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Openet: Applications of Satellite-Based Evapotranspiration Data for Water Resources Management in the Western United States

Advancing water security in overallocated river basins globally requires consistent and reproducible information on consumptive use of water that can anchor the development of data-driven solutions to the challenge of balancing water supply and demand. OpenET is a fully automated system for field-scale (30 m), satellite-based mapping of evapotranspiration (ET) at daily, monthly and annual timesteps. OpenET currently provides spatially contiguous data throughout the 23 westernmost states in the continental US, and includes both current information as well as multi-year timeseries of ET. The OpenET consortium has implemented an ensemble of satellite-based ET models (ALEXI/DisALEXI, eeMETRIC, PT-JPL, geeSEBAL, SIMS and SSEBop) on Google Earth Engine, which provides a shared computing platform for collaboration on processing of data from Landsat and other satellites, land cover and meteorological inputs, leading to increased consistency and accuracy across the ensemble of models. Earth Engine also facilitates hosting and distribution of data via open data collections and an application programming interface. We provide updates on the OpenET framework, open data services and data access tools, approach to geographic expansion, recent accuracy assessments, and describe how a user-driven design approach has facilitated successful applications of OpenET data for a wide range of water resource management activities. Applications to date include: use of ET data to improve quantification of ET and consumptive use in Oregon, Utah and the Upper Colorado River Basin; streamlining of water use reporting requirements in the California Delta; support for calculation of water budgets for the implementation of the Sustainable Groundwater Management Act in California; and integration into decision support tools for irrigation management. The use cases demonstrate how satellite-derived ET data that are easily accessed and seen as broadly accepted can accelerate adoption of innovative water management practices at scale, and support advances in the sustainability of water supplies. Uptake and use of data by the OpenET science community has also led to advances in our understanding of the impacts of landcover change, irrigation intensification and wildfire events on hydrology and the water security.

Applications↗

DOE OSTI2021

The PetscSF Scalable Communication Layer

PetscSF, the communication component of the Portable, Extensible Toolkit for Scientific Computation (PETSc), is designed to provide PETSc's communication infrastructure suitable for exascale computers that utilize GPUs and other accelerators. PetscSF provides a simple application programming interface (API) for managing common communication patterns in scientific computations by using a star-forest graph representation. PetscSF supports several implementations based on MPI and NVSHMEM, whose selection is based on the characteristics of the application or the target architecture. An efficient and portable model for network and intra-node communication is essential for implementing large-scale applications. The Message Passing Interface, which has been the de facto standard for distributed memory systems, has developed into a large complex API that does not yet provide high performance on the emerging heterogeneous CPU-GPU-based exascale systems. Here, we discuss the design of PetscSF, how it can overcome some difficulties of working directly with MPI on GPUs, and we demonstrate its performance, scalability, and novel features.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

A high-fidelity building performance simulation test bed for the development and evaluation of advanced controls

We present an open-source building performance simulation test bed, the Advanced Controls Test Bed (ACTB), that interfaces high-fidelity Spawn of EnergyPlus building models, with advanced controllers implemented in Python. Additionally, the ACTB leverages the Building Optimization Testing and Alfalfa platforms for managing simulations, providing an external clock, a representational state transfer (REST) application programming interface (API), and key performance indicators for evaluating the effectiveness of control strategies. The REST API allows the development of external controllers programmed in languages such as Python, which provides flexibility and a rich choice of scientific libraries for designing control sequences. We present three test cases based on the U.S. Department of Energy's Reference Small Office Building to demonstrate the ACTB's capabilities: (a) rule-based controls compliant with ASHRAE Guideline 36 control sequences; (b) an economic model predictive control implemented using do-mpc; and (c) a deep Q-network reinforcement learning agent implemented using OpenAI Gym.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS2020

Machine Learning-Based Predictive Analytics for Aircraft Engine Conceptual Design

