Results for “coded source” — Page 16

DOE OSTI2023

Automatic Code Generation for High-Performance Graph Algorithms

Graph problems are common across fields of scientific computing and social sciences. However, despite their importance, implementing graph algorithms effectively on modern computing systems is a challenging task that requires significant programming effort and generally results in customized implementations. Current computing and memory hierarchies are not architected for irregular computations resulting in challenges for graph algorithms to achieve high performance on those architectures. In this paper, we present GraphX, a novel compiler framework and DSL designed to simplify the development of efficient graph algorithms and achieve high performance on modern computing systems. GraphX consists of a DSL for efficient implementation of graph algorithms, various optimizations, such as support for sparse linear algebra and workspace transformations, optimized graph primitives, including semiring and masking, and a high-performance code generation engine. Using GraphX, users can implement graph algorithms using a semantically-rich language with graph-oriented operators. GraphX uses these semantics to automatically generate efficient code for target architectures, increasing performance and portability across architectures. The composable nature of GraphX makes it possible to extend the set of optimizations and architectures without modifying the source code. We demonstrate GraphX outperforms state-of-the-art graph libraries, such as LAGraph, up to $3.7 speedup in semiring operations, $2.19 speedup in an important sparse computational kernel, and $9.05 speedup in graph processing algorithms.

compiler, graph algorithms, semiring, masking, wor↗

DOE OSTI2018

Summer Report: Tool Integration for Variable-Precision Computing

This summer I worked in the tools group of the variable-precision computing effort at Lawrence Livermore National Laboratory (LLNL). I coordinated an integration project that combined three existing tools into a single pipeline for automated mixed-precision tuning at the source code level. This involved coordinating efforts between several different project groups and making improvements to all three tools. Two of the tools are already available publicly as open-source projects, and the third has been submitted for release. This document serves as an overview of the summer's efforts, focusing on our contributions as well as ideas for future work.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2015

Sandia Simple Particle Tracking (Sandia SPT) v. 1.0

Sandia SPT is designed as software to accompany a book chapter being published a methods chapter which provides an introduction on how to label and track individual proteins. The Sandia Simple Particle Tracking code uses techniques common to the image processing community, where its value is that it facilitates implementing the methods described in the book chapter by providing the necessary open-source code. The code performs single particle spot detection (or segmentation and localization) followed by tracking (or connecting the detected particles into trajectories). The book chapter, which along with the headers in each file, constitutes the documentation for the code is: Anthony, S.M.; Carroll-Portillo, A.; Timlon, J.A., Dynamics and Interactions of Individual Proteins in the Membrane of Living Cells. In Anup K. Singh (Ed.) Single Cell Protein Analysis Methods in Molecular Biology. Springer

Anthony, StephenM.↗

DOE OSTI2018

Matlab Code for Multiscale Topology Optimization

This Matlab script implements a simple topology optimization algorithm that minimizes the compliance of a structure within a 3D prismatic design domain. It uses a simple linear elastic finite element solver to solve the equilibrium equations, and the optimality criterion (00) method to update the design iteratively. This functionality is identical to, or the simplest possible extension from 2D to 3D of, a 99-line Matlab code released in 2001 in a journal article by Sigmund. What is new in this code is our implementation of simple surrogate models for several truss micro-architectures, which converts this code to a multiscale design tool, whereas the original code is single-scale. The development of these surrogate models and their implementation is described in a journal article we intend to submit. We plan to include the full source code in an Appendix in this paper. The code’s primary function is as a pedagogical tool rather than as a finished software product. Sigmund’s 2001 paper describes the implementation line-by-line. We are including this updated version of the code to allow the reader to understand exactly what changes must be made to a “standard” topology optimization code to implement the surrogate models and thus multiscale design optimization.

