advancement of computing technology in aerospace applications. The research program is improving the state of knowledge of fundamental aerospace computing principles and advancing computing technology in space applications such as software engineering and information extraction from data collected by scientific instruments in space. The program includes the development of special algorithms and techniques to exploit the computing power provided by high performance parallel processors and special purpose architectures. Research is being conducted in the fundamentals of data base logic and improvement techniques for producing reliable computing systems.

Smith, Paul H.↗
NASA NTRS1986

First 3 years of operation of RIACS (Research Institute for Advanced Computer Science) (1983-1985)

The focus of the Research Institute for Advanced Computer Science (RIACS) is to explore matches between advanced computing architectures and the processes of scientific research. An architecture evaluation of the MIT static dataflow machine, specification of a graphical language for expressing distributed computations, and specification of an expert system for aiding in grid generation for two-dimensional flow problems was initiated. Research projects for 1984 and 1985 are summarized.

Denning, P. J.↗
NASA NTRS1993

Embedded Data Processor and Portable Computer Technology testbeds

Attention is given to current activities in the Embedded Data Processor and Portable Computer Technology testbed configurations that are part of the Advanced Data Systems Architectures Testbed at the Information Sciences Division at NASA Ames Research Center. The Embedded Data Processor Testbed evaluates advanced microprocessors for potential use in mission and payload applications within the Space Station Freedom Program. The Portable Computer Technology (PCT) Testbed integrates and demonstrates advanced portable computing devices and data system architectures. The PCT Testbed uses both commercial and custom-developed devices to demonstrate the feasibility of functional expansion and networking for portable computers in flight missions.

Alena, Richard↗
NASA NTRS1986

White paper: A plan for cooperation between NASA and DARPA to establish a center for advanced architectures

Large, complex computer systems require many years of development. It is recognized that large scale systems are unlikely to be delivered in useful condition unless users are intimately involved throughout the design process. A mechanism is described that will involve users in the design of advanced computing systems and will accelerate the insertion of new systems into scientific research. This mechanism is embodied in a facility called the Center for Advanced Architectures (CAA). CAA would be a division of RIACS (Research Institute for Advanced Computer Science) and would receive its technical direction from a Scientific Advisory Board established by RIACS. The CAA described here is a possible implementation of a center envisaged in a proposed cooperation between NASA and DARPA.

Denning, P. J.↗
NASA NTRS2003

High End Computing Technologies for Earth Science Applications: Trends, Challenges, and Innovations

Earth science applications of the future will stress the capabilities of even the highest performance supercomputers in the areas of raw compute power, mass storage management, and software environments. These NASA mission critical problems demand usable multi-petaflops and exabyte-scale systems to fully realize their science goals. With an exciting vision of the technologies needed, NASA has established a comprehensive program of advanced research in computer architecture, software tools, and device technology to ensure that, in partnership with US industry, it can meet these demanding requirements with reliable, cost effective, and usable ultra-scale systems. NASA will exploit, explore, and influence emerging high end computing architectures and technologies to accelerate the next generation of engineering, operations, and discovery processes for NASA Enterprises. This article captures this vision and describes the concepts, accomplishments, and the potential payoff of the key thrusts that will help meet the computational challenges in Earth science applications.

Parks, John↗
NASA NTRS1985

The science of computing - Parallel computation

Although parallel computation architectures have been known for computers since the 1920s, it was only in the 1970s that microelectronic components technologies advanced to the point where it became feasible to incorporate multiple processors in one machine. Concommitantly, the development of algorithms for parallel processing also lagged due to hardware limitations. The speed of computing with solid-state chips is limited by gate switching delays. The physical limit implies that a 1 Gflop operational speed is the maximum for sequential processors. A computer recently introduced features a 'hypercube' architecture with 128 processors connected in networks at 5, 6 or 7 points per grid, depending on the design choice. Its computing speed rivals that of supercomputers, but at a fraction of the cost. The added speed with less hardware is due to parallel processing, which utilizes algorithms representing different parts of an equation that can be broken into simpler statements and processed simultaneously. Present, highly developed computer languages like FORTRAN, PASCAL, COBOL, etc., rely on sequential instructions. Thus, increased emphasis will now be directed at parallel processing algorithms to exploit the new architectures.

