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At least 451 records · Page 25

The TENNLab Exploratory Neuromorphic Computing Framework

Spiking, neuromorphic computing systems are in a period of active exploration by the computing community. While they feature computational expressiveness beyond both von Neumann computing models and feed-forward neural networks, they are also challenging to design and program. The TENNLab exploratory neuromorphic computing framework is a software infrastructure, soon to be open-source, whose goal is to enable potential users of spiking, neuromorphic computing systems to develop applications and evaluate computing architectures, and for architecture researchers to develop and evaluate their architectures with a variety of applications. In this letter, we present the software architecture of the TENNLab framework.

97 MATHEMATICS AND COMPUTING↗

SmartFuse: Reconfigurable Smart Switches to Accelerate Fused Collectives in HPC Applications

Communication switches have sometimes been augmented to process collectives (e.g., the IBM BlueGene project and the Mellanox SHArP switch). In this work, we find that there is a great acceleration opportunity through the further augmentation of switches to accelerate more complex functions that combine communication with computation. We consider three types of such functions. The first is fully-fused collectives built by fusing multiple existing collectives like Allreduce with Alltoall. The second is semi-fused collectives built by combining a collective with another computation. The third we refer to as higher-order collectives built by combining multiple computations and communications, such as to perform matrix-matrix multiply (PGEMM). In this work, we propose a framework called SmartFuse to accelerate fused collective functions. The core of SmartFuse is a reconfigurable smart switch to support these operations. The semi/fully fused collectives are implemented with a CGRAlike architecture, while higher-order collectives are implemented with a more specialized computational unit that can also schedule communication. Supporting our framework is software to evaluate and translate relevant parts of the input program, compile them into a control data flow graph, and then map this graph to the switch hardware. The proposed framework, once deployed, has the strong potential to accelerate existing HPC applications transparently by encapsulation within an MPI implementation. Experimental results show that this approach improves the performance of the PGEMM kernel, MINIFE, and AMG by, on average, 94%, 15%, and 13%, respectively.

Haghi, Pouya↗

RELAP-7 Numerical Stabilization: Entropy Viscosity Method

The RELAP-7 code is the next generation nuclear reactor system safety analysis code being developed at the Idaho National Laboratory (INL). The code is based on the INL's modern scientific software development framework, MOOSE (Multi-Physics Object Oriented Simulation Environment). The overall design goal of RELAP-7 is to take advantage of the previous thirty years of advancements in computer architecture, software design, numerical integration methods, and physical models. The end result will be a reactor systems analysis capability that retains and improves upon RELAP5's capability and extends the analysis capability for all reactor system simulation scenarios. RELAP-7 utilizes a single phase and a novel seven-equation two-phase flow models as described in the RELAP-7 Theory Manual (INL/EXT-14-31366). The basic equation systems are hyperbolic, which generally require some type of stabilization (or artificial viscosity) to capture nonlinear discontinuities and to suppress advection-caused oscillations. This report documents one of the available options for this stabilization in RELAP-7 -- a new and novel approach known as the entropy viscosity method. Because the code is an ongoing development effort in which the physical sub models, numerics, and coding are evolving, so too must the specific details of the entropy viscosity stabilization method. Here the fundamentals of the method in their current state are presented.

42 ENGINEERING↗

RELAP-7 Closure Correlations

The RELAP-7 code is the next generation nuclear reactor system safety analysis code being developed at the Idaho National Laboratory (INL). The code is based on the INL’s modern scientific software development framework, MOOSE (Multi-Physics Object Oriented Simulation Environment). The overall design goal of RELAP-7 is to take advantage of the previous thirty years of advancements in computer architecture, software design, numerical integration methods, and physical models. The end result will be a reactor systems analysis capability that retains and improves upon RELAP5’s and TRACE’s capabilities and extends their analysis capabilities for all reactor system simulation scenarios. The RELAP-7 code utilizes the well-posed 7-equation two-phase flow model for compressible two-phase flow. Closure models used in the TRACE code has been reviewed and selected to reflect the progress made during the past decades and provide a basis for the colure correlations implemented in the RELAP-7 code. This document provides a summary on the closure correlations that are currently implemented in the RELAP-7 code. The closure correlations include sub-grid models that describe interactions between the fluids and the flow channel, and interactions between the two phases.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

RELAP-7 User's Guide

The RELAP-7 code is the next generation nuclear reactor system safety analysis code being developed at the Idaho National Laboratory (INL). The code is based on the INL’s modern scientific software development framework, MOOSE (Multi-Physics Object Oriented Simulation Environment). The overall design goal of RELAP-7 is to take advantage of the previous thirty years of advancements in computer architecture, software design, numerical integration methods, and physical models. The end result will be a reactor systems analysis capability that retains and improves upon RELAP5’s capability and extends the analysis capability for all reactor system simulation scenarios.This document is a user's guide on how to use the RELAP-7 code.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

