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At least 631 records · Page 35

A report on SHARP (Spacecraft Health Automated Reasoning Prototype) and the Voyager Neptune encounter

The development and application of the Spacecraft Health Automated Reasoning Prototype (SHARP) for the operations of the telecommunications systems and link analysis functions in Voyager mission operations are presented. An overview is provided of the design and functional description of the SHARP system as it was applied to Voyager. Some of the current problems and motivations for automation in real-time mission operations are discussed, as are the specific solutions that SHARP provides. The application of SHARP to Voyager telecommunications had the goal of being a proof-of-capability demonstration of artificial intelligence as applied to the problem of real-time monitoring functions in planetary mission operations. AS part of achieving this central goal, the SHARP application effort was also required to address the issue of the design of an appropriate software system architecture for a ground-based, highly automated spacecraft monitoring system for mission operations, including methods for: (1) embedding a knowledge-based expert system for fault detection, isolation, and recovery within this architecture; (2) acquiring, managing, and fusing the multiple sources of information used by operations personnel; and (3) providing information-rich displays to human operators who need to exercise the capabilities of the automated system. In this regard, SHARP has provided an excellent example of how advanced artificial intelligence techniques can be smoothly integrated with a variety of conventionally programmed software modules, as well as guidance and solutions for many questions about automation in mission operations.

Martin, R. G.↗

A Review of Software for Designing and Operating Quantum Networks

Quantum networks development is crucial to realizing a production-grade network that can support distributed sensing, secure communication, and utility-scale quantum computation. However, the transition from laboratory demonstration to deployable networks requires software implementations of architectures and protocols tailored to the unique constraints of quantum systems. This paper reviews the current state of software implementations for quantum networks, organized around a three-plane abstraction of infrastructure, logical, and control/service planes. We cover software for both designing quantum network protocols (e.g., SeQUeNCe, QuISP, and NetSquid) and operating testbeds, with a focus on essential control/service plane functions such as entanglement, topology, and resource management, in a proposed taxonomy. Our review highlights a persistent gap between theoretical architecture and protocol proposals and their realization in simulators or testbeds, particularly in dynamic topology and network management. We conclude by outlining open challenges and proposing a roadmap for developing scalable software architectures to enable hybrid, large-scale quantum networks.

Network Design↗

Runtime Techniques to Enable a Highly-Scalable Global Address Space Model for Petascale Computing

Over the past decade, the trajectory to the petascale has been built on increased complexity and scale of the underlying parallel architectures. Meanwhile, software developers have struggled to provide tools that maintain the productivity of computational science teams using these new systems. In this regard, Global Address Space (GAS) programming models provide a straightforward and easy to use addressing model, which can lead to improved productivity. However, the scalability of GAS depends directly on the design and implementation of the runtime system on the target petascale distributed-memory architecture. In this paper, we describe the design, implementation, and optimization of the Aggregate Remote Memory Copy Interface (ARMCI) runtime library on the Cray XT5 2.3 PetaFLOPs computer at Oak Ridge National Laboratory. We optimized our implementation with the flow intimation technique that we have introduced in this paper. Our optimized ARMCI implementation improves scalability of both the Global Arrays programming model and a real-world chemistry application—NWChem—from small jobs up through 180,000 cores.

Computer Science↗

ARM Data Integrator

The Atmospheric Radiation Measurement (ARM) Data Integrator (ADI) streamlines the development of scientific algorithms and analysis of time-series NetCDF data, and improves the content and consistency of the output data products produced by these algorithms. The framework automates the process of retrieving and preparing data for analysis, and allows users to design output data products through a graphical interface. It also provides a modular, flexible software development architecture that scientists can use to generate C, Python, and IDL source code templates that embed the pre and post processing logic allowing the scientist to focus on only their science. The input data, preprocessing, and output data specifications of algorithms are defined through a graphical interface and stored in a database. ADI implements workflow for data integration and supports user access to data through a library of software modules. Data preprocess capabilities supported include automated retrieval of data from input files, merging the retrieved data into appropriately sized chunks, and transformation of the data onto a common coordinate system grid. Through the graphical interface, users can view the details of both their data products and those in the ARM catalog and allows developers to use existing data product to build new data products. Views of the output data products include an overlay of how the design meets ARM archive's data standards providing the user with a visual cue indicating where their output violates an archive standard. The ADI libraries access the information provided through the GUI via a Postgres database. The ADI framework and its supporting components can significantly decrease the time and cost of implementing scientific algorithms while improving the ability of scientists to disseminate their results.