Denning, P. J.↗
NASA NTRS1987

Computer Sciences and Data Systems, volume 2

Topics addressed include: data storage; information network architecture; VHSIC technology; fiber optics; laser applications; distributed processing; spaceborne optical disk controller; massively parallel processors; and advanced digital SAR processors.

Source record↗
NASA NTRS2016

Developing the Next Generation of Science Data System Engineers

At Goddard, engineers and scientists with a range of experience in science data systems are needed to employ new technologies and develop advances in capabilities for supporting new Earth and Space science research. Engineers with extensive experience in science data, software engineering and computer-information architectures are needed to lead and perform these activities. The increasing types and complexity of instrument data and emerging computer technologies coupled with the current shortage of computer engineers with backgrounds in science has led the need to develop a career path for science data systems engineers and architects.The current career path, in which undergraduate students studying various disciplines such as Computer Engineering or Physical Scientist, generally begins with serving on a development team in any of the disciplines where they can work in depth on existing Goddard data systems or serve with a specific NASA science team. There they begin to understand the data, infuse technologies, and begin to know the architectures of science data systems. From here the typical career involves peermentoring, on-the-job training or graduate level studies in analytics, computational science and applied science and mathematics. At the most senior level, engineers become subject matter experts and system architect experts, leading discipline-specific data centers and large software development projects. They are recognized as a subject matter expert in a science domain, they have project management expertise, lead standards efforts and lead international projects. A long career development remains necessary not only because of the breadth of knowledge required across physical sciences and engineering disciplines, but also because of the diversity of instrument data being developed today both by NASA and international partner agencies and because multidiscipline science and practitioner communities expect to have access to all types of observational data.This paper describes an approach to defining career-path guidance for college-bound high school and undergraduate engineering students, junior and senior engineers from various disciplines.

Next Generation of Science↗
NASA NTRS2006

Implementing the President's Vision: JPL and NASA's Exploration Systems Mission Directorate

As part of the NASA team the Jet Propulsion Laboratory is involved in the Exploration Systems Mission Directorate (ESMD) work to implement the President's Vision for Space exploration. In this slide presentation the roles that are assigned to the various NASA centers to implement the vision are reviewed. The plan for JPL is to use the Constellation program to advance the combination of science an Constellation program objectives. JPL's current participation is to contribute systems engineering support, Command, Control, Computing and Information (C3I) architecture, Crew Exploration Vehicle, (CEV) Thermal Protection System (TPS) project support/CEV landing assist support, Ground support systems support at JSC and KSC, Exploration Communication and Navigation System (ECANS), Flight prototypes for cabin atmosphere instruments

Industry Day↗
NASA NTRSDate not supplied

NASA's Small Spacecraft and Distributed Systems: Development and Demonstration of Technologies Enabling Swarms and New Spacecraft Platforms with AI and Edge Computing