RELAP-7 Software Verification and Validation Plan

This INL plan comprehensively describes the software for RELAP-7 and documents the software, interface, and software design requirements for the application. The plan also describes the testing-based software verification and validation (SV&V) process—a set of specially designed software models used to test RELAP-7. The RELAP-7 (Reactor Excursion and Leak Analysis Program) code is a nuclear reactor system safety analysis code being developed at Idaho National Laboratory (INL). The code is based on the INL’s modern scientific software development framework – MOOSE (Multi-Physics Object-Oriented Simulation Environment). The overall design goal of RELAP-7 is to take advantage of the previous thirty years of advancements in computer architecture, software design, numerical integration methods, and physical models. The end result will be a reactor systems analysis capability that retains and improves upon RELAP5’s capability and extends the analysis capability for all reactor system simulation scenarios.

97 MATHEMATICS AND COMPUTING↗

HEP Software Foundation Community White Paper Working Group - Data Processing Frameworks

Data processing frameworks are an essential part of HEP experiments' software stacks. Frameworks provide a means by which code developers can undertake the essential tasks of physics data processing, accessing relevant inputs and storing their outputs, in a coherent way without needing to know the details of other domains. Frameworks provide essential core services for developers and help deliver a configurable working application to the experiments' production systems. Modern HEP processing frameworks are in the process of adapting to a new computing landscape dominated by parallel processing and heterogeneity, which pose many questions regarding enhanced functionality and scaling that must be faced without compromising the maintainability of the code. In this paper we identify a program of work that can help further clarify the key concepts of frameworks for HEP and then spawn R&D activities that can focus the community's efforts in the most efficient manner to address the challenges of the upcoming experimental program.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Towards a systematic framework for the synthesis of operable process intensification systems

In this work we present an integrated framework to derive intensified designs with guaranteed safety and operability performance. A step-by-step procedure is described featuring: (i) superstructure-based process synthesis using Generalized Modular Representation Framework, (ii) development of advanced multi-parametric control strategies following the PAROC framework and software platform, and (iii) inherent safety analysis at early design stage utilizing quantitative risk assessment. Here, two case studies with increasing intensification complexity, namely heat exchanger network synthesis and reactive distillation column design, are investigated to demonstrate the capabilities of the proposed framework.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

EMMA: a new paradigm in configurable software

EMMA is a framework designed to create a family of configurable software systems, with emphasis on extensibility and flexibility. It is based on a loosely coupled, event driven architecture. The EMMA framework has been built upon the premise of composing software systems from independent components. It opens up opportunities for reuse of components and their functionality and composing them together in many different ways. As a result, it provides the developer of test and measurement applications with a lightweight alternative to microservices, while sharing their various advantages, including composability, loose coupling, encapsulation, and reuse.

97 MATHEMATICS AND COMPUTING↗

EMMA: A New Paradigm in Configurable Software

EMMA is a framework designed to create a family of configurable software systems, with emphasis on extensibility and flexibility. It is based on a loosely coupled, event driven architecture. The EMMA framework has been built upon the premise of composing software systems from independent components. It opens up opportunities for reuse of components and their functionality and composing them together in many different ways. It provides the developer of test and measurement applications with a lightweight alternative to microservices, while sharing their various advantages, including composability, loose coupling, encapsulation, and reuse.

Nogiec, J. M.↗

Optimal Efficiency and Operational Cost Savings: A Framework for Automated Rooftop PV Placement

Residential energy consumers are charged based on a utility rate structure, such as net metering or feed-in tariff. To lower consumers' electricity bills, expensive batteries are deployed to reduce the electricity fed from the grid during peak hours. However, strategic photovoltaic (PV) panel placement enables the reduction of operational energy cost while considering the spatial feasibility and efficiency for hosting rooftop PV. In this paper, we present a framework to automatically identify the optimal location of rooftop PV panels on residential buildings. Our framework integrates multiple workflows, including energy and environmental simulation, parametric modeling, and optimization to identify the ideal location of PV panels to balance the demand and supply at a building and community scale. These workflows are linked using the Grasshopper plug-in for Rhinoceros CAD software. The framework includes two different workflows, each satisfying a target for optimal PV placement: (a) maximizing PV panel efficiency, where users aim to maximize energy generation, and (b) minimizing operational energy cost, where "best'' panels are selected considering utility rates for operational energy cost. Our framework is demonstrated in a residential community in Fort Collins, Colorado, to generate the optimal PV placement for each of the two aforementioned targets. Results from the two workflows are compared to illustrate the effect of PV location and orientation on solar energy production efficiency and operational energy cost. The developed workflows are introduced as tools within the Grasshopper plug-in to investigate the solar potential of rooftop PV panels while taking into account factors such as contextual shading, utility rate structures, and buildings' energy demand profiles.

