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At least 109 records · Page 6

Near Real-time Data Analysis of Core-collapse Supernova Simulations with Bellerophon

We present an overview of a software system, Bellerophon, built to support a production-level HPC application called CHIMERA, which simulates core-collapse supernova events at the petascale. Developed over the last four years, Bellerophon enables CHIMERA's geographically dispersed team of collaborators to perform data analysis in near real-time. Its n-tier architecture provides an encapsulated, end-to-end software solution that enables the CHIMERA team to quickly and easily access highly customizable animated and static views of results from anywhere in the world via a web- deliverable, cross-platform desktop application. In addition, Bellerophon addresses software engineering tasks for the CHIMERA team by providing an automated mechanism for performing regression testing on a variety of supercomputing platforms. Elements of the team's workflow management needs are met with software tools that dynamically generate code repository statistics, access important online resources, and monitor the current status of several supercomputing resources.

97 MATHEMATICS AND COMPUTING↗

UQpy v4.1: Uncertainty quantification with Python

This paper presents the latest improvements introduced in Version 4 of the UQpy, Uncertainty Quantification with Python, library. In the latest version, the code was restructured to conform with the latest Python coding conventions, refactored to simplify previous tightly coupled features, and improve its extensibility and modularity. To improve the robustness of UQpy, software engineering best practices were adopted. A new software development workflow significantly improved collaboration between team members, and continuous integration and automated testing ensured the robustness and reliability of software performance. Continuous deployment of UQpy allowed its automated packaging and distribution in system agnostic format via multiple channels, while a Docker image enables the use of the toolbox regardless of operating system limitations.

97 MATHEMATICS AND COMPUTING↗

A New Overview of The Trilinos Project

Since An Overview of the Trilinos Project [ACM Trans. Math. Softw. 31(3) (2005), 397–423] was published in 2005, Trilinos has grown significantly. It now supports the development of a broad collection of libraries for scalable computational science and engineering applications, and a full-featured software infrastructure for rigorous lean/agile software engineering. This growth has created significant opportunities and challenges. This paper focuses on some of the most notable changes to the Trilinos project in the last few years. At the time of the writing of this article, the current release version of Trilinos was 10.12.2.

Heroux, Michael A.↗

A Survey of Open Source Software Repositories in the U.S. Department of Energy’s National Laboratories

There are 17 national laboratory systems in the United States operating under the auspices of the U.S. Department of Energy (DOE). These government labs employ tens of thousands of people engaging in research software engineering activities across a variety of missions. To support this work, many open source projects are maintained. Further, many of these projects have broad utility to the computing community at large and domain scientists in a variety of fields. However, the complexity and decentralized nature of the laboratory system has resulted in a situation where no one entity even knows about all the open source software projects in this ecosystem, let alone crude metrics of their health. In this article, we do the first external inventory of open source software repositories with a nexus to DOE labs. We posit that a project’s need for sustainability support can be determined by comparing measures of active use to measures of active maintenance.

97 MATHEMATICS AND COMPUTING↗

Impacts of software and its engineering on the carbon footprint of ICT

The energy consumption of information and communication technology (ICT) is still increasing. Even though several solutions regarding the hardware side of Green IT exist, the software contribution to Green IT is not well investigated. The carbon footprint is one way to rate the environmental impacts of ICT. In order to get an impression of the induced CO{sub 2} emissions of software, we will present a calculation method for the carbon footprint of a software product over its life cycle. We also offer an approach on how to integrate some aspects of carbon footprint calculation into software development processes and discuss impacts and tools regarding this calculation method. We thus show the relevance of energy measurements and the attention to impacts on the carbon footprint by software within Green Software Engineering.

