Search NASA⌕ Search

SEARCH · Search NASA

Results for “linear solver”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

GridPACK Toolkit for Developing Power Grid Simulations on High Performance Computing Platforms

This paper describes the GridPACK™ framework, which is designed to help power grid engineers develop modeling software capable of running on todays high performance computers. The framework contains modules for setting up distributed power grid networks, assigning buses and branches with arbitrary behaviors to the network, creating distributed matrices and vectors, using parallel linear and non-linear solvers to solve algebraic equations, and mapping functionality to create matrices and vectors based on properties of the network. In addition, the framework contains additional functionality to support IO and to manage errors.

Palmer, Bruce J.↗
DOE OSTI2022

Reproduced Computational Results Report for “Ginkgo: A Modern Linear Operator Algebra Framework for High Performance Computing”

The article titled “Ginkgo: A Modern Linear Operator Algebra Framework for High Performance Computing” by Anzt et al. presents a modern, linear operator centric, C++ library for sparse linear algebra. Experimental results in the article demonstrate that Ginkgo is a flexible and user-friendly framework capable of achieving high-performance on state-of-the-art GPU architectures. In this report, the Ginkgo library is installed and a subset of the experimental results are reproduced. Specifically, the experiment that shows the achieved memory bandwidth of the Ginkgo Krylov linear solvers on NVIDIA A100 and AMD MI100 GPUs is redone and the results are compared to what presented in the published article. Upon completion of the comparison, the published results are deemed reproducible.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

PyTrilinos

PyTrilinos is a Python interface to selected Trilinos packages. This makes Trilinos linear algebra classes, linear solvers, preconditioners, nonlinear solvers, eigensolvers, and tools available to Python programmers. This broadens the user base of Trilinos, and facilitates rapid prototyping of scientific codes and interactive manipulation of large, distributed data sets.

Spotz, William↗
DOE OSTI2017

Futility

The Futility package contains the following: 1) Definition of the size of integers and real numbers; 2) A generic Unit test harness; 3) Definitions for some basic extensions to the Fortran language: arbitrary length strings, a parameter list construct, exception handlers, command line processor, timers; 4) Geometry definitions: point, line, plane, box, cylinder, polyhedron; 5) File wrapper functions: standard Fortran input/output files, Fortran binary files, HDF5 files; 6) Parallel wrapper functions: MPI, and Open MP abstraction layers, partitioning algorithms; 7) Math utilities: BLAS, Matrix and Vector definitions, Linear Solver methods and wrappers for other TPLs (PETSC, MKL, etc), preconditioner classes; 8) Misc: random number generator, water saturation properties, sorting algorithms.

Collins, BenjaminS.↗
DOE OSTI2017

Thermochimica

Thermochimica is a software library that determines a unique combination of phases and their compositions at thermochemical equilibrium. Thermochimica can be used for stand-alone calculations or it can be directly coupled to other codes. This release of the software does not have a graphical user interface (GUI) and it can be executed from the command line or from an Application Programming Interface (API). Also, it is not intended for thermodynamic model development or for constructing phase diagrams. The main purpose of the software is to be directly coupled with a multi-physics code to provide material properties and boundary conditions for various physical phenomena. Significant research efforts have been dedicated to enhance computational performance through advanced algorithm development, such as improved estimation techniques and non-linear solvers. Various useful parameters can be provided as output from Thermochimica, such as: determination of which phases are stable at equilibrium, the mass of solution species and phases at equilibrium, mole fractions of solution phase constituents, thermochemical activities (which are related to partial pressures for gaseous species), chemical potentials of solution species and phases, and integral Gibbs energy (referenced relative to standard state). The overall goal is to provide an open source computational tool to enhance the predictive capability of multi-physics codes without significantly impeding computational performance.

Simunovic, Srdjan↗
DOE OSTI2017

smoothG

smoothG is a collection of parallel C++ classes/functions that algebraically constructs reduced models of different resolutions from a given high-fidelity graph model. In addition, smoothG also provides efficient linear solvers for the reduced models. Other than pure graph problem, the software finds its application in subsurface flow and power grid simulations in which graph Laplacians are found

Barker, AndrewT.↗
DOE OSTI2021

EKAT v.1.0

E3SM Kokkos Application Toolkit (EKAT) is a collection of C++, Fortran, and CMake utilities for providing a single implementation of common kernels based on the Kokkos programming model. The library contains utilities for vectorization, tridiagonal linear system solvers, and linear interpolation as well as some general-purpose utilities such as testing utilities, parameter lists, representation of physical units, and additional interfaces. The goal is to provide a centralized implementation for high-performance computing structures and common utilities that reduce code duplication and streamline maintenance efforts. 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. SAND2022-1327 O