Source record↗

ARM Data Integrator

The Atmospheric Radiation Measurement (ARM) Data Integrator (ADI) streamlines the development of scientific algorithms and analysis of time-series NetCDF data, and improves the content and consistency of the output data products produced by these algorithms. The framework automates the process of retrieving and preparing data for analysis, and allows users to design output data products through a graphical interface. It also provides a modular, flexible software development architecture that scientists can use to generate C, Python, and IDL source code templates that embed the pre and post processing logic allowing the scientist to focus on only their science. The input data, preprocessing, and output data specifications of algorithms are defined through a graphical interface and stored in a database. ADI implements workflow for data integration and supports user access to data through a library of software modules. Data preprocess capabilities supported include automated retrieval of data from input files, merging the retrieved data into appropriately sized chunks, and transformation of the data onto a common coordinate system grid. Through the graphical interface, users can view the details of both their data products and those in the ARM catalog and allows developers to use existing data product to build new data products. Views of the output data products include an overlay of how the design meets ARM archive's data standards providing the user with a visual cue indicating where their output violates an archive standard. The ADI libraries access the information provided through the GUI via a Postgres database. The ADI framework and its supporting components can significantly decrease the time and cost of implementing scientific algorithms while improving the ability of scientists to disseminate their results.

Source record↗

Multidisciplinary High-Fidelity Analysis and Optimization of Aerospace Vehicles: Preliminary Results - Part 2

An objective of the High Performance Computing and Communication Program at the NASA Langley Research Center is to demonstrate multidisciplinary shape and sizing optimization of a complete aerospace vehicle configuration by using high-fidelity finite-element structural analysis and computational fluid dynamics aerodynamic analysis in a distributed, heterogeneous computing environment that includes high performance parallel computing. A software system has been designed and implemented to integrate a set of existing discipline analysis codes, some of them computationally intensive, into a distributed computational environment for the design of a high-speed civil transport configuration. The paper describes both the preliminary results from implementing and validating the multidisciplinary analysis and the results from an aerodynamic optimization. The discipline codes are integrated by using the Java programming language and a Common Object Request Broker Architecture compliant software product. A companion paper describes the formulation of the multidisciplinary analysis and optimization system.

Walsh, J. L.↗

UQpy: A general purpose Python package and development environment for uncertainty quantification

In this paper, we present the UQpy software toolbox, an open-source Python package for general uncertainty quantification (UQ) in mathematical and physical systems. The software serves as both a user-ready toolbox that includes many of the latest methods for UQ in computational modeling and a convenient development environment for Python programmers advancing the field of UQ. The paper presents an introduction to the software's architecture and existing capabilities, divided in the code in a set of modules centered around different UQ tasks such as sampling methods, generation of random processes and random fields, probabilistic inverse modeling, reliability analysis, surrogate modeling, and active learning. The paper also highlights the importance of the RunModel module, which is used to drive simulations in the uncertainty analyses performed in UQpy. This module conveniently allows the user to define computational models directly in Python, or to run simulations from a third-party software in serial or in parallel. To illustrate the various capabilities, two examples are tracked throughout the paper and analyzed repeatedly for various UQ tasks. The first is a Python model solving a nonlinear structural dynamics problem, used to illustrate UQpy's capabilities in sampling and forward propagation of high dimensional random vectors (stochastic processes), and probabilistic inference. The second model is a third-party Abaqus finite element model solving the thermomechanical response of a beam structure. This example is used to illustrate UQpy's capabilities in variance reduction sampling techniques, reliability analysis, surrogate modeling and active learning techniques.

