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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 sources NASA NTRS DOE OSTI

NASA NTRS1991

The AI Bus architecture for distributed knowledge-based systems

The AI Bus architecture is layered, distributed object oriented framework developed to support the requirements of advanced technology programs for an order of magnitude improvement in software costs. The consequent need for highly autonomous computer systems, adaptable to new technology advances over a long lifespan, led to the design of an open architecture and toolbox for building large scale, robust, production quality systems. The AI Bus accommodates a mix of knowledge based and conventional components, running on heterogeneous, distributed real world and testbed environment. The concepts and design is described of the AI Bus architecture and its current implementation status as a Unix C++ library or reusable objects. Each high level semiautonomous agent process consists of a number of knowledge sources together with interagent communication mechanisms based on shared blackboards and message passing acquaintances. Standard interfaces and protocols are followed for combining and validating subsystems. Dynamic probes or demons provide an event driven means for providing active objects with shared access to resources, and each other, while not violating their security.

Schultz, Roger D.↗

DOE OSTI2021

Charged Particle Tracking via Edge-Classifying Interaction Networks

Recent work has demonstrated that geometric deep learning methods such as graph neural networks (GNNs) are well suited to address a variety of reconstruction problems in high-energy particle physics. In particular, particle tracking data are naturally represented as a graph by identifying silicon tracker hits as nodes and particle trajectories as edges, given a set of hypothesized edges, edge-classifying GNNs identify those corresponding to real particle trajectories. In this work, we adapt the physics-motivated interaction network (IN) GNN toward the problem of particle tracking in pileup conditions similar to those expected at the high-luminosity Large Hadron Collider. Assuming idealized hit filtering at various particle momenta thresholds, we demonstrate the IN’s excellent edge-classification accuracy and tracking efficiency through a suite of measurements at each stage of GNN-based tracking: graph construction, edge classification, and track building. The proposed IN architecture is substantially smaller than previously studied GNN tracking architectures; this is particularly promising as a reduction in size is critical for enabling GNN-based tracking in constrained computing environments. Furthermore, the IN may be represented as either a set of explicit matrix operations or a message passing GNN. Efforts are underway to accelerate each representation via heterogeneous computing resources towards both high-level and low-latency triggering applications.

accelerator physics↗

NASA NTRS1997

New NAS Parallel Benchmarks Results

NPB2 (NAS (NASA Advanced Supercomputing) Parallel Benchmarks 2) is an implementation, based on Fortran and the MPI (message passing interface) message passing standard, of the original NAS Parallel Benchmark specifications. NPB2 programs are run with little or no tuning, in contrast to NPB vendor implementations, which are highly optimized for specific architectures. NPB2 results complement, rather than replace, NPB results. Because they have not been optimized by vendors, NPB2 implementations approximate the performance a typical user can expect for a portable parallel program on distributed memory parallel computers. Together these results provide an insightful comparison of the real-world performance of high-performance computers. New NPB2 features: New implementation (CG), new workstation class problem sizes, new serial sample versions, more performance statistics.

Yarrow, Maurice↗

DOE OSTI2014

Improving the Performance of the Extreme-scale Simulator

Investigating the performance of parallel applications at scale on future high-performance computing (HPC) architectures and the performance impact of different architecture choices is an important component of HPC hardware/software co-design. The Extreme-scale Simulator (xSim) is a simulation-based toolkit for investigating the performance of parallel applications at scale. xSim scales to millions of simulated Message Passing Interface (MPI) processes. The overhead introduced by a simulation tool is an important performance and productivity aspect. This paper documents two improvements to xSim: (1) a new deadlock resolution protocol to reduce the parallel discrete event simulation management overhead and (2) a new simulated MPI message matching algorithm to reduce the oversubscription management overhead. The results clearly show a significant performance improvement, such as by reducing the simulation overhead for running the NAS Parallel Benchmark suite inside the simulator from 1,020\% to 238% for the conjugate gradient (CG) benchmark and from 102% to 0% for the embarrassingly parallel (EP) and benchmark, as well as, from 37,511% to 13,808% for CG and from 3,332% to 204% for EP with accurate process failure simulation.