54 ENVIRONMENTAL SCIENCES↗

Cyber Dumpster Diving: Creating New Software Systems for Less

Modern scientific software is daunting in its breadth and complexity. From massively parallel simulations running on the world’s largest supercomputers to visualizations and user support environments that manage ever-growing, complex data collections, the challenges for software engineers are plentiful indeed.

software architecture↗

Building a Community Infrastructure for Scalable On-Line Performance Analysis Tools around Open|SpeedShop

In this project we created a community tool infrastructure for program development tools targeting Petascale class machines and beyond. This includes tools for performance analysis, debugging, and correctness tools, as well as tuning and optimization frameworks. The developed infrastructure provides a comprehensive and extensible set of individual tool building components. We started with the basic elements necessary across all tools in such an infrastructure followed by a set of generic core modules that allow a comprehensive performance analysis at scale. Further, we developed a methodology and workflow that allows others to add or replace modules, to integrate parts into their own tools, or to customize existing solutions. In order to form the core modules, we built on the existing Open|SpeedShop infrastructure and decomposed it into individual modules that match the necessary tool components. At the same time, we addressed the challenges found in performance tools for petascale systems in each module. When assembled, this instantiation of community tool infrastructure provides an enhanced version of Open|SpeedShop, which, while completely different in its architecture, provides scalable performance analysis for petascale applications through a familiar interface. This project also built upon and enhances capabilities and reusability of project partner components as specified in the original project proposal. The overall project team’s work over the project funding cycle was focused on several areas of research, which are described in the following sections. The reminder of this report also highlights related work as well as preliminary work that supported the project. In addition to the project partners funded by the Office of Science under this grant, the project team included several collaborators who contribute to the overall design of the envisioned tool infrastructure. In particular, the project team worked closely with the other two DOE NNSA laboratories Los Alamos and Sandia leveraging co-funding for Krell by ASC’s Common Computing Environment (CCE) program as laid out in the original proposal. The ASC CCE co-funding, coordinated through LLNL, was for 50% of the total project funding, with the ASC CCE portion of the funding going entirely to Krell, while the ASCR funding itself was split between Krell and the funded partners. This report covers the entire project from both funding sources. Additionally, the team leveraged the expertise of software engineering researchers from Carnegie Mellon University, who specialize in software framework design, in order to achieve a broadly acceptable component framework. The Component Based Tool Framework (CBTF) software has been released to the community. Information related to the project and the released software can be found on the CBTF wiki page at: http://sourceforge.net/p/cbtf/wiki/Home.

97 MATHEMATICS AND COMPUTING↗

Sensitivity Analysis of Offshore Wind Cost of Energy (Poster)

No matter the source, offshore wind energy plant cost estimates are significantly higher than for land-based projects. For instance, a National Renewable Energy Laboratory (NREL) review on the 2010 cost of wind energy found baseline cost estimates for onshore wind energy systems to be 71 dollars per megawatt-hour ($/MWh), versus 225 $/MWh for offshore systems. There are many ways that innovation can be used to reduce the high costs of offshore wind energy. However, the use of such innovation impacts the cost of energy because of the highly coupled nature of the system. For example, the deployment of multimegawatt turbines can reduce the number of turbines, thereby reducing the operation and maintenance (O&M) costs associated with vessel acquisition and use. On the other hand, larger turbines may require more specialized vessels and infrastructure to perform the same operations, which could result in higher costs. To better understand the full impact of a design decision on offshore wind energy system performance and cost, a system analysis approach is needed. In 2011-2012, NREL began development of a wind energy systems engineering software tool to support offshore wind energy system analysis. The tool combines engineering and cost models to represent an entire offshore wind energy plant and to perform system cost sensitivity analysis and optimization. Initial results were collected by applying the tool to conduct a sensitivity analysis on a baseline offshore wind energy system using 5-MW and 6-MW NREL reference turbines. Results included information on rotor diameter, hub height, power rating, and maximum allowable tip speeds.

17 WIND ENERGY↗

Shadow of the Future: Developing Trust and Software within the Exascale Computing Project

Collaboration and team science are emerging areas of interest in software production. Historically, multi-institutional research collaborations are difficult to initiate and maintain, negatively impacting communication, negotiation, and dialogue between industry, government, and academic researchers. The Exascale Computing Project (ECP), a massive, multi-team, high-stakes initiative, facilitated broader research collaboration under a shared funding structure and extended timeline to support scientific discovery. Here, we conducted interviews with ECP teams, representing a variety of domain specialties, research institutions, and programming backgrounds. Using thematic analysis, we assessed how ECP’s structure created an environment of increased trust among projects and how software shared between teams facilitated sustained collaboration. We found that the expectation of future collaboration, i.e., the shadow of the future, greatly enhanced trust among teams and the quality of scientific software produced. Based on our findings within ECP projects, we connect to the existing literature on trust in software engineering and share recommendations for sustainable multi-institutional collaboration and shared best software practices.