97 MATHEMATICS AND COMPUTING↗

Customizing the JPL Multimission Ground Data System: Lessons learned

The Multimission Ground Data System (MGDS) at NASA's Jet Propulsion Laboratory has brought improvements and new technologies to mission operations. It was designed as a generic data system to meet the needs of multiple missions and avoid re-inventing capabilities for each new mission and thus reduce costs. It is based on adaptable tools that can be customized to support different missions and operations scenarios. The MGDS is based on a distributed client/server architecture, with powerful Unix workstations, incorporating standards and open system architectures. The distributed architecture allows remote operations and user science data exchange, while also providing capabilities for centralized ground system monitor and control. The MGDS has proved its capabilities in supporting multiple large-class missions simultaneously, including the Voyager, Galileo, Magellan, Ulysses, and Mars Observer missions. The Operations Engineering Lab (OEL) at JPL has been leading Customer Adaptation Training (CAT) teams for adapting and customizing MGDS for the various operations and engineering teams. These CAT teams have typically consisted of only a few engineers who are familiar with operations and with the MGDS software and architecture. Our experience has provided a unique opportunity to work directly with the spacecraft and instrument operations teams and understand their requirements and how the MGDS can be adapted and customized to minimize their operations costs. As part of this work, we have developed workstation configurations, automation tools, and integrated user interfaces at minimal cost that have significantly improved productivity. We have also proved that these customized data systems are most successful if they are focused on the people and the tasks they perform and if they are based upon user confidence in the development team resulting from daily interactions. This paper will describe lessons learned in adapting JPL's MGDS to fly the Voyager, Galileo, and Mars Observer missions. We will explain how powerful, existing ground data systems can be adapted and packaged in a cost effective way for operations of small and large planetary missions. We will also describe how the MGDS was adapted to support operations within the Galileo Spacecraft Testbed. The Galileo testbed provided a unique opportunity to adapt MGDS to support command and control operations for a small autonomous operations team of a handful of engineers flying the Galileo Spacecraft flight system model.

Murphy, Susan C.↗

Implementing Production Grids

We have presented the essence of experience gained in building two production Grids, and provided some of the global context for this work. As the reader might imagine, there were a lot of false starts, refinements to the approaches and to the software, and several substantial integration projects (SRB and Condor integrated with Globus) to get where we are today. However, the point of this paper is to try and make it substantially easier for others to get to the point where Information Power Grids (IPG) and the DOE Science Grids are today. This is what is needed in order to move us toward the vision of a common cyber infrastructure for science. The author would also like to remind the readers that this paper primarily represents the actual experiences that resulted from specific architectural and software choices during the design and implementation of these two Grids. The choices made were dictated by the criteria laid out in section 1. There is a lot more Grid software available today that there was four years ago, and various of these packages are being integrated into IPG and the DOE Grids. However, the foundation choices of Globus, SRB, and Condor would not be significantly different today than they were four years ago. Nonetheless, if the GGF is successful in its work - and we have every reason to believe that it will be - then in a few years we will see that the 28 functions provided by these packages will be defined in terms of protocols and MIS, and there will be several robust implementations available for each of the basic components, especially the Grid Common Services. The impact of the emerging Web Grid Services work is not yet clear. It will likely have a substantial impact on building higher level services, however it is the opinion of the author that this will in no way obviate the need for the Grid Common Services. These are the foundation of Grids, and the focus of almost all of the operational and persistent infrastructure aspects of Grids.

Johnston, William E.↗

Case Study of the Space Shuttle Cockpit Avionics Upgrade Software

The purpose of the Space Shuttle Cockpit Avionics Upgrade project was to reduce crew workload and improve situational awareness. The upgrade was to augment the Shuttle avionics system with new hardware and software. An early version of this system was used to gather human factor statistics in the Space Shuttle Motion Simulator of the Johnson Space Center for one month by multiple teams of astronauts. The results were compiled by NASA Ames Research Center and it was was determined that the system provided a better than expected increase in situational awareness and reduction in crew workload. Even with all of the benefits nf the system, NASA cancelled the project towards the end of the development cycle. A major success of this project was the validation of the hardware architecture and software design. This was significant because the project incorporated new technology and approaches for the development of human rated space software. This paper serves as a case study to document knowledge gained and techniques that can be applied for future space avionics development efforts. The major technological advances were the use of reflective memory concepts for data acquisition and the incorporation of Commercial off the Shelf (COTS) products in a human rated space avionics system. The infused COTS products included a real time operating system, a resident linker and loader, a display generation tool set, and a network data manager. Some of the successful design concepts were the engineering of identical outputs in multiple avionics boxes using an event driven approach and inter-computer communication, a reconfigurable data acquisition engine, the use of a dynamic bus bandwidth allocation algorithm. Other significant experiences captured were the use of prototyping to reduce risk, and the correct balance between Object Oriented and Functional based programming.