Engelmann, Christian↗

DOE OSTI2017

Home Energy Management System - VOLTTRON Integration

In most Home Energy Management Systems (HEMS) available in the market, different devices running different communication protocols cannot interact with each other and exchange information. As a result of this integration, the information about different devices running different communication protocol can be accessible by other agents and devices running on VOLTTRON platform. The integration process can be used by any HEMS available in the market regardless of the programming language they use. If the existing HEMS provides an Application Programming Interface (API) based on the RESTFul architecture, that API can be used for integration. Our candidate HEMS in this project is home-assistant (Hass). An agent is implemented which can communicate with the Hass API and receives information about the devices loaded on the API. The agent publishes the information it receives on the VOLTTRON message bus so other agents can have access to this information. On the other side, for each type of devices, an agent is implemented such as Climate Agent, Lock Agent, Switch Agent, Light Agent, etc. Each of these agents is subscribed to the messages published on the message bus about their associated devices. These agents can also change the status of the devices by sending appropriate service calls to the API. Other agents and services on the platform can also access this information and coordinate their decision-making process based on this information.

Zandi, Helia↗

DOE OSTI2017

Home Energy Management System - VOLTTRON Integration

Zandi, Helia↗

NASA NTRS1995

New applications for the EUTELTRACS service

The EUTELTRACS two-way Mobile Satellite Messaging and Automatic Satellite Position Reporting (ASPR) service is Europe's first commercially operated Mobile Satellite Service. It was introduced by the European Telecommunications Satellite Organization (EUTELSAT) for commercial service in 1991. The system is based on a centralized network architecture organized around a single hub station operated by EUTELSAT. Initially the system was designed with a close user group architecture enabling a mobile user to communicate exclusively with its own headquarters. This paper describes the new applications (design and tests prior to their introduction into service) especially developed for the European market and particularly the Double Hop Services opening the system to authorized external entities. In addition, the European Commission (EC) pilot demonstrations in which the EUTELTRACS system is involved are described.

Colcy, Jean-Noel↗

NASA NTRS2018

Delay Tolerant Network Routing as a Machine Learning Classification Problem

This paper discusses a machine learning-based approach to routing for delay tolerant networks (DTNs) [1]. DTNs are networks which experience frequent disconnections between nodes, uncertainty of an end-to-end path, long one-way trip times, and may have high error rates and asymmetric links. Such networks exist in deep space satellite networks, very rural environments, disaster areas and underwater environments. In this work, we use machine learning classifiers to predict a set of neighboring nodes which are the most likely to deliver a message to a desired location based on message history delivery information.We use the Common Open Research Emulator (CORE) [2] to emulate the DTN environment based on real-world location traces and collect network traffic statistics from the Bundle Protocol implementation IBR-DTN [3]. The software architecture for classification-based routing, analysis and preparation of the network history data and prediction results are discussed.

Delay Tolerant Networks↗

NASA NTRS2008

Orchestrator Telemetry Processing Pipeline

Orchestrator is a software application infrastructure for telemetry monitoring, logging, processing, and distribution. The architecture has been applied to support operations of a variety of planetary rovers. Built in Java with the Eclipse Rich Client Platform, Orchestrator can run on most commonly used operating systems. The pipeline supports configurable parallel processing that can significantly reduce the time needed to process a large volume of data products. Processors in the pipeline implement a simple Java interface and declare their required input from upstream processors. Orchestrator is programmatically constructed by specifying a list of Java processor classes that are initiated at runtime to form the pipeline. Input dependencies are checked at runtime. Fault tolerance can be configured to attempt continuation of processing in the event of an error or failed input dependency if possible, or to abort further processing when an error is detected. This innovation also provides support for Java Message Service broadcasts of telemetry objects to clients and provides a file system and relational database logging of telemetry. Orchestrator supports remote monitoring and control of the pipeline using browser-based JMX controls and provides several integration paths for pre-compiled legacy data processors. At the time of this reporting, the Orchestrator architecture has been used by four NASA customers to build telemetry pipelines to support field operations. Example applications include high-volume stereo image capture and processing, simultaneous data monitoring and logging from multiple vehicles. Example telemetry processors used in field test operations support include vehicle position, attitude, articulation, GPS location, power, and stereo images.

Powell, Mark↗

DOE OSTI2016

Multispeaker

MultiSpeaker is a software application that parses wsdl and xsd files that define the MultiSpeak protocol. The MultiSpeak protocol (www.multispeak.org) is a SOA-based integration architecture that defines the complex communications between various endpoints of a utility company. MultiSpeaker parses the files and presents an easy to read and understand representation of the underlying protocol. The user may then use visual clues to know what message elements are required, descriptions for the elements along with valid entries. The user may then edit or modify the payload of the actual messages. MultiSpeaker also provides a mechanism for scheduling multiple modified protocol messages.