Bertagna, Luca↗
DOE OSTI2023

ReSolve

Library of GPU-resident linear solvers

Swirydowicz, Kasia↗
DOE OSTI2024

AMReX v2024

The software framework, AMReX, supports the development of block-structured adaptive mesh refinement (AMR) algorithms for solving systems of partial differential equations. AMR reduces the computational cost and memory footprint compared to a uniform mesh while preserving the essential local descriptions of different physical processes in complex multiphysics algorithms. AMR uses a hierarchical representation of the solution at multiple levels of resolution where the solution on each level is defined on the union of data containers at that resolution. These data containers, which represent the solution over a logically rectangular subregion of the domain, can contain field data defined on a mesh, Lagrangian particles or combinations of both. In addition to these basic data types, AMReX supports a multilevel embedded boundary representation of complex geometry; linear solvers for cell-centered and nodal data; asynchronous I/O in a native format readable by ParaView, VisIt and yt; and interfaces to hypre and PETSc solvers. AMReX enables applications to run on distributed memory architectures with multicore CPUs and with GPU accelerators. AMReX uses a lightweight abstraction layer that effectively hides the details of the architecture from the application. The framework currently supports CUDA, HIP and SYCL for GPU acceleration and OpenMP for multi-core CPU architectures.

Almgren, Ann↗
DOE OSTI2024

pnnl/LAP

A software framework to study, from the performance and energy perspective, the efficacy of GPU-resident parallel Conjugate Gradient (CG) linear solver with different preconditioner options, including Gauss-Seidel, Jacobi, and incomplete Cholesky. We also propose a novel GPU-based preconditioner, in which the triangular solves are approximated by an iterative process

Swirydowicz, Kasia↗
DOE OSTI2016

GridPACK™ : A Framework for Developing Power Grid Simulations on High-Performance Computing Platforms

This paper describes the GridPACK™ framework, which is designed to help power grid engineers develop modeling software capable of running on high performance computers. The framework makes extensive use of software templates to provide high level functionality while at the same time allowing developers the freedom to express whatever models and algorithms they are using. GridPACK™ contains modules for setting up distributed power grid networks, assigning buses and branches with arbitrary behaviors to the network, creating distributed matrices and vectors and using parallel linear and non-linear solvers to solve algebraic equations. It also provides mappers to create matrices and vectors based on properties of the network and functionality to support IO and to mana

Palmer, Bruce J.↗
DOE OSTI2021

Efficient exascale discretizations: High-order finite element methods

Efficient exploitation of exascale architectures requires rethinking of the numerical algorithms used in many large-scale applications. These architectures favor algorithms that expose ultra fine-grain parallelism and maximize the ratio of floating point operations to energy intensive data movement. One of the few viable approaches to achieve high efficiency in the area of PDE discretizations on unstructured grids is to use matrix-free/partially assembled high-order finite element methods, since these methods can increase the accuracy and/or lower the computational time due to reduced data motion. In this paper we provide an overview of the research and development activities in the Center for Efficient Exascale Discretizations (CEED), a co-design center in the Exascale Computing Project that is focused on the development of next-generation discretization software and algorithms to enable a wide range of finite element applications to run efficiently on future hardware. CEED is a research partnership involving more than 30 computational scientists from two US national labs and five universities, including members of the Nek5000, MFEM, MAGMA and PETSc projects. We discuss the CEED co-design activities based on targeted benchmarks, miniapps and discretization libraries and our work on performance optimizations for large-scale GPU architectures. We also provide a broad overview of research and development activities in areas such as unstructured adaptive mesh refinement algorithms, matrix-free linear solvers, high-order data visualization, and list examples of collaborations with several ECP and external applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

TwoFold: Highly accurate structure and affinity prediction for protein-ligand complexes from sequences

We describe our development of ab initio protein-ligand binding pose prediction models based on transformers and binding affinity prediction models based on the neural tangent kernel (NTK). Folding both protein and ligand, the TwoFold models achieve efficient and quality predictions matching state-of-the-art implementations while additionally reconstructing protein structures. In conclusion, solving NTK models points to a new use case for highly optimized linear solver benchmarking codes on HPC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Towards exascale for wind energy simulations

We examine large-eddy-simulation modeling approaches and computational performance of two open-source computational fluid dynamics codes for the simulation of atmospheric boundary layer flows that are of direct relevance to wind energy production. The first code, NekRS, is a high-order, unstructured-grid, spectral element code. The second code, AMR-Wind, is a second-order, block-structured, finite-volume code with adaptive mesh refinement capabilities. The objective of this study is to co-develop these codes in order to improve model fidelity and performance for each. These features will be critical for running ABL-based applications such as wind farm analysis on advanced computing architectures. To this end, we investigate the performance of NekRS and AMR-Wind on the Oak Ridge Leadership Facility supercomputers Summit, using 4 to 800 nodes (24 to 4,800 NVIDIA V100 GPUs), and Crusher, the testbed for the Frontier exascale system, using 18 to 384 Graphics Compute Dies on AMD MI250X GPUs. We compare strong- and weak-scaling capabilities, linear solver performance, and time to solution. We also identify leading inhibitors to parallel scaling.