Exascale computing project↗

Kokkos v.4.0

SAND2023-07883O Kokkos software implements C++ performance portability programming models, tools and math libraries, which enables science and engineering software developers to use single-source codes for a wide range of computer architectures. Kokkos also provides implementations of existing and proposed C++ standard features that support programming model and math libraries that are used for implementing performance-portable scientific and engineering applications. The Kokkos libraries provide algorithms, data structures, and tools to enable high-performance computing developers to write performance-portable code. Capabilities fall into three broad categories: Kokkos Core, Kokkos Kernels, and Kokkos Tools. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

SciDAC↗

MetaBAT 2: an adaptive binning algorithm for robust and efficient genome reconstruction from metagenome assemblies

We previously reported MetaBAT, an automated metagenome binning software tool to reconstruct single genomes from microbial communities for subsequent analyses of uncultivated microbial species. MetaBAT has become one of the most popular binning tools largely due to its computational efficiency and ease of use, especially in binning experiments with a large number of samples and a large assembly. MetaBAT requires users to choose parameters to fine-tune its sensitivity and specificity. If those parameters are not chosen properly, binning accuracy can suffer, especially on assemblies of poor quality. Here we developed MetaBAT 2 to overcome this problem. MetaBAT 2 uses a new adaptive binning algorithm to eliminate manual parameter tuning. We also performed extensive software engineering optimization to increase both computational and memory efficiency. Comparing MetaBAT 2 to alternative software tools on over 100 real world metagenome assemblies shows superior accuracy and computing speed. Binning a typical metagenome assembly takes only a few minutes on a single commodity workstation. We therefore recommend the community adopts MetaBAT 2 for their metagenome binning experiments. MetaBAT 2 is open source software and available at https://bitbucket.org/berkeleylab/metabat .

Kang, Dongwan↗

MetaBAT 2: an adaptive binning algorithm for robust and efficient genome reconstruction from metagenome assemblies

We previously reported on MetaBAT, an automated metagenome binning software tool to reconstruct single genomes from microbial communities for subsequent analyses of uncultivated microbial species. MetaBAT has become one of the most popular binning tools largely due to its computational efficiency and ease of use, especially in binning experiments with a large number of samples and a large assembly. MetaBAT requires users to choose parameters to fine-tune its sensitivity and specificity. If those parameters are not chosen properly, binning accuracy can suffer, especially on assemblies of poor quality. Here, we developed MetaBAT 2 to overcome this problem. MetaBAT 2 uses a new adaptive binning algorithm to eliminate manual parameter tuning. We also performed extensive software engineering optimization to increase both computational and memory efficiency. Comparing MetaBAT 2 to alternative software tools on over 100 real world metagenome assemblies shows superior accuracy and computing speed. Binning a typical metagenome assembly takes only a few minutes on a single commodity workstation. We therefore recommend the community adopts MetaBAT 2 for their metagenome binning experiments. MetaBAT 2 is open source software and available at https://bitbucket.org/berkeleylab/metabat .

59 BASIC BIOLOGICAL SCIENCES↗

An Approach to Automate tools for the Risk Assessment of Digital Instrumentation and Control Systems