Source record↗

NASA NTRS2003

Enhanced Multi-Modal Access to Planetary Exploration

Tomorrow's Interplanetary Network (IPN) will evolve from JPL's Deep-Space Network (DSN) and provide key capabilities to future investigators, such as simplified acquisition of higher-quality science at remote sites and enriched access to these sites. These capabilities could also be used to foster public interest, e.g., by making it possible for students to explore these environments personally, eventually perhaps interacting with a virtual world whose models could be populated by data obtained continuously from the IPN. Our paper looks at JPL's approach to making this evolution happen, starting from improved communications. Evolving space protocols (e.g., today's CCSDS proximity and file-transfer protocols) will provide the underpinning of such communications in the next decades, just as today's rich web was enabled by progress in Internet Protocols starting from the early 1970's (ARPAnet research). A key architectural thrust of this effort is to deploy persistent infrastructure incrementally, using a layered service model, where later higher-layer capabilities (such as adaptive science planning) are enabled by earlier lower-layer services (such as automated routing of object-based messages). In practice, there is also a mind shift needed from an engineering culture raised on point-to-point single-function communications (command uplink, telemetry downlink), to one in which assets are only indirectly accessed, via well-defined interfaces. We are aiming to foster a 'community of access' both among space assets and the humans who control them. This enables appropriate (perhaps eventually optimized) sharing of services and resources to the greater benefit of all participants. We envision such usage to be as automated in the future as using a cell phone is today - with all the steps in creating the real-time link being automated.

interplanetary network (IPN)↗

DOE OSTI2026

Scaling kinetic Monte-Carlo simulations of grain growth with combined convolutional and graph neural networks

Graph neural networks (GNN) have emerged as a promising machine learning method for microstructure simulations such as grain growth. However, accurate modeling of realistic grain boundary networks requires large simulation cells, which GNN has difficulty scaling up to. To alleviate the computational costs and memory footprint of GNN, we suggest a hybrid architecture combining a convolutional neural network (CNN) based bijective autoencoder to compress the spatial dimensions, and a GNN that evolves the microstructure in the latent space of reduced spatial sizes. Our results demonstrate that the new design significantly reduces computational costs with using fewer message passing layer (from 12 down to 3) compared with GNN alone. The reduction in computational cost becomes more pronounced as the spatial size increases, indicating strong computational scalability. For the largest mesh evaluated (160 3 ), our method reduces memory usage and runtime in inference by 117× and 115×, respectively, compared with GNN-only baseline. More importantly, it shows higher accuracy and stronger spatiotemporal capability than the GNN-only baseline, especially in long-term testing. Such combination of scalability and accuracy is essential for simulating realistic material microstructures over extended time scales. The improvements can be attributed to the bijective autoencoder’s ability to compress information losslessly from spatial domain into a high dimensional feature space, thereby producing more expressive latent features for the GNN to learn from, while also contributing its own spatiotemporal modeling capability. Training data are generated from stochastic grain growth simulations, providing realistic variability for learning robust microstructure evolution. Comprehensive system validation confirms that the model is accurate, robust, and scalable.

36 MATERIALS SCIENCE↗

NASA NTRS1994

Advanced information processing system: Authentication protocols for network communication

In safety critical I/O and intercomputer communication networks, reliable message transmission is an important concern. Difficulties of communication and fault identification in networks arise primarily because the sender of a transmission cannot be identified with certainty, an intermediate node can corrupt a message without certainty of detection, and a babbling node cannot be identified and silenced without lengthy diagnosis and reconfiguration . Authentication protocols use digital signature techniques to verify the authenticity of messages with high probability. Such protocols appear to provide an efficient solution to many of these problems. The objective of this program is to develop, demonstrate, and evaluate intercomputer communication architectures which employ authentication. As a context for the evaluation, the authentication protocol-based communication concept was demonstrated under this program by hosting a real-time flight critical guidance, navigation and control algorithm on a distributed, heterogeneous, mixed redundancy system of workstations and embedded fault-tolerant computers.

Harper, Richard E.↗

DOE OSTI2023

Optimizing Communication in 2D Grid-Based MPI Applications at Exascale

The new reality of exascale computing faces many challenges in achieving optimal performance on large numbers of nodes. A key challenge is the efficient utilization of the message-passing interface (MPI), a critical component for process communication. This paper explores communication optimization strategies to harness the GPU-accelerated architectures of these supercomputers. We focus on MPI applications where processors form a two-dimensional process grid, a common arrangement in applications involving dense matrix operations. This configuration offers a unique opportunity to implement innovative strategies to improve performance and maintain effective load distribution. We study two applications— Dist-FW (Apsp:all-pair-shortest-path) and HPL-MxP (LU factorization with Mixed precision)—on two accelerated systems: Summit (IBM Power and NVIDIA V100) and Frontier (AMD EPYC and MI250X). These supercomputers are operated by the Oak Ridge Leadership Computing Facility (OLCF) and are currently ranked #1 and #5 on the Top500 list. We show how to scale up both applications to exascale levels and tackle the MPI challenges related to implementation, synchronization, and performance. We also compare the performance of several communication strategies at an unprecedented scale. Accurately predicting application performance becomes crucial for cost reduction as the computational scale grows. To address this, we suggest a hyperbolic model as a better alternative to the traditional one-sided asymptotic model for predicting future application performance at such large scales.