Watts, Seth↗

DOE OSTI2015

Sandia Simple Particle Tracking (Sandia SPT) v. 1.0

Sandia SPT is designed as software to accompany a book chapter being published a methods chapter which provides an introduction on how to label and track individual proteins. The Sandia Simple Particle Tracking code uses techniques common to the image processing community, where its value is that it facilitates implementing the methods described in the book chapter by providing the necessary open-source code. The code performs single particle spot detection (or segmentation and localization) followed by tracking (or connecting the detected particles into trajectories). The book chapter, which along with the headers in each file, constitutes the documentation for the code is: Anthony, S.M.; Carroll-Portillo, A.; Timlon, J.A., Dynamics and Interactions of Individual Proteins in the Membrane of Living Cells. In Anup K. Singh (Ed.) Single Cell Protein Analysis Methods in Molecular Biology. Springer

Anthony, Stephen M.↗

DOE OSTI2015

Virtual Flow Simulator

Virtual Flow Simulator (VFS) is a state-of-the-art computational fluid mechanics (CFD) package that is capable of simulating multi-physics/multi-phase flows with the most advanced turbulence models (RANS, LES) over complex terrains. The flow solver is based on the Curvilinear Immersed Boundary (CURVIB) method to handle geometrically complex and moving domains. Different modules of the VFS package can provide different simulation capabilities for specific applications ranging from the fluid-structure interaction (FSI) of solid and deformable bodies, the two-phase free surface flow solver based on the level set method for ocean waves, sediment transport models in rivers and the large-scale models of wind farms based on actuator lines and surfaces. All numerical features of VFS package have been validated with known analytical and experimental data as reported in the related journal articles. VFS package is suitable for a broad range of engineering applications within different industries. VFS has been used in different projects with applications in wind and hydrokinetic energy, offshore and near-shore ocean studies, cardiovascular and biological flows, and natural streams and river morphodynamics. Over the last decade, the development of VFS has been supported and assisted with the help of various United States companies and federal agencies that are listed in the sponsor lists. In this version, VFS-Wind contains all the necessary modeling tools for wind energy applications, including land-based and offshore wind farms. VFS is highly scalable to run on either desktop computers or high performance clusters (up to 16,000 CPUs). This released version comes with a detailed user’s manual and a set of case studies designed to facilitate the learning of the various aspects of the code in a comprehensive manner. The included documentation and support material has been elaborated in a collaboration effort with Sandia National Labs under the contract DE-EE0005482. The VFS-Wind source code is distributed under the GNU General Public License (GPL 2.0), offering to the community the flexibility to use and expand the capabilities of the package. We note that future publications including academic journals that result from the use of VFS must be cited appropriately under the GPL v.2 license agreement.

Yang, Xiaolei↗

DOE OSTI2018

Enhancements to Concrete Modeling Capabilities in Grizzly 2.0

The Grizzly code has been under development for several years with the goal of modeling aging effects in a variety of nuclear power plant systems, components, and structures. Version 2.0 of Grizzly was recently released, including both major improvements to its probabilistic fracture mechanics capabilities for evaluation of irradiated reactor pressure vessels, as well as multiple improvements to its capability for modeling degradation of concrete structures. This report summarizes recent development in the Grizzly code specific to concrete modeling that are included in this release. Major highlights of this work include the release of much of the concrete modeling capabilities of Grizzly in an open-source code called BlackBear, modernization of the models and documentation of the code, support for including nonlinear mechanical constitutive models, including creep and damage, re-architecting the anisotropic expansion model to allow its use for modeling both expansion due to alkali-silica reaction and radiation-induced volumetric expansion, and developing a preliminary capability for modeling connection of reinforcing bars to a concrete matrix.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2015

