Shields - Code Coupling
This PowerPoint presentation focuses on the history and benefits of the Space Weather Modeling Framework (SWMF) code and collaborative software development.
79 ASTRONOMY AND ASTROPHYSICS↗
SEARCH · Engineering Papers
Results for “Computer Programming and software”
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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Power/energy use cases for high performance computing
Power and Energy have been identified as a first order challenge for future extreme scale high performance computing (HPC) systems. In practice the breakthroughs will need to be provided by the hardware vendors. But to make the best use of the solutions in an HPC environment, it will likely require periodic tuning by facility operators and software components. This document describes the actions and interactions needed to maximize power resources. It strives to cover the entire operational space in which an HPC system occupies. The descriptions are presented as formal use cases, as documented in the Unified Modeling Language Specification [1]. The document is intended to provide a common understanding to the HPC community of the necessary management and control capabilities. Assuming a common understanding can be achieved, the next step will be to develop a set of Application Programing Interfaces (APIs) to which hardware vendors and software developers could utilize to steer power consumption.
97 MATHEMATICS AND COMPUTING↗
VTK-m User's Guide (V.1.6)
High-performance computing relies on ever finer threading. Advances in processor technology include ever greater numbers of cores, hyperthreading, accelerators with integrated blocks of cores, and special vectorized instructions, all of which require more software parallelism to achieve peak performance. Traditional visualization solutions cannot support this extreme level of concurrency. Extreme scale systems require a new programming model and a fundamental change in how we design algorithms. To address these issues we created VTK-m: the visualization toolkit for multi-/many-core architectures.
97 MATHEMATICS AND COMPUTING↗
Providing performance portable numerics for Intel GPUs
Summary With discrete Intel GPUs entering the high‐performance computing landscape, there is an urgent need for production‐ready software stacks for these platforms. In this article, we report how we enable the Ginkgo math library to execute on Intel GPUs by developing a kernel backed based on the DPC++ programming environment. We discuss conceptual differences between the CUDA and DPC++ programming models and describe workflows for simplified code conversion. We evaluate the performance of basic and advanced sparse linear algebra routines available in Ginkgo's DPC++ backend in the hardware‐specific performance bounds and compare against routines providing the same functionality that ship with Intel's oneMKL vendor library.
97 MATHEMATICS AND COMPUTING↗
High Performance Computing Operations Review Report
The High Performance Computing Operations Review (HPCOR) meeting—requested by the ASC and ASCR program headquarters at DOE—was held November 5 and 6, 2013, at the Marriott Hotel in San Francisco, CA. The purpose of the review was to discuss the processes and practices for HPC integration and its related software and facilities. Experiences and lessons learned from the most recent systems deployed were covered in order to benefit the deployment of new systems.
97 MATHEMATICS AND COMPUTING↗
Fiscal Year 2023 Software Quality Assurance Activities for the ARC Software
The Argonne Reactor Code (ARC) software suite [1-17] has been developed by Argonne researchers for fast reactor design and analysis since the 1970s. With the ARC software suite, a user can quickly build a model of a proposed or existing fast spectrum reactor and carry out fuel cycle, nominal thermal analysis and flow requirements, and assess, as is appropriate, whether the core design and constraint system yield an acceptable mechanical behavior. For transient reactor analysis with SAS4A [18], the ARC software suite can be used to generate reactivity coefficients and kinetics parameters at any modeled fuel cycle time point which forms part of the input to SAS4A. The ARC suite was consistently being developed until the 1990s and followed a software QA program which was an appropriate standard for the time. In the 1990s, the DOE funding to fast reactor research and development was all but eliminated and the ARC software was put into maintenance mode. In the early 2000s, the software quality assurance (SQA) program for ARC was still in place to define an official version, but by 2005 it all but was abandoned as there were insufficient staff to fill the work roles. Since 2005, there has been a considerable increase in research and design work on fast spectrum reactors. The ARC software as a whole has since been exported to many universities and commercial companies and ANL support has been given to the various projects over the years [19-23]. Further, MC 2 -3, PERSENT, and DASSH were all developed after 2005 without any adherence to a software standard. In recent time, the DOE VTR project [22] paid for verification work to be done on the ARC software as part of the goal of making it NQA-1 complaint. The VTR project was not considered the appropriate pathway to fund and maintain a SQA program for the ARC software and while software developments (DASSH) were made and several manuals were updated and software verification work was carried out, the ARC software is not NQA-1 compliant. More recently the Advanced Reactor Development Program (ARDP [23]) has funded the creation of manuals for some ARC utility programs and funded additional software verification work on DIF3D [6, 7] and MC 2 -3 [2-5] for the purpose of commercial grade dedication. Because of the VTR and ARDP projects, software verification work was completed on MC 2 -3 and DIF3D, and detailed reports were created for each piece of software, which discuss the inputs and outputs from the codes that are covered by the verification work and link various analytic, code-to-code, and hand calculation based verification work presented in the report with verification test problems provided with the software. This is a key part of the commercial grade dedication work and constitutes the bulk of the cost to get the ARC software to commercial grade. The ARC software suite is a valuable asset as a fast reactor design and analysis tool set that has been reasonably well verified and validated with various fast reactor benchmark problems and experiments over decades. Some or all of the ARC software suite has been utilized for designing the IFR [20], PGSFR [21], VTR [22], and Natrium [23] reactors and we can expect it to continue to be used for advanced fast reactor design and/or confirmatory calculation purposes in the future. Due to increased interest by commercial companies and regulatory bodies, it is becoming more important to make the ARC software suite complete and ready-to-use in terms of its SQA pedigree and commercial grade dedication needs. This report discusses the achievements made towards building a new SQA program for the ARC software and dealing with outstanding identified QA gaps.
