Search NASA⌕ Search

SEARCH · Search NASA

Results for “COMPUTER NETWORKS”

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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

A graph-based computational framework for simulation and optimisation of coupled infrastructure networks

Here, we present a computational framework that facilitates the construction, instantiation, and analysis of large-scale optimization and simulation applications of coupled energy networks. The framework integrates the optimization modeling package PLASMO and the simulation package DMNetwork (built around PETSc). These tools use a common graphbased abstraction that enables us to achieve compatibility between data structures and to build applications that use network models of different physical fidelity. We also describe how to embed these tools within complex computational workflows using SWIFT, which is a tool that facilitates parallel execution of multiple simulation runs and management of input and output data. We discuss how to use these capabilities to target coupled natural gas and electricity systems.

42 ENGINEERING↗
NASA NTRS2006

Protocols for Handling Messages Between Simulation Computers

Practical Simulator Network (PSimNet) is a set of data-communication protocols designed especially for use in handling messages between computers that are engaging cooperatively in real-time or nearly-real-time training simulations. In a typical application, computers that provide individualized training at widely dispersed locations would communicate, by use of PSimNet, with a central host computer that would provide a common computational- simulation environment and common data. Originally intended for use in supporting interfaces between training computers and computers that simulate the responses of spacecraft scientific payloads, PSimNet could be especially well suited for a variety of other applications -- for example, group automobile-driver training in a classroom. Another potential application might lie in networking of automobile-diagnostic computers at repair facilities to a central computer that would compile the expertise of numerous technicians and engineers and act as an expert consulting technician.

Balcerowski, John P.↗
DOE OSTI2024

Containers on Switches: A Cluster School Experience

Network switches, such as those from Arista and Mellanox, often have underutilized computational resources in the form of built-in processors and memory. By leveraging these untapped resources, we can optimize functionality and efficiency of computational cluster networks. Our research focuses on deploying containers directly onto these switches to execute various auxiliary tasks ranging from metric logging to system-wide management via post-boot configuration. By doing so, we can significantly enchance the capabilities of the cluster without the need for additional dedicated hardware. Our research involved five distinct scenarios where switch utilization could have a profound impact on HPC Clusters: run cloud-init services via link-local connection; configuring a Telegraf container to export metrics; deploying a caching proxy; creating a reconfigurable IPv6 DHCP/DNS provider for VLAN; and implementing a client detection with Magellan discovery. These scenarios were containerized with podman and docker, and tested both physically on the switch virtually on a QEMU VM both running SONiC OS. Testing and findings indicate that network switches can indeed be used for these scenarios. They offer a wide range of possibilities beyond these applications. They run as expected as containers on the switches, and although there were some minor issues, work-arounds were implemented. Overall, this is a positive result that can be further explored with more scenarios.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Measuring the Energy Consumption and Efficiency of Deep Neural Networks: An Empirical Analysis and Design Recommendations

Addressing the "Red-AI" trend of rising energy consumption by large-scale neural networks, this study investigates the measured energy consumption of training various fully connected neural network architectures. We introduce the BUTTER-E dataset, an augmentation to the BUTTER Empirical Deep Learning dataset, containing energy consumption and performance data from 41,129 individual experimental runs spanning 30,582 distinct configurations: 13 datasets, 20 sizes (trainable parameters), 8 "shapes", and 14 depths on both CPUs and GPUs using node-level watt-meters. This dataset reveals the complex relationship between dataset size, network structure, and energy use. Our analysis uncovers a surprising, hardware-mediated non-linear relationship between energy efficiency and network design, challenging the assumption that reducing the number of parameters or FLOPs is the best way to achieve greater energy efficiency. We propose a straightforward and effective energy model that accounts for network size, computing, and memory hierarchy. Highlighting the need for cache-considerate algorithm development, we suggest a codesign approach to energy efficient network, algorithm, and hardware design. This work contributes to the fields of sustainable computing and Green AI, offering practical guidance for creating more energy-efficient neural networks and promoting sustainable AI.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

DeePMD-kit v2: A software package for deep potential models

DeePMD-kit is a powerful open-source software package that facilitates molecular dynamics simulations using machine learning potentials known as Deep Potential (DP) models. This package, which was released in 2017, has been widely used in the fields of physics, chemistry, biology, and material science for studying atomistic systems. The current version of DeePMD-kit offers numerous advanced features, such as DeepPot-SE, attention-based and hybrid descriptors, the ability to fit tensile properties, type embedding, model deviation, DP-range correction, DP long range, graphics processing unit support for customized operators, model compression, non-von Neumann molecular dynamics, and improved usability, including documentation, compiled binary packages, graphical user interfaces, and application programming interfaces. This article presents an overview of the current major version of the DeePMD-kit package, highlighting its features and technical details. Additionally, this article presents a comprehensive procedure for conducting molecular dynamics as a representative application, benchmarks the accuracy and efficiency of different models, and discusses ongoing developments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Streaming Data Reorganization at Scale with DeltaFS Indexed Massive Directories