Virtual Flow Simulator

Virtual Flow Simulator (VFS) is a state-of-the-art computational fluid mechanics (CFD) package that is capable of simulating multi-physics/multi-phase flows with the most advanced turbulence models (RANS, LES) over complex terrains. The flow solver is based on the Curvilinear Immersed Boundary (CURVIB) method to handle geometrically complex and moving domains. Different modules of the VFS package can provide different simulation capabilities for specific applications ranging from the fluid-structure interaction (FSI) of solid and deformable bodies, the two-phase free surface flow solver based on the level set method for ocean waves, sediment transport models in rivers and the large-scale models of wind farms based on actuator lines and surfaces. All numerical features of VFS package have been validated with known analytical and experimental data as reported in the related journal articles. VFS package is suitable for a broad range of engineering applications within different industries. VFS has been used in different projects with applications in wind and hydrokinetic energy, offshore and near-shore ocean studies, cardiovascular and biological flows, and natural streams and river morphodynamics. Over the last decade, the development of VFS has been supported and assisted with the help of various United States companies and federal agencies that are listed in the sponsor lists. In this version, VFS-Wind contains all the necessary modeling tools for wind energy applications, including land-based and offshore wind farms. VFS is highly scalable to run on either desktop computers or high performance clusters (up to 16,000 CPUs). This released version comes with a detailed user’s manual and a set of case studies designed to facilitate the learning of the various aspects of the code in a comprehensive manner. The included documentation and support material has been elaborated in a collaboration effort with Sandia National Labs under the contract DE-EE0005482. The VFS-Wind source code is distributed under the GNU General Public License (GPL 2.0), offering to the community the flexibility to use and expand the capabilities of the package. We note that future publications including academic journals that result from the use of VFS must be cited appropriately under the GPL v.2 license agreement.

Calderer, Antoni↗

DOE OSTI2018

MUFFSgenMC: An Open Source Muon Flexible Framework for Spectral Generation for Monte Carlo Applications

A cosmic ray Muon Flexible Framework for Spectral Generation for Monte Carlo Applications (MUFFSgenMC) has been developed to support state-of-the-art cosmic ray muon detection and tomographic applications. The flexible framework allows for easy and fast creation of source terms for popular Monte Carlo applications such as GEANT4 and MCNP, which simplifies the process of simulations. The flexible framework contains a variety of analytical, numerical, and parametric models that capture the main characteristics of the muon energy and angular distributions in the range 0 to 90 and at arbitrary energies. The primary model for muon energy distribution is an implementation of the Smith and Duller phenomenological model. The predictions for muon energies in the range from 1 GeV to 1 TeV and zenith angles 0 to 90 are validated against an extensive series of experimental spectrum measurements. Finally, the open source code available on Matlab’s Mathworks File Exchange (https://www.mathworks.com/matlabcentral/fileexchange/65585-muffsgenmc) was written to allow users to easily modify and expand the code. MUFFSgenMC can facilitate the study of cosmic ray muons for nuclear nonproliferation applications and will enable the development of new muon-based detection and imaging techniques by providing an easy source term generator.

Greulich, Christopher↗

DOE OSTI2021

Building Efficiency Targeting Tool for Energy Retrofits (BETTER) Web Application (BETTER Web App) v1.0

The Building Efficiency Targeting Tool for Energy Retrofits (BETTER) V.1.0 web application identifies cost-saving energy and emissions reductions in buildings and portfolios, without site visits or complex modeling. With minimal data entry, BETTER benchmarks a building's or portfolio's energy use against peers; quantifies energy, cost, and greenhouse gas (GHG) reduction potential; and recommends energy efficiency measures for individual buildings or portfolios, targeting specific energy savings levels. The source code of BETTER's modular, cross-platform analytical engine has previously been disclosed (2019-001) and is available on GitHub and can be adopted, redeveloped, and redistributed freely under an open-source license, allowing users to incorporate BETTER's analytical capabilities into their own software platforms and tools. The BETTER V.1.0 web application, developed with the Django web-framework and the Model-View-Controller (MVC) architecture being disclosed here, provides a graphical user interface (GUI) for any user to view the software tutorials, download and upload a data entry template, configure and run the BETTER analyses, and view the final analytical reports.