Big data and artificial intelligence/machine learning are transforming the global business environment. Data is now the most valuable asset for enterprises in every industry. Companies are using data-driven insights for competitive advantage. With that, the adoption of machine learning-based data analytics is rapidly taking hold across various industries, producing autonomous systems that support human decision-making. This work explored the application of machine learning to aircraft engine conceptual design. Supervised machine-learning algorithms for regression and classification were employed to study patterns in an existing, open-source database of production and research turbofan engines, and resulting in predictive analytics for use in predicting performance of new turbofan designs. Specifically, the author developed machine learning-based analytics to predict cruise thrust specific fuel consumption (TSFC) and core sizes of high-efficiency turbofan engines, using engine design parameters as the input. The predictive analytics were trained and deployed in Keras, an open-source neural networks application program interface (API) written in Python, with Google’s TensorFlow (an open source library for numerical computation) serving as the backend engine. The promising results of the predictive analytics show that machine-learning techniques merit further exploration for application in aircraft engine conceptual design.

deep-learning↗

DOE OSTI2015

2015 ESGF Progress Report

The Earth System Grid Federation (ESGF) is a multi-agency, international collaboration whose purpose is to develop the software infrastructure needed to facilitate and empower the study of climate change on a global scale. ESGF’s architecture employs a system of geographically distributed peer nodes that are independently administered yet united by common federation protocols and application programming interfaces. The cornerstones of its interoperability are the peer-to-peer messaging, which is continuously exchanged among all nodes in the federation; a shared architecture for search and discovery; and a security infrastructure based on industry standards. ESGF integrates popular application engines available from the open-source community with custom components (for data publishing, searching, user interface, security, and messaging) that were developed collaboratively by the team. The full ESGF infrastructure has now been adopted by multiple Earth science projects and allows access to petabytes of geophysical data, including the Coupled Model Intercomparison Project (CMIP)—output used by the Intergovernmental Panel on Climate Change assessment reports. ESGF is a successful example of integration of disparate open-source technologies into a cohesive functional system that serves the needs of the global climate science community.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Domain-Specific Type-Safe APIs for Hierarchical Scientific Data with Modern C++

General-purpose library application programming interfaces (APIs) for self-describing hierarchical scientific data storage, such as the HDF5 and NetCDF libraries, are traditionally of runtime nature. Runtime errors for entry existence and data types are typically caught later in the development process of higher-level application-specific APIs. In this paper, we propose exploiting modern C++ metaprogramming features to add compile-time type-safety to improve the interaction with a well-defined metadata-rich scientific schema in domain-specific hierarchical datasets. We tackle two aspects of common use: (i) direct data access, (ii) flexible “in-memory” index models for efficient search and data processing. The proposed APIs use C++17’s template type auto deduction features, C++11’s enum class for type-safety and C-style preprocessor macros for generative templated code. We showcase the pros and cons of our initial work on the standard NeXus schema used for annotating and storing experimental neutron scattering data at several facilities around the world on top of HDF5. Extendable compile-time type-safe APIs are a desirable feature that could be indexed by any modern integrated development environment (IDE). Hence, such APIs can help ease the learning curve for domain scientists using a less error-prone software interaction to enhance the findability of their data without resorting to a domain-specific language (DSL).