97 MATHEMATICS AND COMPUTING↗
Converting DYNAMO simulations to Powersim Studio simulations
DYNAMO is a computer program for building and running 'continuous' simulation models. It was developed by the Industrial Dynamics Group at the Massachusetts Institute of Technology for simulating dynamic feedback models of business, economic, and social systems. The history of the system dynamics method since 1957 includes many classic models built in DYANMO. It was not until the late 1980s that software was built to take advantage of the rise of personal computers and graphical user interfaces that DYNAMO was supplanted. There is much learning and insight to be gained from examining the DYANMO models and their accompanying research papers. We believe that it is a worthwhile exercise to convert DYNAMO models to more recent software packages. We have made an attempt to make it easier to turn these models into a more current system dynamics software language, Powersim © Studio produced by Powersim AS 2 of Bergen, Norway. This guide shows how to convert DYNAMO syntax into Studio syntax.
97 MATHEMATICS AND COMPUTING↗
Code Verification and Solution Verification framework in pin-resolved neutron transport code MPACT
Program verification in scientific computing encompasses the application of formal and mathematical techniques to a scientific computing code for its credibility, accuracy, and validity. Code Verification identifies bugs and performance issues in the software development stage. Solution Verification assesses the applicability of the code and the accuracy of the solution to problems of interest. Both activities utilize application cases and quantify the error against prescribed acceptance criteria. However, simply executing more application cases does not guarantee stronger or more comprehensive credibility. Here, we establish a verification framework that involves Code Verification and Solution Verification, both of which work together such that the overarching goal of “converge to the correct answer for the intended application” can be reasonably inferred. The application of such a verification framework is demonstrated using the pin-resolved neutron transport code MPACT, where standard unit tests and regression tests are covered, and where the Method of Exact Solutions and the Method of Manufactured Solutions are successfully used. Additionally, the applicability of Method of Manufactured Solutions is extended to the OECD/NEA C5G7 benchmark problems of practical material and geometric configurations. Solution Verification activities are demonstrated on a practical hierarchy of application models of increasing complexity ranging from 2D pin cell problems to 3D assembly problems. The convergence behavior and rate of convergence with respect to each individual variable are studied and provided. This framework can be adapted broadly to other fields involving scientific computing codes.
97 MATHEMATICS AND COMPUTING↗
Simple utility for creat1n1 and signing SSL certificates.
Generally, for encrypted communication to occur, a root trust must be established (usually In the form of a certificate authority) and used to sign communlcatln1 component's certificates that are used to perform encryption. This process ls rather Involved In a number of manual steps with arcane command syntax. Certlpy wraps the standard Python PyOpenSSL library to simplify the calls to create the above mentioned PKI (public key infrastructure) with both a command line and programming Interface. Certlpy was orlglnally created to automate and manage PKI within the open source JupyterHub project so that It could be deployed safely In Uvennore Computing. JupyterHub Is a collection of software components enabling Interactive python notebooks and reproducible science. To ensure secure communication throuahout, Certlpy signs and Issues certs to each component: enabling encryption and authentication (SSL).
Mendoza, Thomas↗
Large Scale Computing and Storage Requirements for Basic Energy Sciences: Target 2017. Report of the NERSC Requirements Review Conducted October 8–9, 2013, Gathersburg, MD
The National Energy Research Scientific Computing Center (NERSC) is the primary computing center for the DOE Office of Science, serving approximately 5,000 users working on some 700 projects that involve nearly 600 codes in a wide variety of scientific disciplines. In addition to large-scale computing and storage resources NERSC provides support and expertise that help scientists make efficient use of its systems. The latest review revealed several key requirements, in addition to achieving its goal of characterizing BES computing and storage needs. high-level findings are: 1) Scientists will need access to significantly more computational and storage resources to achieve their goalds and reach BES research objectives; 2) Users will need assistance from NERSC to prepare for Cori (NERSC-8) and follow-on manycore systems; 3) Research teams need to run complex jobs of many different types and scales; 4) BES is a leader in innovative use of HPC and requires a diverse set of resources and services from NERSC; and 5) BES facilities need computational analysis and data storage resources beyond what they can provide. This report expands upon these key points and add others. The results are based upon representative samples, called "case studies," of the needs of science teams within BES. The case study topics were selected by the NERSC meeting coordinators and BES program managers to represent the BES production computing workload. Prepared by BES workshop participants, the case studies contain a summary of science goals, methods of solution, current and future computing requirements, and special software and support needs. Also included are strategies for computing in the highly parallel "many-core" environment that is expected to dominate HPC architectures over the next few years.