17 WIND ENERGY↗
DOE OSTI2012

Peridigm users' guide V1.0.0

Peridigm is Sandia’s primary open-source computational peridynamics code. It is a compo nent software project, built largely upon Sandia’s Trilinos project and Sandia’s agile software components efforts. It is massively parallel, utilizes peridynamic state-based material models, Exodus/Genesis-format mesh input, Exodus-format output, and multiple material blocks. It performs explicit dynamic, implicit dynamic, and quasistatic analyses utilizing powerful nonlin ear and linear solvers.

Parks, Michael L.↗
DOE OSTI2012

Xyce TM Parallel Electronic Simulator: Users’ Guide, Version 5.3

This manual describes the use of the Xyce Parallel Electronic Simulator. Xyce has been designed as a SPICE-compatible, high-performance analog circuit simulator, and has been written to support the simulation needs of the Sandia National Laboratories electrical designers. This development has focused on improving capability over the current state-of-the-art in the following areas: ■ Capability to solve extremely large circuit problems by supporting large-scale parallel computing platforms (up to thousands of processors). Note that this includes support for most popular parallel and serial computers. ■ Improved performance for all numerical kernels (e.g., time integrator, nonlinear and linear solvers) through state-of-the-art algorithms and novel techniques. ■ Device models which are specifically tailored to meet Sandia’s needs, including some radiation-aware devices (for Sandia users only). ■ Object-oriented code design and implementation using modern coding practices that ensure that the Xyce Parallel Electronic Simulator will be maintainable and extensible far into the future. Xyce is a parallel code in the most general sense of the phrase - a message passing parallel implementation - which allows it to run efficiently on the widest possible number of computing platforms. These include serial, shared-memory and distributed-memory parallel as well as heterogeneous platforms. Careful attention has been paid to the specific nature of circuit-simulation problems to ensure that optimal parallel efficiency is achieved as the number of processors grows. The development of Xyce provides a platform for computational research and development aimed specifically at the needs of the Laboratory. With Xyce, Sandia has an “in-house” capability with which both new electrical (e.g., device model development) and algorithmic (e.g., faster time-integration methods, parallel solver algorithms) research and development can be performed. As a result, Xyce is a unique electrical simulation capability, designed to meet the unique needs of the laboratory

42 ENGINEERING↗
DOE OSTI2012

Thermochimica User Manual – v1.0

A new software library called Thermochimica has been developed that determines a unique combination of phases and their compositions at thermochemical equilibrium. The development of Thermochimica in this research is aimed at direct integration in multi-physics codes and to address several concerns with using commercially available software, including: licensing entanglements associated with code distribution, access to the source code, convenient incorporation into other codes with quality assurance considerations, and computational performance. In particular, significant research efforts have been dedicated to enhance computational performance through advanced algorithm development, such as improved estimation techniques and non-linear solvers. The overall goal of this undertaking is to provide an open source computational tool to enhance the predictive capability of multiphysics codes without significantly impeding computational performance. The purpose of this document is to describe the design of Thermochimica and the basic use of the software library. A brief background to computational thermodynamics and the conditions for thermodynamic equilibrium is given in §2, details of the code development is discussed in §3, details of building and compiling Thermochimica is given in §4, specific programming details for each subroutine in the library is given in the Appendix. The open license for Thermochimica is provided with the source code. As is always the case, software quality assurance (SQA) is an extremely important subject in software development. The importance of this warrants an independent document dedicated to SQA, which has been developed in parallel to this document. The subject of thermodynamic model validation is also of extreme importance in scientific computing and must be given careful attention. To be clear, this document is concerned with the development and use of a general thermodynamic solver and the validation of any models should be included in the discussion of the development of a thermodynamic model that is specific to a particular system.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Status Report on NEAMS System Analysis Module Development

Under the Reactor Product Line (RPL) of DOE-NE’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, an advanced SFR System Analysis Module (SAM) is being developed at Argonne National Laboratory. The goal of the SAM development is to provide fast-running, improved-fidelity, whole-plant transient analyses capabilities. SAM utilizes an object-oriented application framework MOOSE), and its underlying meshing and finite-element library libMesh, as well as linear and non-linear solvers PETSc, to leverage modern advanced software environments and numerical methods. It also incorporates advances in physical and empirical models and seeks closure models based on information from high-fidelity simulations and experiments. This report provides an update on the SAM development, and summarizes the activities performed in FY15 and the first quarter of FY16. The tasks include: (1) implement the support of 2nd-order finite elements in SAM components for improved accuracy and computational efficiency; (2) improve the conjugate heat transfer modeling and develop pseudo 3-D full-core reactor heat transfer capabilities; (3) perform verification and validation tests as well as demonstration simulations; (4) develop the coupling requirements for SAS4A/SASSYS-1 and SAM integration.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