Lu, Hao↗

NASA NTRS2018

Software System for the Mars 2020 Mission Sampling and Caching Testbeds

The development of the Sampling and Caching Subsystem (SCS) of the Mars 2020 Rover Mission is highly dependent on testing of prototype hardware and software operating in explicit conditions as part of integrated testbeds. To achieve relevant integration of hardware and software while maintaining rapid algorithm development capabilities and high testing throughput, the Controls and Autonomy for Sample Acquisition and Handling (CASAH) software system was developed. CASAH is an implementation of the Intelligent Robotics System Architecture (IRSA),which mimics JPL Flight Software (FSW) in that it is divided into hierarchical modules that run separate processes that communicate via message passing, each module is assigned an owner that is a single developer, and the operator initiates requests via a text-based interface that interprets sequences of commands.IRSA enables a modular breakdown of CASAH that follows that of 2020 Flight Software,so developers can take an algorithm from a module in CASAH and re-code it into the same module in FSW. As deployment of CASAH has grown to ten testbeds - each with different hardware and objectives - bottom-up design decisions have been intentionally made to keep the system lightweight and maintainable by a very small team. To date, CASAH has been used to run 1393 different tests. This work describes CASAH, the testbeds and functionality it supports, the tools used to manage the development and sharing of code, and the features of the software. Lessons learned over the past three years of development and deployment are provided.

Vieira, Peter↗

NASA NTRS1992

A self-defining hierarchical data system

The Self-Defining Data System (SDS) is a system which allows the creation of self-defining hierarchical data structures in a form which allows the data to be moved between different machine architectures. Because the structures are self-defining they can be used for communication between independent modules in a distributed system. Unlike disk-based hierarchical data systems such as Starlink's HDS, SDS works entirely in memory and is very fast. Data structures are created and manipulated as internal dynamic structures in memory managed by SDS itself. A structure may then be exported into a caller supplied memory buffer in a defined external format. This structure can be written as a file or sent as a message to another machine. It remains static in structure until it is reimported into SDS. SDS is written in portable C and has been run on a number of different machine architectures. Structures are portable between machines with SDS looking after conversion of byte order, floating point format, and alignment. A Fortran callable version is also available for some machines.

Bailey, J.↗

NASA NTRS2007

Distributed Operations Planning

Maestro software provides a secure and distributed mission planning system for long-term missions in general, and the Mars Exploration Rover Mission (MER) specifically. Maestro, the successor to the Science Activity Planner, has a heavy emphasis on portability and distributed operations, and requires no data replication or expensive hardware, instead relying on a set of services functioning on JPL institutional servers. Maestro works on most current computers with network connections, including laptops. When browsing down-link data from a spacecraft, Maestro functions similarly to being on a Web browser. After authenticating the user, it connects to a database server to query an index of data products. It then contacts a Web server to download and display the actual data products. The software also includes collaboration support based upon a highly reliable messaging system. Modifications made to targets in one instance are quickly and securely transmitted to other instances of Maestro. The back end that has been developed for Maestro could benefit many future missions by reducing the cost of centralized operations system architecture.

Fox, Jason↗

NASA NTRS2003

Increasing the Operational Value of Event Messages

Assessing the health of a space mission has traditionally been performed using telemetry analysis tools. Parameter values are compared to known operational limits and are plotted over various time periods. This presentation begins with the notion that there is an incredible amount of untapped information contained within the mission s event message logs. Through creative advancements in message handling tools, the event message logs can be used to better assess spacecraft and ground system status and to highlight and report on conditions not readily apparent when messages are evaluated one-at-a-time during a real-time pass. Work in this area is being funded as part of a larger NASA effort at the Goddard Space Flight Center to create component-based, middleware-based, standards-based general purpose ground system architecture referred to as GMSEC - the GSFC Mission Services Evolution Center. The new capabilities and operational concepts for event display, event data analyses and data mining are being developed by Lockheed Martin and the new subsystem has been named GREAT - the GMSEC Reusable Event Analysis Toolkit. Planned for use on existing and future missions, GREAT has the potential to increase operational efficiency in areas of problem detection and analysis, general status reporting, and real-time situational awareness.

Li, Zhenping↗