Godoy, William↗

DOE OSTI2018

Epi Archive: Automated Synthesis of Global Notifiable Disease Data

ObjectiveLANL has built software that automatically collects global notifiable disease data, synthesizes the data, and makes it available to humans and computers within the Biosurveillance Ecosystem (BSVE) as a novel data stream. These data have many applications including improving the prediction and early warning of disease events.IntroductionMost countries do not report national notifiable disease data in a machine-readable format. Data are often in the form of a file that contains text, tables and graphs summarizing weekly or monthly disease counts. This presents a problem when information is needed for more data intensive approaches to epidemiology, biosurveillance and public health.While most nations likely store incident data in a machine-readable format, governments are often hesitant to share data openly for a variety of reasons that include technical, political, economic, and motivational issues1.A survey conducted by LANL of notifiable disease data reporting in over fifty countries identified only a few websites that report data in a machine-readable format. The majority (>70%) produce reports as PDF files on a regular basis. The bulk of the PDF reports present data in a structured tabular format, while some report in natural language.The structure and format of PDF reports change often; this adds to the complexity of identifying and parsing the desired data. Not all websites publish in English, and it is common to find typos and clerical errors.LANL has developed a tool, Epi Archive, to collect global notifiable disease data automatically and continuously and make it uniform and readily accessible.MethodsWe conducted a survey of the national notifiable disease reporting systems notating how the data are reported and in what formats. We determined the minimal metadata that is required to contextualize incident counts properly, as well as optional metadata that is commonly found.The development of software to regularly ingest notifiable disease data and make it available involves three or four main steps: scraping, detecting, parsing and persisting.Scraping: we examine website design and determine reporting mechanisms for each country/website, as well as what varies across the reporting mechanisms. We then designed and wrote code to automate the downloading of the data for each country. We store all artifacts presented as files (PDF, XLSX, etc.) in their original form, along with appropriate metadata for parsing and data provenance.Detecting: This step is required when parsing structured non-machine-readable data such as tabular data in PDF files. We combined the Nurminen methodology of PDF table detection with in-house heuristics to find the desired data within PDF reports2.Parsing: We determined what to extract from each dataset and parsed these data into uniform data structures, correctly accommodating the variations in metadata (e.g., time interval definitions) and the various human languages.Persisting: We store the data in the Epi Archive database and make it available on the internet and through the BSVE. The data is persisted into a structured and normalized SQL database.ResultsThe Epi Archive tool currently contains national and/or subnational notifiable disease data from twenty nations. When a user accesses the Epi Archive site, they are prompted with four fields: country, subregion, disease of interest, and date duration. Upon form submission, a time series is generated from the users’ specifications. The generated graph can then be downloaded into a CSV file if a user is interested in performing personal analysis. Additionally, the data from Epi Archive can be reached through a REST API (Representational State Transfer Application Programming Interface).ConclusionsLANL, as part of a currently funded DTRA effort, is automatically and continually collecting global notifiable disease data. While 20 nations are in production, more are being brought online in the near future. These data are already being utilized and will have many applications including improving the prediction and early warning of disease events.References[1] van Panhuis WG, Paul P, Emerson C, et al. A systematic review of barriers to data sharing in public health. BMC Public Health. 2014. 14:1144. doi:10.1186/1471-2458-14-1144[2] Nurminen, Anssi. "Algorithmic extraction of data in tables in PDF documents." (2013).

Khalsa, Hari S.↗

NASA NTRS1997

Steady-State Cycle Deck Launcher Developed for Numerical Propulsion System Simulation

One of the objectives of NASA's High Performance Computing and Communications Program's (HPCCP) Numerical Propulsion System Simulation (NPSS) is to reduce the time and cost of generating aerothermal numerical representations of engines, called customer decks. These customer decks, which are delivered to airframe companies by various U.S. engine companies, numerically characterize an engine's performance as defined by the particular U.S. airframe manufacturer. Until recently, all numerical models were provided with a Fortran-compatible interface in compliance with the Society of Automotive Engineers (SAE) document AS681F, and data communication was performed via a standard, labeled common structure in compliance with AS681F. Recently, the SAE committee began to develop a new standard: AS681G. AS681G addresses multiple language requirements for customer decks along with alternative data communication techniques. Along with the SAE committee, the NPSS Steady-State Cycle Deck project team developed a standard Application Program Interface (API) supported by a graphical user interface. This work will result in Aerospace Recommended Practice 4868 (ARP4868). The Steady-State Cycle Deck work was validated against the Energy Efficient Engine customer deck, which is publicly available. The Energy Efficient Engine wrapper was used not only to validate ARP4868 but also to demonstrate how to wrap an existing customer deck. The graphical user interface for the Steady-State Cycle Deck facilitates the use of the new standard and makes it easier to design and analyze a customer deck. This software was developed following I. Jacobson's Object-Oriented Design methodology and is implemented in C++. The AS681G standard will establish a common generic interface for U.S. engine companies and airframe manufacturers. This will lead to more accurate cycle models, quicker model generation, and faster validation leading to specifications. The standard will facilitate cooperative work between industry and NASA. The NPSS Steady-State Cycle Deck team released a batch version of the Steady-State Cycle Deck in March 1996. Version 1.1 was released in June 1996. During fiscal 1997, NPSS accepted enhancements and modifications to the Steady-State Cycle Deck launcher. Consistent with NPSS' commercialization plan, these modifications will be done by a third party that can provide long-term software support.