We report complex storage stacks providing data compression, indexing, and analytics help leverage the massive amounts of data generated today to derive insights. It is challenging to perform this computation, however, while fully utilizing the underlying storage media. This is because, while storage servers with large core counts are widely available, single-core performance and memory bandwidth per core grow slower than the core count per die. Computational storage offers a promising solution to this problem by utilizing dedicated compute resources along the storage processing path. We present DeltaFS Indexed Massive Directories (IMDs), a new approach to computational storage. DeltaFS IMDs harvest available (i.e., not dedicated) compute, memory, and network resources on the compute nodes of an application to perform computation on data. We demonstrate the efficiency of DeltaFS IMDs by using them to dynamically reorganize the output of a real-world simulation application across 131,072 CPU cores. DeltaFS IMDs speed up reads by 1,740x while only slightly slowing down the writing of data during simulation I/O for in situ data processing.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2003

Perspectives on Emerging/Novel Computing Paradigms and Future Aerospace Workforce Environments

The accelerating pace of the computing technology development shows no signs of abating. Computing power reaching 100 Tflop/s is likely to be reached by 2004 and Pflop/s (10(exp 15) Flop/s) by 2007. The fundamental physical limits of computation, including information storage limits, communication limits and computation rate limits will likely be reached by the middle of the present millennium. To overcome these limits, novel technologies and new computing paradigms will be developed. An attempt is made in this overview to put the diverse activities related to new computing-paradigms in perspective and to set the stage for the succeeding presentations. The presentation is divided into five parts. In the first part, a brief historical account is given of development of computer and networking technologies. The second part provides brief overviews of the three emerging computing paradigms grid, ubiquitous and autonomic computing. The third part lists future computing alternatives and the characteristics of future computing environment. The fourth part describes future aerospace workforce research, learning and design environments. The fifth part lists the objectives of the workshop and some of the sources of information on future computing paradigms.

Noor, Ahmed K.↗
NASA NTRS2006

Montage Version 3.0

The final version (3.0) of the Montage software has been released. To recapitulate from previous NASA Tech Briefs articles about Montage: This software generates custom, science-grade mosaics of astronomical images on demand from input files that comply with the Flexible Image Transport System (FITS) standard and contain image data registered on projections that comply with the World Coordinate System (WCS) standards. This software can be executed on single-processor computers, multi-processor computers, and such networks of geographically dispersed computers as the National Science Foundation s TeraGrid or NASA s Information Power Grid. The primary advantage of running Montage in a grid environment is that computations can be done on a remote supercomputer for efficiency. Multiple computers at different sites can be used for different parts of a computation a significant advantage in cases of computations for large mosaics that demand more processor time than is available at any one site. Version 3.0 incorporates several improvements over prior versions. The most significant improvement is that this version is accessible to scientists located anywhere, through operational Web services that provide access to data from several large astronomical surveys and construct mosaics on either local workstations or remote computational grids as needed.

Jacob, Joseph↗
NASA NTRS2013

Multiple-Frame Detection of Subpixel Targets in Thermal Image Sequences

The new technology in this approach combines the subpixel detection information from multiple frames of a sequence to achieve a more sensitive detection result, using only the information found in the images themselves. It is taken as a constraint that the method is automated, robust, and computationally feasible for field networks with constrained computation and data rates. This precludes simply downloading a video stream for pixel-wise co-registration on the ground. It is also important that this method not require precise knowledge of sensor position or direction, because such information is often not available. It is also assumed that the scene in question is approximately planar, which is appropriate for a high-altitude airborne or orbital view.

Thompson, David R.↗
NASA NTRS1996

A Comprehensive and Cost-Effective Computer Infrastructure for K-12 Schools

Since 1993, NASA Langley Research Center has been developing and implementing a low-cost Internet connection model, including system architecture, training, and support, to provide Internet access for an entire network of computers. This infrastructure allows local area networks which exceed 50 machines per school to independently access the complete functionality of the Internet by connecting to a central site, using state-of-the-art commercial modem technology, through a single standard telephone line. By locating high-cost resources at this central site and sharing these resources and their costs among the school districts throughout a region, a practical, efficient, and affordable infrastructure for providing scale-able Internet connectivity has been developed. As the demand for faster Internet access grows, the model has a simple expansion path that eliminates the need to replace major system components and re-train personnel. Observations of optical Internet usage within an environment, particularly school classrooms, have shown that after an initial period of 'surfing,' the Internet traffic becomes repetitive. By automatically storing requested Internet information on a high-capacity networked disk drive at the local site (network based disk caching), then updating this information only when it changes, well over 80 percent of the Internet traffic that leaves a location can be eliminated by retrieving the information from the local disk cache.