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Rich-Text based PSA Model Transformation and Verification in RiskA
Nuclear Energy is one of the most possible alternative to fossil energy in large-scale. Nuclear safety is the lifeline of nuclear energy development, and has been an important part of national security, especially after the accident of Fukushima. On the basis of computer codes, reliability engineering and Probabilistic Risk Assessment (PSA) is effective methods to improve the safety of nuclear power plants. After many years of development, the methodologies, applications and relevant soft programs have been quite sufficient in the area of nuclear safety. However, it is still difficult for the current PSA technologies and software to meet the needs of dealing with the problems of quantitatively public risk assessment in the digital society. Especially, there are so many software that adopted different modeling and analyzing methods, which brings difficulties to the comparison, evaluation or verification for different software and models. By using its own academic advantages, the advanced nuclear energy research team, i.e., FDS Team has invested a few hundreds person-years of independent research and development of a reliability and probabilistic safety assessment software system RiskA. The system consists of three main functions: device reliability optimization management, probabilistic safety assessment and instantaneous risk monitoring, and the comprehensive public risk assessment in digital society. RiskA establishes an integrated risk evaluation system for the device reliability, nuclear power plant (NPP) risk monitoring and public risk assessment. Currently, RiskA has successfully been applied in more than 600 organizations and institutes from a variety of fields in 39 countries, involving nuclear, aerospace, defense and so on. For example, RiskA has been used in the safety analysis of International Thermonuclear Experimental Reactor (ITER), FDS series fusion reactor, and the Strategic Priority Research Program of Chinese Academy of Sciences 'the Future Advanced Nuclear Fission Energy - Accelerator Driven Sub-critical (ADS) transmutation system'. Also, RiskA has been used in public risk communication and risk assessment. Among them, Third Qinshan nuclear power plant Risk Monitor (TQRM), which is the China's first domestic nuclear safety analysis software used in the actual online operation, has been highly apprised by renowned experts in the field. Meanwhile, it has been identified as the first domestic nuclear power plant risk monitoring system with completely independent intellectual property rights, and has reached the international advanced level. (authors)
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Control And Optimization Modular Modeling Application For Nuclear Deployment
The purpose of the COMMAND code is to provide a flexible, scalable tool for use in developing, integrating, and testing the technologies necessary for achieving autonomous operations of advanced nuclear reactors. The code enables users to efficiently implement custom simulations and experiments by combining key methods from different software modules. These modules are focused on: modeling and simulation tools, such as nuclear simulation tools used for high-fidelity modeling (e.g., Reactor Excursion and Leak Analysis Program [RELAP5-3D] and Monte Carlo N-Particle [MCNP]); machine learning and optimization tools (e.g., anomaly detection and data-driven modeling techniques); advanced control in its digital, high-performance, and supervisory control forms (e.g., proportional integral derivative (PID) control and model predictive control (MPC); and integration with hardware through industrial communication protocols. To ensure flexibility and scalability, COMMAND was designed to be both modular—the software “pieces” all inherit from generic building blocks and can be combined and connected to create complicated simulations—and high performing—designed for parallel processing, enabling simulations and experiments to take advantage of multi-core computers, servers, and nodes. The code is written in the Python programming language due to the language's popularity, active community, and open-source and cross-platform nature. Maintaining consistency with other simulation tools used within the nuclear energy community, users implement simulations and experiments through text input files, which define components, parameters, connections, etc., through lines of text. Given that COMMAND is written in Python, these input files are native Python scripts, and so use the standard Python structure and formatting. This also enables users to take advantage of Python's extensive package library to develop custom capabilities for their specific use cases.
Faber, Jacob [Idaho National Laboratory (INL), Ida↗
PCF File Format
PCF files are binary files designed to contain gamma spectra and neutron count rates from radiation sensors. It is the native format for the GAmma Detector Response and Analysis Software (GADRAS) package. It can contain multiple spectra and information about each spectrum such as energy calibration. This document outlines the format of the file that would allow one to write a computer program to parse and write such files.