VanDrei, Donald E.↗

DOE OSTI2016

Institute for Sustained Performance, Energy, and Resilience (SuPER)

The University of Tennessee (UTK) and University of Texas at El Paso (UTEP) partnership supported the three main thrusts of the SUPER project---performance, energy, and resilience. The UTK-UTEP effort thus helped advance the main goal of SUPER, which was to ensure that DOE's computational scientists can successfully exploit the emerging generation of high performance computing (HPC) systems. This goal is being met by providing application scientists with strategies and tools to productively maximize performance, conserve energy, and attain resilience. The primary vehicle through which UTK provided performance measurement support to SUPER and the larger HPC community is the Performance Application Programming Interface (PAPI). PAPI is an ongoing project that provides a consistent interface and methodology for collecting hardware performance information from various hardware and software components, including most major CPUs, GPUs and accelerators, interconnects, I/O systems, and power interfaces, as well as virtual cloud environments. The PAPI software is widely used for performance modeling of scientific and engineering applications---for example, the HOMME (High Order Methods Modeling Environment) climate code, and the GAMESS and NWChem computational chemistry codes---on DOE supercomputers. PAPI is widely deployed as middleware for use by higher-level profiling, tracing, and sampling tools (e.g., CrayPat, HPCToolkit, Scalasca, Score-P, TAU, Vampir, PerfExpert), making it the de facto standard for hardware counter analysis. PAPI has established itself as fundamental software infrastructure in every application domain (spanning academia, government, and industry), where improving performance can be mission critical. Ultimately, as more application scientists migrate their applications to HPC platforms, they will benefit from the extended capabilities this grant brought to PAPI to analyze and optimize performance in these environments, whether they use PAPI directly, or via third-party performance tools. Capabilities added to PAPI through this grant include support for new architectures such as the lastest GPU and Xeon Phi accelerators, and advanced power measurement and management features. Another important topic for the UTK team was providing support for a rich ecosystem of different fault management strategies in the context of parallel computing. Our long term efforts have been oriented toward proposing flexible strategies and providing building boxes that application developers can use to build the most efficient fault management technique for their application. These efforts span across the entire software spectrum, from theoretical models of existing strategies to easily assess their performance, to algorithmic modifications to take advantage of specific mathematical properties for data redundancy and to extensions to widely used programming paradigms to empower the application developers to deal with all types of faults. We have also continued our tight collaborations with users to help them adopt these technologies to ensure their application always deliver meaningful scientific data. Large supercomputer systems are becoming more and more power and energy constrained, and future systems and applications running on them will need to be optimized to run under power caps and/or minimize energy consumption. The UTEP team contributed to the SUPER energy thrust by developing power modeling methodologies and investigating power management strategies. Scalability modeling results showed that some applications can scale better with respect to an increasing power budget than with respect to only the number of processors. Power management, in particular shifting power to processors on the critical path of an application execution, can reduce perturbation due to system noise and other sources of runtime variability, which are growing problems on large-scale power-constrained computer systems.

42 ENGINEERING↗

NASA NTRS2017

Ground System Architectures Workshop GMSEC SERVICES SUITE (GSS): an Agile Development Story

The GMSEC (Goddard Mission Services Evolution Center) Services Suite (GSS) is a collection of tools and software services along with a robust customizable web-based portal that enables the user to capture, monitor, report, and analyze system-wide GMSEC data. Given our plug-and-play architecture and the needs for rapid system development, we opted to follow the Scrum Agile Methodology for software development. Being one of the first few projects to implement the Agile methodology at NASA GSFC, in this presentation we will present our approaches, tools, successes, and challenges in implementing this methodology. The GMSEC architecture provides a scalable, extensible ground and flight system for existing and future missions. GMSEC comes with a robust Application Programming Interface (GMSEC API) and a core set of Java-based GMSEC components that facilitate the development of a GMSEC-based ground system. Over the past few years, we have seen an upbeat in the number of customers who are moving from a native desktop application environment to a web based environment particularly for data monitoring and analysis. We also see a need to provide separation of the business logic from the GUI display for our Java-based components and also to consolidate all the GUI displays into one interface. This combination of separation and consolidation brings immediate value to a GMSEC-based ground system through increased ease of data access via a uniform interface, built-in security measures, centralized configuration management, and ease of feature extensibility.