NASA’s Small Spacecraft & Distributed Systems (SSDS) within the Research and Technology Mission Directorate (RTMD) expands U.S. capability to execute unique missions through targeted investment, rapid development, and flight demonstration of small spacecraft technologies applicable to exploration, science and the commercial space sector. SSDS strategically invests in technology development and on-orbit demonstrations executed across NASA, other government agencies, industry, and academia. The program’s University SmallSat Technology Partnerships initiative awards academic researchers with the opportunity to collaborate with NASA to mature innovative technology. Capabilities aligned with RTMD’s technology shortfalls and interests - power, processing, propulsion, sensors, communications, autonomous navigation, architectures, and advanced applications like artificial intelligence (AI), machine learning, and edge computing - are prioritized in SSDS investments. These investments enable distributed, autonomous, and cooperative small spacecraft systems that support swarm missions extending beyond low Earth orbit into cislunar and deep space. This paper highlights representative SSDS flight demonstrations that mature these capabilities to enable a future operational infrastructure needed to support sustained exploration of the Moon and beyond. SSDS’s investment strategy emphasizes rapid development and on-orbit demonstration to validate spacecraft technologies required for swarms and distributed mission architectures. The Starling swarm technology demonstration mission exemplifies this approach by advancing distributed spacecraft autonomy, cooperative operations, and space situational awareness. Extended flight testing and ongoing studies of next generation swarm configurations and on-orbit space traffic monitoring and management continue to inform future swarm designs. DiskSat’s four-spacecraft demonstration mission represents SSDS’s strategic vision to expand the design space for future small spacecraft through its commitment to advance novel platform concepts that can impact how science is performed on orbit. Continuing to invest in future platforms, the notional PY12 concept is a 12-spacecraft swarm hosting neuromorphic processors and is envisioned as an on-orbit testbed for AI, edge computing, and positioning, navigation and timing technologies. SSDS also invests in single-spacecraft technology demonstrations that underpin the success of future swarm missions and accelerate the availability of validated technologies across the small spacecraft ecosystem. Examples of such demonstrations include Pathfinder Technology Demonstrator-3 (PTD-3), which performed high-rate optical communications; PTD-R, which demonstrated a camera capable of simultaneous ultraviolet and short-wave infrared optical sensing; and CAPSTONE, the Cislunar Autonomous Positioning System Technology and Operations Navigation Experiment, which validated autonomous navigation in cislunar space. Collectively, SSDS-funded demonstrations advance capabilities across swarms and illustrate a coordinated investment strategy to mature high-impact technologies required for autonomous, distributed, and cooperative small spacecraft systems for low Earth orbit, cislunar, and deep space applications. Technology demonstrations strengthen SSDS partnerships with industry, academia, and other government agencies, and promote small spacecraft community adoption of capabilities required to close technical gaps for swarm missions.

Jan Stupl↗
NASA NTRSDate not supplied

NASA's Small Spacecraft and Distributed Systems: Development and Demonstration of Technologies Enabling Swarms and New Spacecraft Platforms with AI and Edge Computing

NASA’s Small Spacecraft & Distributed Systems (SSDS) within the Research and Technology Mission Directorate (RTMD) expands U.S. capability to execute unique missions through targeted investment, rapid development, and flight demonstration of small spacecraft technologies applicable to exploration, science and the commercial space sector. SSDS strategically invests in technology development and on-orbit demonstrations executed across NASA, other government agencies, industry, and academia. The program’s University SmallSat Technology Partnerships initiative awards academic researchers with the opportunity to collaborate with NASA to mature innovative technology. Capabilities aligned with RTMD’s technology shortfalls and interests - power, processing, propulsion, sensors, communications, autonomous navigation, architectures, and advanced applications like artificial intelligence (AI), machine learning, and edge computing - are prioritized in SSDS investments. These investments enable distributed, autonomous, and cooperative small spacecraft systems that support swarm missions extending beyond low Earth orbit into cislunar and deep space. This paper highlights representative SSDS flight demonstrations that mature these capabilities to enable a future operational infrastructure needed to support sustained exploration of the Moon and beyond. SSDS’s investment strategy emphasizes rapid development and on-orbit demonstration to validate spacecraft technologies required for swarms and distributed mission architectures. The Starling swarm technology demonstration mission exemplifies this approach by advancing distributed spacecraft autonomy, cooperative operations, and space situational awareness. Extended flight testing and ongoing studies of next generation swarm configurations and on-orbit space traffic monitoring and management continue to inform future swarm designs. DiskSat’s four-spacecraft demonstration mission represents SSDS’s strategic vision to expand the design space for future small spacecraft through its commitment to advance novel platform concepts that can impact how science is performed on orbit. Continuing to invest in future platforms, the notional PY12 concept is a 12-spacecraft swarm hosting neuromorphic processors and is envisioned as an on-orbit testbed for AI, edge computing, and positioning, navigation and timing technologies. SSDS also invests in single-spacecraft technology demonstrations that underpin the success of future swarm missions and accelerate the availability of validated technologies across the small spacecraft ecosystem. Examples of such demonstrations include Pathfinder Technology Demonstrator-3 (PTD-3), which performed high-rate optical communications; PTD-R, which demonstrated a camera capable of simultaneous ultraviolet and short-wave infrared optical sensing; and CAPSTONE, the Cislunar Autonomous Positioning System Technology and Operations Navigation Experiment, which validated autonomous navigation in cislunar space. Collectively, SSDS-funded demonstrations advance capabilities across swarms and illustrate a coordinated investment strategy to mature high-impact technologies required for autonomous, distributed, and cooperative small spacecraft systems for low Earth orbit, cislunar, and deep space applications. Technology demonstrations strengthen SSDS partnerships with industry, academia, and other government agencies, and promote small spacecraft community adoption of capabilities required to close technical gaps for swarm missions.