30 DIRECT ENERGY CONVERSION↗

Processors, Pipelines, and Protocols for Advanced Modeling Networks

Predictive capabilities arise from our understanding of natural processes and our ability to construct models that accurately reproduce these processes. Although our modeling state-of-the-art is primarily limited by existing computational capabilities, other technical areas will soon present obstacles to the development and deployment of future predictive capabilities. Advancement of our modeling capabilities will require not only faster processors, but new processing algorithms, high-speed data pipelines, and a common software engineering framework that allows networking of diverse models that represent the many components of Earth's climate and weather system. Development and integration of these new capabilities will pose serious challenges to the Information Systems (IS) technology community. Designers of future IS infrastructures must deal with issues that include performance, reliability, interoperability, portability of data and software, and ultimately, the full integration of various ES model systems into a unified ES modeling network.

Coughlan, Joseph↗

SoK: A Framework for and Analysis of Software Bill of Materials Tools

Modern software development has gradually become more complex, leveraging available open-source software and third party components. This practice has raised questions about the provenance, licensing, versioning and compliance of reused code and its dependencies. Furthermore, it is par ticularly important to review such code fragments and third party components for known-vulnerabilities before they are included in a software product. A Software Bill of Materials (SBoM) is a mechanism to achieve such an analysis, provid ing transparency and visibility into a software product to both the software developer and its respective consumer. An SBoM lists information and details about all the elements constituting a piece of software and can, therefore, be used to evaluate associated security risk. While the concept of SBoMs is growing in popularity, it is still fairly new to many organizations, causing them to potentially struggle with pro ducing and processing SBoMs and limiting their widespread adoption. In this work, we delve into the area of SBoMs and present the state-of-the-art SBoM tools, creating a framework for analysis and categorizing them based on a diverse set of features and functionalities. We are the first to provide a detailed analysis of 83 open-source SBoM tools along with a perspective on how a potential SBoM user can select a tool based on their specific requirements. Our work aims to help promote understanding of this domain, thereby encouraging and furthering its overall adoption. We additionally seek to pave a path for future work in this area by providing recommendations to tool developers and users, researchers, and standardizing organizations.

99 GENERAL AND MISCELLANEOUS↗

Uncertainty and Sensitivity Analysis Methods and Applications in the GDSA Framework (FY2025)

The Spent Fuel and Waste Science and Technology Campaign (SFWST) of the U.S. Department of Energy (DOE) Office of Nuclear Energy (NE) is conducting research and development on geologic disposal of spent nuclear fuel (SNF) and high-level nuclear waste (HLW). Two priorities for SFWST are design concept development and disposal system modeling. These priorities are directly addressed in the Geologic Disposal Safety Assessment (GDSA) control account, which is charged with developing a geologic repository system modeling and analysis capability, and the associated software, GDSA Framework, for evaluating disposal system performance for nuclear waste in geologic media. This report describes specific activities in the Fiscal Year (FY) 2025 associated with the GDSA Uncertainty and Sensitivity Analysis Methods work package. This report fulfills the GDSA Uncertainty and Sensitivity Analysis Methods work package (SF-25SN01030407) level 3 milestone, Uncertainty and Sensitivity Analysis Methods and Applications in GDSA Framework (FY2025) (M3SF-25SN010304072). This work was closely coordinated with the other Sandia National Laboratory GDSA work packages: the GDSA Framework Development work package (SF-25SN01030408), the GDSA Repository Systems Analysis work package (SF-25SN01030409), and the GDSA PFLOTRAN Development work package (SF-25SN01030410). This report builds on developments reported in previous GDSA Framework milestones, particularly M3SF-24SN010304072.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Uncertainty and Sensitivity Analysis Methods and Applications in the GDSA Framework (FY2024)

The Spent Fuel and Waste Science and Technology Campaign (SFWST) of the U.S. Department of Energy (DOE) Office of Nuclear Energy (NE) is conducting research and development on geologic disposal of spent nuclear fuel (SNF) and high-level nuclear waste (HLW). Two priorities for SFWST are design concept development and disposal system modeling. These priorities are directly addressed in the Geologic Disposal Safety Assessment (GDSA) control account, which is charged with developing a geologic repository system modeling and analysis capability, and the associated software, GDSA Framework, for evaluating disposal system performance for nuclear waste in geologic media.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Status Report on Uncertainty Quantification and Sensitivity Analysis Tools in the Geologic Disposal Safety Assessment (GDSA) Framework