Software Development/Agile↗

DOE OSTI2021

Saline: An API for Thermophysical Properties

An initial interface for thermophysical data was generalized for broader incorporation into modeling and simulation codes used for molten salt reactor analysis. A quality assurance review of the thermophysical properties data was conducted; errors were fixed, and improvements were made with consistency and accuracy to references. The Saline code application programming interface was created to facilitate access and integration of thermophysical properties. This report describes the thermophysical data, the quality assurance improvements, and the Saline interface.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2025

Connecting Minds: AI Use Cases to Bridge Power Systems and Large Language Models for Practical Applications

Recent advances in artificial intelligence (AI) and development of large language models (LLMs) present the opportunity to develop a new generation of power systems applications. In contrast with early power system AI applications based on structured numerical data, LLMs offer unique capabilities to perform logical reasoning using text documents, unstructured data, and application programming interface (API) calls to computational software. This paper seeks to bridge the knowledge gap between power systems engineers and LLM developers through a crosscutting explanation of use cases, characteristics, requirements, practical considerations from the perspectives of both LLM capabilities and industry needs. Specific focus is given to applications that can be realistically deployed by electric utilities. After introducing the architecture of LLMs and unique challenges of the power systems domain, this paper proposes twenty representative LLM applications grouped into categories of 1) power system operations, 2) asset management, 3) system planning and analytics, and 4) energy management and protection systems. Five use cases are presented within each category with descriptions of the motivation, objectives, approaches, example inputs / outputs, and benefits of each use case.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2018

Correlated Production and Analog Transport of Fission Neutrons and Photons Using Fission Models FREYA, FIFRELIN, and the Monte Carlo Code TRIPOLI-4

Fission modeling in general-purpose Monte Carlo transport codes often relies on average nuclear data provided by the international evaluation libraries. As such, only average fission multiplicities are available and correlations between fission neutrons and photons are missing. Whereas uncorrelated fission physics is usually sufficient for standard reactor core and radiation shielding calculations, correlated fission secondaries are required for specialized nuclear instrumentation and detector modeling. For coincidence counting detector optimization for instance, the precise simulation of fission neutrons and photons that remain correlated in time from birth to detection is essential. New developments were recently integrated into the Monte Carlo transport code TRIPOLI-4 to model fission physics more precisely, the purpose being to access event-by-event fission events from two different fission models: Fission Reaction Event Yield Algorithm (FREYA) and Fission Fragment Evaporation Leading to an Investigation of Nuclear Data (FIFRELIN). TRIPOLI-4 simulations can now be performed, either by connecting via an application programming interface to the Lawrence Livermore National Laboratory fission library including FREYA, or by reading the external fission event data files produced by FIFRELIN beforehand. These new capabilities enable us to easily compare results from the Monte Carlo transport calculations using the two fission models in a nuclear instrumentation application. In the first part of this paper, the broad underlying principles of the two fission models are recalled. We then present the experimental measurements of neutron angular correlations for 252 Cf(sf) and 240 Pu(sf). The correlations were measured for several neutron kinetic energy thresholds. In the latter part of this paper, simulation results are compared with the experimental data. Spontaneous fissions in 252 Cf and 240 Pu are modeled by FREYA or FIFRELIN. Emitted neutrons and photons are subsequently transported to an array of scintillators by TRIPOLI-4 in the analog mode to preserve their correlations. Angular correlations between fission neutrons obtained independently from these TRIPOLI-4 simulations, using either FREYA or FIFRELIN, are compared with the experimental results. In conclusion, for 240 Pu(sf), the measured correlations were used to tune one of the FREYA model parameters. Similarly, different sets of parameters have been tested in FIFRELIN to try to improve the agreement with the experimental data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2016

SU-F-T-262: Commissioning Varian Portal Dosimetry for EPID-Based Patient Specific QA in a Non-Aria Environment