Ferguson, Roscoe C.↗

Verification and Validation of Hybridspectral Radiometry Obtained from an Unmanned Surface Vessel (USV) in the Open and Coastal Oceans

The hardware and software capabilities of the compact-profiling hybrid instrumentation for radiometry and ecology (C-PHIRE) instruments on an unmanned surface vessel (USV) are evaluated. Both the radiometers and USV are commercial-off-the-shelf (COTS) products, with the latter being only minimally modified to deploy the C-PHIRE instruments. The hybridspectral C-PHIRE instruments consist of an array of 18 multispectral microradiometers with 10 nm wavebands spanning 320–875 nm plus a hyperspectral compact grating spectrometer (CGS) with 2048 pixels spanning 190–1000 nm. The C-PHIRE data were acquired and processed using two architecturally linked software packages, thereby allowing lessons learned in one to be applied to the other. Using standard data products and unbiased statistics, the C-PHIRE data were validated with those from the well-established compact-optical profiling system (C-OPS) and verified with the marine optical buoy (MOBY). Agreement between algorithm variables used to estimate colored dissolved organic matter (CDOM) absorption and chlorophyll a concentration were also validated. Developing and operating novel technologies, such as the C-PHIRE series of instruments, deployed on a USV increase the frequency and coverage of optical observations, which are required to fully support the present and next-generation validation exercises in radiometric remote sensing of aquatic ecosystems.

Hybridspectral↗

Architectural Implementation of NASA Space Telecommunications Radio System Specification

This software demonstrates a working implementation of the NASA STRS (Space Telecommunications Radio System) architecture specification. This is a developing specification of software architecture and required interfaces to provide commonality among future NASA and commercial software-defined radios for space, and allow for easier mixing of software and hardware from different vendors. It provides required functions, and supports interaction with STRS-compliant simple test plug-ins ("waveforms"). All of it is programmed in "plain C," except where necessary to interact with C++ plug-ins. It offers a small footprint, suitable for use in JPL radio hardware. Future NASA work is expected to develop into fully capable software-defined radios for use on the space station, other space vehicles, and interplanetary probes.

Peters, Kenneth J.↗

The Application of Coordination to Magnetic Measurement Automation: An SSW System Example

Magnetic measurements are an integral part of the development cycle of accelerator magnets, a part which provides necessary feedback to drive design and manufacturing improvements and corrections. Automation of these measurements allows for reduction of human errors and reproducibility of measurements. Realization of automation via coordination that is separated at the architectural level from the functional code provides flexibility in defining measurement procedures and substantial extensibility. The described Single Stretched Wire (SSW) system herein is an implementation of such a solution with the use of a component-based framework designed to build a family of measurement systems.

43 PARTICLE ACCELERATORS↗

Applying Service-Oriented Architecture to Archiving Data in Control and Monitoring Systems

Current trends in the architecture of software systems focus our attention on building systems using a set of loosely coupled components, each providing a specific functionality known as service. It is not much different in control and monitoring systems, where a functionally distinct sub-system can be identified and independently designed, implemented, deployed and maintained. One functionality that renders itself perfectly to becoming a service is archiving the history of the system state. The design of such a service and our experience of using it are the topic of this article. The service is built with responsibility segregation in mind, therefore, it provides for reducing data processing on the data viewer side and separation of data access and modification operations. The service architecture and the details concerning its data store design are discussed. An implementation of a service client capable of archiving EPICS process variables (PV) and LabVIEW shared variables is presented. Data access tools, including a browser-based data viewer and a mobile viewer, are also presented.