Jan Stupl↗
NASA NTRS1985

Parallel processor programs in the Federal Government

In 1982, a report dealing with the nation's research needs in high-speed computing called for increased access to supercomputing resources for the research community, research in computational mathematics, and increased research in the technology base needed for the next generation of supercomputers. Since that time a number of programs addressing future generations of computers, particularly parallel processors, have been started by U.S. government agencies. The present paper provides a description of the largest government programs in parallel processing. Established in fiscal year 1985 by the Institute for Defense Analyses for the National Security Agency, the Supercomputing Research Center will pursue research to advance the state of the art in supercomputing. Attention is also given to the DOE applied mathematical sciences research program, the NYU Ultracomputer project, the DARPA multiprocessor system architectures program, NSF research on multiprocessor systems, ONR activities in parallel computing, and NASA parallel processor projects.

Schneck, P. B.↗
NASA NTRS2000

HTMT-class Latency Tolerant Parallel Architecture for Petaflops Scale Computation

Computational Aero Sciences and other numeric intensive computation disciplines demand computing throughputs substantially greater than the Teraflops scale systems only now becoming available. The related fields of fluids, structures, thermal, combustion, and dynamic controls are among the interdisciplinary areas that in combination with sufficient resolution and advanced adaptive techniques may force performance requirements towards Petaflops. This will be especially true for compute intensive models such as Navier-Stokes are or when such system models are only part of a larger design optimization computation involving many design points. Yet recent experience with conventional MPP configurations comprising commodity processing and memory components has shown that larger scale frequently results in higher programming difficulty and lower system efficiency. While important advances in system software and algorithms techniques have had some impact on efficiency and programmability for certain classes of problems, in general it is unlikely that software alone will resolve the challenges to higher scalability. As in the past, future generations of high-end computers may require a combination of hardware architecture and system software advances to enable efficient operation at a Petaflops level. The NASA led HTMT project has engaged the talents of a broad interdisciplinary team to develop a new strategy in high-end system architecture to deliver petaflops scale computing in the 2004/5 timeframe. The Hybrid-Technology, MultiThreaded parallel computer architecture incorporates several advanced technologies in combination with an innovative dynamic adaptive scheduling mechanism to provide unprecedented performance and efficiency within practical constraints of cost, complexity, and power consumption. The emerging superconductor Rapid Single Flux Quantum electronics can operate at 100 GHz (the record is 770 GHz) and one percent of the power required by convention semiconductor logic. Wave Division Multiplexing optical communications can approach a peak per fiber bandwidth of 1 Tbps and the new Data Vortex network topology employing this technology can connect tens of thousands of ports providing a bi-section bandwidth on the order of a Petabyte per second with latencies well below 100 nanoseconds, even under heavy loads. Processor-in-Memory (PIM) technology combines logic and memory on the same chip exposing the internal bandwidth of the memory row buffers at low latency. And holographic storage photorefractive storage technologies provide high-density memory with access a thousand times faster than conventional disk technologies. Together these technologies enable a new class of shared memory system architecture with a peak performance in the range of a Petaflops but size and power requirements comparable to today's largest Teraflops scale systems. To achieve high-sustained performance, HTMT combines an advanced multithreading processor architecture with a memory-driven coarse-grained latency management strategy called "percolation", yielding high efficiency while reducing the much of the parallel programming burden. This paper will present the basic system architecture characteristics made possible through this series of advanced technologies and then give a detailed description of the new percolation approach to runtime latency management.