Purpose: Development of an in-house program facilitates a workflow that allows Electronic Portal Imaging Device (EPID) patient specific quality assurance (QA) measurements to be acquired and analyzed in the Portal Dosimetry Application (Varian Medical Systems, Palo Alto, CA) using a non-Aria Record and Verify (R&V) system (MOSAIQ, Elekta, Crawley, UK) to deliver beams in standard clinical treatment mode. Methods: Initial calibration of an in-house software tool includes characterization of EPID dosimetry parameters by importing DICOM images of varying delivered MUs to determine linear mapping factors in order to convert image pixel values to Varian-defined Calibrated Units (CU). Using this information, the Portal Dose Image Prediction (PDIP) algorithm was commissioned by converting images of various field sizes to output factors using the Eclipse Scripting Application Programming Interface (ESAPI) and converting a delivered configuration fluence to absolute dose units. To verify the algorithm configuration, an integrated image was acquired, exported directly from the R&V client, automatically converted to a compatible, calibrated dosimetric image, and compared to a PDIP calculated image using Varian’s Portal Dosimetry Application. Results: For two C-Series and one TrueBeam Varian linear accelerators, gamma comparisons (global 3% / 3mm) of PDIP algorithm predicted dosimetric images and images converted via the inhouse system demonstrated agreement for ≥99% of all pixels, exceeding vendor-recommended commissioning guidelines. Conclusion: Combinations of a programmatic image conversion tool and ESAPI allow for an efficient and accurate method of patient IMRT QA incorporating a 3rd party R&V system.

60 APPLIED LIFE SCIENCES↗

NASA NTRS2003

SpaceWire Driver Software for Special DSPs

A computer program provides a high-level C-language interface to electronics circuitry that controls a SpaceWire interface in a system based on a space qualified version of the ADSP-21020 digital signal processor (DSP). SpaceWire is a spacecraft-oriented standard for packet-switching data-communication networks that comprise nodes connected through bidirectional digital serial links that utilize low-voltage differential signaling (LVDS). The software is tailored to the SMCS-332 application-specific integrated circuit (ASIC) (also available as the TSS901E), which provides three highspeed (150 Mbps) serial point-to-point links compliant with the proposed Institute of Electrical and Electronics Engineers (IEEE) Standard 1355.2 and equivalent European Space Agency (ESA) Standard ECSS-E-50-12. In the specific application of this software, the SpaceWire ASIC was combined with the DSP processor, memory, and control logic in a Multi-Chip Module DSP (MCM-DSP). The software is a collection of low-level driver routines that provide a simple message-passing application programming interface (API) for software running on the DSP. Routines are provided for interrupt-driven access to the two styles of interface provided by the SMCS: (1) the "word at a time" conventional host interface (HOCI); and (2) a higher performance "dual port memory" style interface (COMI).

Clark, Douglas↗

DOE OSTI2014

Multi-Tenant Isolation via Reconfigurable Networks

High performance computing environments are often used for a wide variety of workloads ranging from simulation, data transformation and analysis, and complex workflows to name just a few. These systems may process data at various security levels but in so doing are often enclaved at the highest security posture. This approach places significant restrictions on the users of the system even when processing data at a lower security level and exposes data at higher levels of confidentiality to a much broader population than otherwise necessary. The traditional approach of isolation, while effective in establishing security enclaves poses significant challenges for the use of shared infrastructure in HPC environments. This report details current state-of-the-art in reconfigurable network enclaving through Software Defined Networking (SDN) and Network Function Virtualization (NFV) and their applicability to secure enclaves in HPC environments. SDN and NFV methods are based on a solid foundation of system wide virtualization. The purpose of which is very straight forward, the system administrator can deploy networks that are more amenable to customer needs, and at the same time achieve increased scalability making it easier to increase overall capacity as needed without negatively affecting functionality. The network administration of both the server system and the virtual sub-systems is simplified allowing control of the infrastructure through well-defined APIs (Application Programming Interface). While SDN and NFV technologies offer significant promise in meeting these goals, they also provide the ability to address a significant component of the multi-tenant challenge in HPC environments, namely resource isolation. Traditional HPC systems are built upon scalable high-performance networking technologies designed to meet specific application requirements. Dynamic isolation of resources within these environments has remained difficult to achieve. SDN and NFV methodology provide us with relevant concepts and available open standards based APIs that isolate compute and storage resources within an otherwise common networking infrastructure. Additionally, the integration of the networking APIs within larger system frameworks such as OpenStack provide the tools necessary to establish isolated enclaves dynamically allowing the benefits of HPC while providing a controlled security structure surrounding these systems.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1992