Warren, G. P.↗
NASA NTRS1985

The application of artificial intelligence techniques to large distributed networks

Data accessibility and transfer of information, including the land resources information system pilot, are structured as large computer information networks. These pilot efforts include the reduction of the difficulty to find and use data, reducing processing costs, and minimize incompatibility between data sources. Artificial Intelligence (AI) techniques were suggested to achieve these goals. The applicability of certain AI techniques are explored in the context of distributed problem solving systems and the pilot land data system (PLDS). The topics discussed include: PLDS and its data processing requirements, expert systems and PLDS, distributed problem solving systems, AI problem solving paradigms, query processing, and distributed data bases.

Dubyah, R.↗
DOE OSTI2014

Sampling Approaches for Multi-Domain Internet Performance Measurement Infrastructures

The next-generation of high-performance networks being developed in DOE communities are critical for supporting current and emerging data-intensive science applications. The goal of this project is to investigate multi-domain network status sampling techniques and tools to measure/analyze performance, and thereby provide “network awareness” to end-users and network operators in DOE communities. We leverage the infrastructure and datasets available through perfSONAR, which is a multi-domain measurement framework that has been widely deployed in high-performance computing and networking communities; the DOE community is a core developer and the largest adopter of perfSONAR. Our investigations include development of semantic scheduling algorithms, measurement federation policies, and tools to sample multi-domain and multi-layer network status within perfSONAR deployments. We validate our algorithms and policies with end-to-end measurement analysis tools for various monitoring objectives such as network weather forecasting, anomaly detection, and fault-diagnosis. In addition, we develop a multi-domain architecture for an enterprise-specific perfSONAR deployment that can implement monitoring-objective based sampling and that adheres to any domain-specific measurement policies.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1991

Numerical Aerodynamic Simulation Program

Report describes developments that occurred at National Aerodynamics Simulation (NAS) facility at Ames Research Center during years 1987 and 1988. Begins with description of NAS processing network, which is large network of computers. Followed by summary of early achievements of program and advanced features of network, including installation of supercomputers, installation of standard operating system and communication software on all processors, accessibility to users at remote facilities across United States, and emphasis on development of graphics workstations to display results of numerical simulation.

Bailey, F. R.↗
NASA NTRS1990

About time

Time has historically been a measure of progress of recurrent physical processes. Coordination of future actions, prediction of future events, and assigning order to events are three practical reasons for implementing clocks and signalling mechanisms. In large networks of computers, these needs lead to the problem of synchronizing the clocks throughout the network. Recent methods allow this to be done in large networks with precision around 1 millisecond despite mean message exchange times near 5 milliseconds. These methods are discussed.

Denning, Peter J.↗
NASA NTRS2002

Fractal Analysis of Drainage Basins on Mars

We used statistical properties of drainage networks on Mars as a measure of martian landscape morphology and an indicator of landscape evolution processes. We utilize the Mars Orbiter Laser Altimeter (MOLA) data to construct digital elevation maps (DEMs) of several, mostly ancient, martian terrains. Drainage basins and channel networks are computationally extracted from DEMs and their structures are analyzed and compared to drainage networks extracted from terrestrial and lunar DEMs. We show that martian networks are self-affine statistical fractals with planar properties similar to terrestrial networks, but vertical properties similar to lunar networks. The uniformity of martian drainage density is between those for terrestrial and lunar landscapes. Our results are consistent with the roughening of ancient martian terrains by combination of rainfall-fed erosion and impacts, although roughening by other fluvial processes cannot be excluded. The notion of sustained rainfall in recent Mars history is inconsistent with our findings.

Stepinski, T. F.↗
DOE OSTI2016

An Application Development Platform for Neuromorphic Computing

Dynamic Adaptive Neural Network Arrays (DANNAs) are neuromorphic computing systems developed as a hardware based approach to the implementation of neural networks. They feature highly adaptive and programmable structural elements, which model arti cial neural networks with spiking behavior. We design them to solve problems using evolutionary optimization. In this paper, we highlight the current hardware and software implementations of DANNA, including their features, functionalities and performance. We then describe the development of an Application Development Platform (ADP) to support efficient application implementation and testing of DANNA based solutions. We conclude with future directions.

Dean, Mark↗
NASA NTRS1985

Some key considerations in evolving a computer system and software engineering support environment for the space station program

The space station data management system involves networks of computing resources that must work cooperatively and reliably over an indefinite life span. This program requires a long schedule of modular growth and an even longer period of maintenance and operation. The development and operation of space station computing resources will involve a spectrum of systems and software life cycle activities distributed across a variety of hosts, an integration, verification, and validation host with test bed, and distributed targets. The requirement for the early establishment and use of an apporopriate Computer Systems and Software Engineering Support Environment is identified. This environment will support the Research and Development Productivity challenges presented by the space station computing system.

Mckay, C. W.↗