The Spent Fuel and Waste Science and Technology (SFWST) Campaign of the U.S. Department of Energy (DOE) Office of Nuclear Energy (NE), Office of Fuel Cycle Technology (FCT) is conducting research and development (R&D) on geologic disposal of spent nuclear fuel (SNF) and high-level nuclear waste (HLW). Two high priorities for SFWST disposal R&D are design concept development and disposal system modeling. These priorities are directly addressed in the SFWST Geologic Disposal Safety Assessment (GDSA) control account, which is charged with developing a geologic repository system modeling and analysis capability, and the associated software, GDSA Framework, for evaluating disposal system performance for nuclear waste in geologic media. GDSA Framework is supported by SFWST Campaign and its predecessor the Used Fuel Disposition (UFD) campaign.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Advances in Uncertainty and Sensitivity Analysis Methods and Applications in GDSA Framework.

The Spent Fuel and Waste Science and Technology (SFWST) Campaign of the U.S. Department of Energy (DOE) Office of Nuclear Energy (NE), Office of Fuel Cycle Technology (FCT) is conducting research and development (R&D) on geologic disposal of spent nuclear fuel (SNF) and high-level nuclear waste (HLW). Two high priorities for SFWST disposal R&D are design concept development and disposal system modeling. These priorities are directly addressed in the SFWST ''Geologic Disposal Safety Assessment'' (GDSA) control account, which is charged with developing a geologic repository system modeling and analysis capability, and the associated software, ''GDSA Framework'', for evaluating disposal system performance for nuclear waste in geologic media. ''GDSA Framework'' is supported by SFWST Campaign and its predecessor the Used Fuel Disposition (UFD) campaign. This report fulfills the GDSA Uncertainty and Sensitivity Analysis Methods work package (SF-20SN01030403) level 3 milestone — ''Advances in Uncertainty and Sensitivity Analysis Methods and Applications in GDSA Framework'' (M3SF-20SN010304032). It presents high level objectives and strategy for development of uncertainty and sensitivity analysis tools, demonstrates uncertainty quantification (UQ) and sensitivity analysis (SA) tools in GDSA Framework in FY20, and describes additional UQ/SA tools whose future implementation would enhance the UQ/SA capability of ''GDSA Framework''. This work was closely coordinated with the other Sandia National Laboratory GDSA work packages: the GDSA Framework Development work package (SF- 2051\101030404), the GDSA Repository Systems Analysis work package (SF-2051\101030405), and the GDSA PFLOTRAN Development work package (SF-20SN01030406). This report builds on developments reported in previous ''GDSA Framework'' milestones, particularly M2SF- 19SNO1030403.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Uncertainty and Sensitivity Analysis Methods and Applications in the GDSA Framework (FY2021)

The Spent Fuel and Waste Science and Technology (SFWST) Campaign of the U.S. Department of Energy (DOE) Office of Nuclear Energy (NE), Office of Fuel Cycle Technology (FCT) is conducting research and development (R&D) on geologic disposal of spent nuclear fuel (SNF) and high-level nuclear waste (HLW). Two high priorities for SFWST disposal R&D are design concept development and disposal system modeling. These priorities are directly addressed in the SFWST Geologic Disposal Safety Assessment (GDSA) control account, which is charged with developing a geologic repository system modeling and analysis capability, and the associated software, GDSA Framework, for evaluating disposal system performance for nuclear waste in geologic media. GDSA Framework is supported by SFWST Campaign and its predecessor the Used Fuel Disposition (UFD) campaign. This report fulfills the GDSA Uncertainty and Sensitivity Analysis Methods work package (SF-21SN01030404) level 3 milestone, Uncertainty and Sensitivity Analysis Methods and Applications in GDSA Framework (FY2021) (M3SF-21SN010304042). It presents high level objectives and strategy for development of uncertainty and sensitivity analysis tools, demonstrates uncertainty quantification (UQ) and sensitivity analysis (SA) tools in GDSA Framework in FY21, and describes additional UQ/SA tools whose future implementation would enhance the UQ/SA capability of GDSA Framework. This work was closely coordinated with the other Sandia National Laboratory GDSA work packages: the GDSA Framework Development work package (SF-21SN01030405), the GDSA Repository Systems Analysis work package (SF-21SN01030406), and the GDSA PFLOTRAN Development work package (SF-21SN01030407). This report builds on developments reported in previous GDSA Framework milestones, particularly M3SF 20SN010304032.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