A new programming metaphor for image processing procedures

Most image processing systems, besides an Application Program Interface (API) which lets users write their own image processing programs, also feature a higher level of programmability. Traditionally, this is a command or macro language, which can be used to build large procedures (scripts) out of simple programs or commands. This approach, a legacy of the teletypewriter has serious drawbacks. A command language is clumsy when (and if! it attempts to utilize the capabilities of a multitasking or multiprocessor environment, it is but adequate for real-time data acquisition and processing, it has a fairly steep learning curve, and the user interface is very inefficient,. especially when compared to a graphical user interface (GUI) that systems running under Xll or Windows should otherwise be able to provide. ll these difficulties stem from one basic problem: a command language is not a natural metaphor for an image processing procedure. A more natural metaphor - an image processing factory is described in detail. A factory is a set of programs (applications) that execute separate operations on images, connected by pipes that carry data (images and parameters) between them. The programs function concurrently, processing images as they arrive along pipes, and querying the user for whatever other input they need. From the user's point of view, programming (constructing) factories is a lot like playing with LEGO blocks - much more intuitive than writing scripts. Focus is on some of the difficulties of implementing factory support, most notably the design of an appropriate API. It also shows that factories retain all the functionality of a command language (including loops and conditional branches), while suffering from none of the drawbacks outlined above. Other benefits of factory programming include self-tuning factories and the process of encapsulation, which lets a factory take the shape of a standard application both from the system and the user's point of view, and thus be used as a component of other factories. A bare-bones prototype of factory programming was implemented under the PcIPS image processing system, and a complete version (on a multitasking platform) is under development.

Smirnov, O. M.↗

NASA NTRS2006

CAPRI: A Geometric Foundation for Computational Analysis and Design

CAPRI is a software building tool-kit that refers to two ideas; (1) A simplified, object-oriented, hierarchical view of a solid part integrating both geometry and topology definitions, and (2) programming access to this part or assembly and any attached data. A complete definition of the geometry and application programming interface can be found in the document CAPRI: Computational Analysis PRogramming Interface appended to this report. In summary the interface is subdivided into the following functional components: 1. Utility routines -- These routines include the initialization of CAPRI, loading CAD parts and querying the operational status as well as closing the system down. 2. Geometry data-base queries -- This group of functions allow all top level applications to figure out and get detailed information on any geometric component in the Volume definition. 3. Point queries -- These calls allow grid generators, or solvers doing node adaptation, to snap points directly onto geometric entities. 4. Calculated or geometrically derived queries -- These entry points calculate data from the geometry to aid in grid generation. 5. Boundary data routines -- This part of CAPRI allows general data to be attached to Boundaries so that the boundary conditions can be specified and stored within CAPRI s data-base. 6. Tag based routines -- This part of the API allows the specification of properties associated with either the Volume (material properties) or Boundary (surface properties) entities. 7. Geometry based interpolation routines -- This part of the API facilitates Multi-disciplinary coupling and allows zooming through Boundary Attachments. 8. Geometric creation and manipulation -- These calls facilitate constructing simple solid entities and perform the Boolean solid operations. Geometry constructed in this manner has the advantage that if the data is kept consistent with the CAD package, therefore a new design can be incorporated directly and is manufacturable. 9. Master Model access This addition to the API allows for the querying of the parameters and dimensions of the model. The feature tree is also exposed so it is easy to see where the parameters are applied. Calls exist to allow for the modification of the parameters and the suppression/unsuppression of nodes in the tree. Part regeneration is performed by a single API call and a new part becomes available within CAPRI (if the regeneration was successful). This is described in a separate document. Components 1-7 are considered the CAPRI base level reader.

Haimes, Robert↗