Nogiec, J. M.↗

FAIR AI models in high energy physics

Abstract The findable, accessible, interoperable, and reusable (FAIR) data principles provide a framework for examining, evaluating, and improving how data is shared to facilitate scientific discovery. Generalizing these principles to research software and other digital products is an active area of research. Machine learning models—algorithms that have been trained on data without being explicitly programmed—and more generally, artificial intelligence (AI) models, are an important target for this because of the ever-increasing pace with which AI is transforming scientific domains, such as experimental high energy physics (HEP). In this paper, we propose a practical definition of FAIR principles for AI models in HEP and describe a template for the application of these principles. We demonstrate the template’s use with an example AI model applied to HEP, in which a graph neural network is used to identify Higgs bosons decaying to two bottom quarks. We report on the robustness of this FAIR AI model, its portability across hardware architectures and software frameworks, and its interpretability.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Discovery and Synchronization Service Architectural Notes

This is a short architectural note for a critical component of safely scaling drone operations. The primary motivation for this note is to collect language and terminology around the Discovery and Synchronization Service (DSS) as it is currently implemented for Uncrewed Aircraft System (UAS) Traffic Management. The major driver for this document was frequent miscommunication about DSS. Often there have been multiple informed and invested stakeholders in the same room making statements about “multiple DSSs” and each of them meaning something slightly different.

uas traffic management↗

Exploring performance and energy tradeoffs for irregular applications: A case study on the Tilera many-core architecture

High performance, parallel applications with irregular data accesses are becoming a critical workload class for modern systems. In particular, the execution of such workloads on emerging many-core systems is expected to be a significant component of applications in data mining, machine learning, scientific computing and graph analytics. However, power and energy constraints limit the capabilities of individual cores, memory hierarchy and on-chip interconnect of such systems, thus leading to architectural and software trade-os that must be understood in the context of the intended application’s behavior. Irregular applications are notoriously hard to optimize given their data-dependent access patterns, lack of structured locality and complex data structures and code patterns. We have ported two irregular applications, graph community detection using the Louvain method (Grappolo) and high-performance conjugate gradient (HPCCG), to the Tilera many-core system and have conducted a detailed study of platform-independent and platform-specific optimizations that improve their performance as well as reduce their overall energy consumption. To conduct this study, we employ an auto-tuning based approach that explores the optimization design space along three dimensions - memory layout schemes, GCC compiler flag choices and OpenMP loop scheduling options. We leverage MIT’s OpenTuner auto-tuning framework to explore and recommend energy optimal choices for different combinations of parameters. We then conduct an in-depth architectural characterization to understand the memory behavior of the selected workloads. Finally, we perform a correlation study to demonstrate the interplay between the hardware behavior and application characteristics. Using auto-tuning, we demonstrate whole-node energy savings and performance improvements of up to 49:6% and 60% relative to a baseline instantiation, and up to 31% and 45:4% relative to manually optimized variants.

auto tuning↗

High speed packet switching

This document constitutes the final report prepared by Proteon, Inc. of Westborough, Massachusetts under contract NAS 5-30629 entitled High-Speed Packet Switching (SBIR 87-1, Phase 2) prepared for NASA-Greenbelt, Maryland. The primary goal of this research project is to use the results of the SBIR Phase 1 effort to develop a sound, expandable hardware and software router architecture capable of forwarding 25,000 packets per second through the router and passing 300 megabits per second on the router's internal busses. The work being delivered under this contract received its funding from three different sources: the SNIPE/RIG contract (Contract Number F30602-89-C-0014, CDRL Sequence Number A002), the SBIR contract, and Proteon. The SNIPE/RIG and SBIR contracts had many overlapping requirements, which allowed the research done under SNIPE/RIG to be applied to SBIR. Proteon funded all of the work to develop new router interfaces other than FDDI, in addition to funding the productization of the router itself. The router being delivered under SBIR will be a fully product-quality machine. The work done during this contract produced many significant findings and results, summarized here and explained in detail in later sections of this report. The SNIPE/RIG contract was completed. That contract had many overlapping requirements with the SBIR contract, and resulted in the successful demonstration and delivery of a high speed router. The development that took place during the SNIPE/RIG contract produced findings that included the choice of processor and an understanding of the issues surrounding inter processor communications in a multiprocessor environment. Many significant speed enhancements to the router software were made during that time. Under the SBIR contract (and with help from Proteon-funded work), it was found that a single processor router achieved a throughput significantly higher than originally anticipated. For this reason, a single processor router was developed and the final delivery under this contract will include a single processor CNX-500 router. The router and its interface boards (2 FDDIs and 2 dual-ethernets) are all product-quality components.

Source record↗