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Management of Digital Equipment in Preproduction by Means of Uniform Numeric Control Language
The requirements on preproduction and the control software for various digital machining systems (numerically controlled machine tools, robot manipulators, additive manufacturing equipment) in flexible production are considered. By analysis of existing programming languages for digital equipment, UNCL (Uniform Numeric Control Language) has been developed for standard representation of control commands. The use of UNCL in verifying program operation on a machining simulator is considered. Software for the translation of control programs (specified in CLDATA formats and in ISO code) to the invariant format of the universal language is described. The postprocessing of control software from the universal language into programs in commonly used digital control systems is also considered.
42 ENGINEERING↗
Robust Critical Point Detection
Robust Critical Point Detection is a software to compute critical points in a 2D or 3D vector field robustly. The software was developed as a part of the author's work at the lab as a Phd student under Livermore Scholar Program (now called Livermore Graduate Scholar Program).
Bhatia, Harsh↗
MFANS 2024 - Formally Proving Characteristics of Cyber-Physical Systems
Cyber-physical systems (CPS) are engineered systems that rely on the smooth integration of computational algorithms and physical elements. This integration presents new challenges for verifying that systems will behave as expected. The goal of this presentation is to present current challenges and potential solutions for the formal verification of cyber-physical systems. For cyber systems, formal methods refer to systematically rigorous mathematical techniques employed in the specification, development, analysis, and verification of both software and hardware systems. Recent advancements in computer science have yielded sophisticated tools specifically designed to address challenges associated with formal methods in complex systems. These tools leverage various foundational concepts such as logic, formal languages, program semantics, type systems, type theory, and automata theory. A notable achievement in the application of formal methods is the seL4 microkernel, claimed to be the first general-purpose operating-system kernel to be verified. Its proof implies the absence of bugs and guarantees that the kernel meets specifications. For physical systems, dynamic and control theory has a history of using rigorous analytic techniques to prove functional correctness. Lyapunov, optimal, classical, modern, and robust control theories all provide rigorous mathematical methods both to analyze system performance and to design controller that can be guaranteed to meet certain objectives. Recent computational techniques like level set theory and reachability analysis provide assertions that a system's state will avoid unsafe regions. Even though success has been independently achieved for cyber systems and physical systems, the integration of such systems creates new challenges. In particular, there is an obvious discrepancy between finite-state machines and infinite-state systems, resulting in different approaches for modeling and analyzing these system. While it is possible to simulate hybrid systems, this provides only a demonstration of a performance and not proof. For hybrid systems, current formal methods and system analysis approaches typically require a workarounds to work on hybrid systems like CPS. This paper will outline the state of the art and limits of current practice for formally verifying CPS and will identify possible research directions that require attention.
97 MATHEMATICS AND COMPUTING↗
INTEGRATED WORKFLOW MANAGEMENT FOR PARTICLE ACCELERATOR SIMULATION
Supercomputing systems are used for a wide range of computationally demanding tasks in many fields of science and engineering. They play a key role in numerical simulation, in which mathematical models are computed in order to simulate the behavior of physical systems. Scientists and engineers that use supercomputers for numerical simulation often have their productivity limited by the need to manually organize and manage extremely large amounts of data that are often produced and consumed by the software programs run on these systems. Recognizing these limitations, Kitware Inc. (Clifton Park, NY) and SLAC National Accelerator Laboratory (Menlo Park, CA) are developing an advanced software platform that can reduce the cognitive overhead required by knowledge workers when using supercomputers for numerical simulation. Phase I of the project is complete and includes the development of new capabilities for organizing simulation project files, improvements to the user interface and overall usability, and deployment of a “middle tier” server to sit between user desktop machines and supercomputers to offload much of the data management workload. The project also developed prototype software for executing sequences of numerical simulations, and a prototype for migrating supercomputing software to cloud-based computing systems to provide a potential alternative to supercomputers with different logistical and price-to-performance tradeoffs.
Tourtellott, John↗
MOLNs: A Cloud Platform for Interactive, Reproducible, and Scalable Spatial Stochastic Computational Experiments in Systems Biology Using PyURDME
Computational experiments using spatial stochastic simulations have led to important new biological insights, but they require specialized tools and a complex software stack, as well as large and scalable compute and data analysis resources due to the large computational cost associated with Monte Carlo computational workflows. The complexity of setting up and managing a large-scale distributed computation environment to support productive and reproducible modeling can be prohibitive for practitioners in systems biology. This results in a barrier to the adoption of spatial stochastic simulation tools, effectively limiting the type of biological questions addressed by quantitative modeling. In this paper, we present PyURDME, a new, user-friendly spatial modeling and simulation package, and MOLNs, a cloud computing appliance for distributed simulation of stochastic reaction-diffusion models. In conclusion, MOLNs is based on IPython and provides an interactive programming platform for development of sharable and reproducible distributed parallel computational experiments.
97 MATHEMATICS AND COMPUTING↗