Szum, Carolyn↗

DOE OSTI2023

Python codes for the paper - "Trade-offs in the latent representation of microstructure evolution"

SAND2024-00946O Python codes used in "Trade-offs in the latent representation of microstructure evolution," a manuscript accepted for publication in Acta Materialia, are part of a repository. The code was developed to perform analysis of microstructure evolution. The repository consists of two main directories: models, which train and test models such as autoencoders and diffusion maps, and analysis, which analyzes microstructures. Source code is used to perform dimensionality reduction of microstructure data for analysis of its evolution in time. 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.

Dingreville, Remi↗

DOE OSTI2021

Sodium Fire Collaborative Study Progress -- CNWG Fiscal Year 2020

This report discusses the progress on the collaboration between Sandia National Laboratories (Sandia) and Japan Atomic Energy Agency (JAEA) on the sodium fire research in fiscal year 2020. First, the current sodium pool fire model in MELCOR, which is adapted from CONTAIN-LMR code, is discussed. The associated sodium fire input requirements are also presented. These input requirements are flexible enough to permit further model development via control functions to enhance the current model without modifying the source code. The theoretical pool fire model improvement developed at Sandia is discussed. A control function model has been developed from this improvement. Then, the validation study of the sodium pool fire model in MELCOR carried out by both Sandia and JAEA’s staff is described. To validate this pool fire model with the enhancement, a JAEA sodium pool fire experiment (F7-1 test) is used. The results of the calculation are discussed as well as suggestions for further model improvement. Finally, recommendations are made for new MELCOR simulations for next fiscal year, 2021.

36 MATERIALS SCIENCE↗

DOE OSTI2012

Burnup calculation methodology in the serpent 2 Monte Carlo code

This paper presents two topics related to the burnup calculation capabilities in the Serpent 2 Monte Carlo code: advanced time-integration methods and improved memory management, accomplished by the use of different optimization modes. The development of the introduced methods is an important part of re-writing the Serpent source code, carried out for the purpose of extending the burnup calculation capabilities from 2D assembly-level calculations to large 3D reactor-scale problems. The progress is demonstrated by repeating a PWR test case, originally carried out in 2009 for the validation of the newly-implemented burnup calculation routines in Serpent 1. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2023

Computational studies of impurity migration during induction stirring of molten uranium

Understanding and controlling impurity behavior in actinide metal casting processes are foundational for efficient part production yet remain major challenges for researchers and industry. To help provide insight regarding impurity distribution during actinide metal casting, we have developed computational fluid dynamics (CFD) models for a laboratory-scale system using commercial and open-source code. Multiple simulation frameworks allow for improved confidence in the resulting outputs, while taking advantage of the maturity and convenience offered by commercial platforms and simultaneously maintaining the transparency and flexibility often provided by open-source software. Here, we describe multiple experiment-informed models designed to simulate a specific laboratory system in which uranium melt, containing a known starting concentration of carbon impurity, is electromagnetically stirred in an induction furnace. Here, the goal of the simulations is to predict the motion of uranium carbide microparticles in the velocity field of the melt. Prior to simulating the uranium-carbon system, numerical models were validated using a previously published nonradioactive experimental system. Effects of the size and shape of impurity particles in the models were investigated and agree with experimental findings. Simulation of smaller particles (< 50 µm) shows more homogenous distribution throughout the stirred melt. With increased particle size (100 µm), the body forces, which include the buoyancy force, dominate over the drag force, causing larger particles to move toward the crucible walls and upward in the system.

36 MATERIALS SCIENCE↗

DOE OSTI2025

useeio-infra-app

This GitHub repository hosts the source code to an RShiny web application that implements the U.S. Environmentally-Extended Input-Output (USEEIO) model in order to conduct a screening-level life cycle analysis. The USEEIO model is an open-source model developed and maintained by the Environmental Protection Agency (EPA), along with colleagues and contractors, and is available on GitHub (https://github.com/USEPA/USEEIO). The USEEIO model incorporates environmental data into pre-existing Economic Input-Output Models, which look at the interdependence of different economic industries. In this web application, the focus is on energy infrastructure applications; however, it can be used to implement USEEIO in any area for which this model is applicable.