Sterling, Thomas↗
NASA NTRSDate not supplied

NASA Small Spacecraft and Distributed Systems Program - Recent and Upcoming Technology Demonstrations and Development Efforts

NASA’s Small Spacecraft & Distributed Systems (SSDS) program strengthens U.S. ability to conduct unique missions by rapidly developing and demonstrating capabilities for SmallSat exploration, science, and commercial space. In collaboration with NASA Centers, other government agencies, commercial industry, and academia, SSDS advances next generation SmallSat technologies like power, processing, propulsion, communications, autonomous navigation, architectures (swarms), and applications (AI/ML/Edge Computing)—to extend missions beyond LEO into cislunar and planetary space. Various investment mechanisms exist for SSDS to select and fund projects that will ultimately advance NASA’s Moon to Mars Architecture. Presented here are the latest achievements and findings from recently completed SSDS projects, along with updates from ongoing efforts and planned future work. Successful missions like Starling and CAPSTONE continue to demonstrate their capability after several years on-orbit. Advancements in next generation swarm configurations are being implemented by Starling for space traffic monitoring and management applications. Findings from recent SSDS flight projects are discussed: DiskSat, a unique SmallSat platform alternative to canisterized nanosatellites, launched December 2025 and is gathering data; the PTD series of missions concluded in December 2025. Current SSDS efforts are focused on addressing NASA Shortfalls relating to rendezvous and proximity operations, neuromorphic computing, and space situational awareness.

Roger C Hunter↗
NASA NTRSDate not supplied

NASA Small Spacecraft and Distributed Systems: Recent and Upcoming Technology Demonstrations and Development Efforts

NASA’s Small Spacecraft & Distributed Systems (SSDS) program strengthens U.S. ability to conduct unique missions by rapidly developing and demonstrating capabilities for SmallSat exploration, science, and commercial space. In collaboration with NASA Centers, other government agencies, commercial industry, and academia, SSDS advances next generation SmallSat technologies like power, processing, propulsion, communications, autonomous navigation, architectures (swarms), and applications (AI/ML/Edge Computing)—to extend missions beyond LEO into cislunar and planetary space. Various investment mechanisms exist for SSDS to select and fund projects that will ultimately advance NASA’s Moon to Mars Architecture. Presented here are the latest achievements and findings from recently completed SSDS projects, along with updates from ongoing efforts and planned future work. Successful missions like Starling and CAPSTONE continue to demonstrate their capability after several years on-orbit. Advancements in next generation swarm configurations are being implemented by Starling for space traffic monitoring and management applications. Findings from recent SSDS flight projects are discussed: DiskSat, a unique SmallSat platform alternative to canisterized nanosatellites, launched December 2025 and is gathering data; the PTD series of missions concluded in December 2025. Current SSDS efforts are focused on addressing NASA Shortfalls relating to rendezvous and proximity operations, neuromorphic computing, and space situational awareness.

Roger Hunter↗
NASA NTRS1993

Optimization of knowledge-based systems and expert system building tools

The objectives of the NASA-AMES Cooperative Agreement were to investigate, develop, and evaluate, via test cases, the system parameters and processing algorithms that constrain the overall performance of the Information Sciences Division's Artificial Intelligence Research Facility. Written reports covering various aspects of the grant were submitted to the co-investigators for the grant. Research studies concentrated on the field of artificial intelligence knowledge-based systems technology. Activities included the following areas: (1) AI training classes; (2) merging optical and digital processing; (3) science experiment remote coaching; (4) SSF data management system tests; (5) computer integrated documentation project; (6) conservation of design knowledge project; (7) project management calendar and reporting system; (8) automation and robotics technology assessment; (9) advanced computer architectures and operating systems; and (10) honors program.

Yasuda, Phyllis↗