Reliable digital instrumentation and control systems (DI&C) are integral for sustaining the continued operation of nuclear power plants. These systems ensure that nuclear reactors operate safely, efficiently, and within regulatory requirements. Yet, the cost of designing and licensing new nuclear DI&C can be prohibitively expensive. Under the U.S. Department of Energy Light Water Reactor Sustainability Program, Idaho National Laboratory has developed a framework for supporting the risk-informed design of DI&C systems by offering methods to support the identification, quantification, and evaluation of risks for various DI&C design architectures. The framework indicates potential software failure modes and provides pathways for quantifying the potential for these software failures, including common cause failures. Using the framework’s systematic approach, challenges for assessing risks within new and existing nuclear DI&C systems can be reduced. Nevertheless, the current framework can be further improved using the convenience of automation. This paper introduces the development of Software for the Hazard Identification and Evaluation of Digital Systems (SHIELDS). SHIELDS is an engineering software package that enables the identification, elimination, and mitigation of potential risks and reduces the burden of deploying reliable DI&C systems. This work introduces plans and techniques to digitize and improve the manual risk assessment modules of the framework. These improvements will save time and increase the repeatability and usability of the framework, making it more accessible to a wider range of users. Ultimately, this introduces SHIELDS and how its modules support efficient development of safe and reliable DI&C systems.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

Spectral/ hp finite element models for fluids and structures

In the numerical simulation of a wide range of physical phenomena (mathematically de scribed in terms of boundary or initial boundary-value problems), the finite element method has emerged as one of the most powerful tools for obtaining accurate, efficient and stable approximate solutions. Since the publication of the groundbreaking work of Turner et al., the scientific literature and, much more importantly , practical engineering software based on the finite element method have grown at a remarkable pace, spanning many fields of engineering and applied science. At present, the finite element method is widely recognized as the premier computational procedure for the numerical simulation of solid mechanics problems. Outside the realm of the mechanics of solids, however, the method has yet to receive such a level of acceptance and prominence. This is especially noteworthy in computational fluid dynamics (CFD), a field that is presently dominated by low-order finite difference and finite volume technologies.

Payette, Gregory Steven↗

Workshop on Software Productivity for Extreme-scale Science, January 13-14, 2014, Hilton Hotel, Rockville, MD

While emerging extreme-scale computing systems provide unprecedented resources for scientific discovery, DOE’s scientific communities now face a crisis in extreme-scale scientific software productivity due to a powerful confluence of factors: ongoing disruptive changes in computer architectures and new frontiers in modeling, simulation, and analysis of complex multiscale and multiphysics phenomena. Research in mission-critical science and energy problems has become increasingly dependent on high-performance computing, but productivity in extreme-scale scientific application development has not kept pace. The principal issues are (1) a significant lag between extreme-scale hardware and algorithmic innovations and their effective use in applications, leading to poorly scaling codes; (2) obstacles in the combined use of independently developed software components; (3) lack of agile yet rigorous software engineering practices for high-performance computing; and (4) failure to consider the entire lifecycle of large scientific software efforts, leading to fragile, complicated application codes that are increasingly difficult to enhance.

97 MATHEMATICS AND COMPUTING↗

Reactor physics verification of the MCNP6 unstructured mesh capability

The Monte Carlo software package MCNP6 has the ability to transport particles on unstructured meshes generated from the Computed-Aided Engineering software Abaqus. Verification is performed using benchmarks with features relevant to reactor physics - Big Ten and the C5G7 computational benchmark. Various meshing strategies are tested and results are compared to reference solutions. Computational performance results are also given. The conclusions show MCNP6 is capable of producing accurate calculations for reactor physics geometries and the computational requirements for small lattice benchmarks are reasonable on modern computing platforms. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

High Fidelity Fast Running Multi-scale Multi-physics Battery Pack Software

The project team comprising of General Motors LLC (GM), ANSYS, ESim, and the National Renewable Energy Laboratory (NREL) proposed to develop multiscale multiphysics battery pack engineering software that significantly surpassed the most advanced state-of-the-art software in computational speed and accuracy. The successful software was to run faster than current state-of-the-art software by a factor of 100 while resolving complex multiphysics interplays across the scales from materials to large automotive battery pack systems. The proposed project was to shift the paradigm to using software for battery pack system design and evaluation, potentially revolutionizing the standard development process for the broader electric vehicle industry. The project objectives were to: (a) enhance computation speed and stability of the pack level multiscale model while still resolving nonlinearities of the battery’s dynamic responses across the scales from particles to a battery pack and (b) enhance multiphysics integrity at the pack level model enabling model-based diagnostics and prognostics for life and safety.

25 ENERGY STORAGE↗