AS↗

DOE OSTI2024

AdvEP

AdvEP is a code repository which contains PyTorch implementations of various adversarial attacks on a deep neural network trained with Equilibrium Propagation (EP), which is a neuromorphic learning framework. AdvEP allows for the training, testing, and conducting white/black-box attacks of EP models on a wide variety of applications and datasets. AdvEP is based on the open-source code https://github.com/Laborieux-Axel/Equilibrium-Propagation which was developed to train energy models. AdvEP was created by modifying the original code to perform and test against adversarial attacks. AdvEP was developed in Python, a high-level programming language that takes advantage of the Python ecosystem of high-quality open-source packages for machine learning. AdvEP interfaces heavily with the open-source PyTorch Python package as well as the open-source Adversarial Robustness Toolbox (ART) package.

Mansingh, Siddarth↗

DOE OSTI2012

THE McGill PLANAR HYDROGEN ATMOSPHERE CODE (McPHAC)

The McGill Planar Hydrogen Atmosphere Code (McPHAC) v1.1 calculates the hydrostatic equilibrium structure and emergent spectrum of an unmagnetized hydrogen atmosphere in the plane-parallel approximation, at surface gravities appropriate for neutron stars. McPHAC incorporates several improvements over previous codes for which tabulated model spectra are available: (1) Thomson scattering is treated anisotropically, which is shown to result in a 0.2%-3% correction in the emergent spectral flux across the 0.1-5 keV passband; (2) the McPHAC source code is made available to the community, allowing it to be scrutinized and modified by other researchers wishing to study or extend its capabilities; and (3) the numerical uncertainty resulting from the discrete and iterative solution is studied as a function of photon energy, indicating that McPHAC is capable of producing spectra with numerical uncertainties <0.01%. The accuracy of the spectra may at present be limited to {approx}1%, but McPHAC enables researchers to study the impact of uncertain inputs and additional physical effects, thereby supporting future efforts to reduce those inaccuracies. Comparison of McPHAC results with spectra from one of the previous model atmosphere codes (NSA) shows agreement to {approx}<1% near the peaks of the emergent spectra. However, in the Wien tail a significant deficit of flux in the spectra of the previous model is revealed, determined to be due to the previous work not considering large enough optical depths at the highest photon frequencies. The deficit is most significant for spectra with T{sub eff} < 10{sup 5.6} K, though even there it may not be of much practical importance for most observations.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

ATLAS: a Snakemake workflow for assembly, annotation, and genomic binning of metagenome sequence data

Background: Metagenomics and metatranscriptomics studies provide valuable insight into the composition and function of microbial populations from diverse environments, however the data processing pipelines that rely on mapping reads to gene catalogs or genome databases for cultured strains yield results that underrepresent the genes and functional potential of uncultured microbes. Recent improvements in sequence assembly methods have eased the reliance on genome databases, thereby allowing the recovery of genomes from uncultured microbes. However, configuring these tools, linking them with advanced binning and annotation tools, and maintaining provenance of the processing continues to be challenging for researchers. Results: Here we present ATLAS, a software package for customizable data processing from raw sequence reads to functional and taxonomic annotations using state-of-the-art tools to assemble, annotate, quantify, and bin metagenome and metatranscriptome data. Genome-centric resolution and abundance estimates are provided for each sample in a dataset. ATLAS is written in Python and the workflow implemented in Snakemake; it operates in a Linux environment, and is compatible with Python 3.5+ and Anaconda 3+ versions. The source code for ATLAS is freely available, distributed under a BSD-3 license. Conclusions: ATLAS provides a user-friendly, modular and customizable Snakemake workflow for metagenome and metatranscriptome data processing; it is easily installable with conda and maintained as open-source on GitHub at https://github.com/metagenome-atlas/atlas.

59 BASIC BIOLOGICAL SCIENCES↗