Software Development Practices Apis for Solver and UDF
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Arxiv:1911.09220V2 [Cs.MS] 13 Jul 2020
MFEM: A MODULAR FINITE ELEMENT METHODS LIBRARY ROBERT ANDERSON, JULIAN ANDREJ, ANDREW BARKER, JAMIE BRAMWELL, JEAN- SYLVAIN CAMIER, JAKUB CERVENY, VESELIN DOBREV, YOHANN DUDOUIT, AARON FISHER, TZANIO KOLEV, WILL PAZNER, MARK STOWELL, VLADIMIR TOMOV Lawrence Livermore National Laboratory, Livermore, USA IDO AKKERMAN Delft University of Technology, Netherlands JOHANN DAHM IBM Research { Almaden, Almaden, USA DAVID MEDINA Occalytics, LLC, Houston, USA STEFANO ZAMPINI King Abdullah University of Science and Technology, Thuwal, Saudi Arabia Abstract. MFEM is an open-source, lightweight, flexible and scalable C++ library for modular finite element methods that features arbitrary high-order finite element meshes and spaces, support for a wide variety of dis- cretization approaches and emphasis on usability, portability, and high-performance computing efficiency. MFEM's goal is to provide application scientists with access to cutting-edge algorithms for high-order finite element mesh- ing, discretizations and linear solvers, while enabling researchers to quickly and easily develop and test new algorithms in very general, fully unstructured, high-order, parallel and GPU-accelerated settings. In this paper we describe the underlying algorithms and finite element abstractions provided by MFEM, discuss the software implementation, and illustrate various applications of the library. arXiv:1911.09220v2 [cs.MS] 13 Jul 2020 1. Introduction The Finite Element Method (FEM) is a powerful discretization technique that uses general unstructured grids to approximate the solutions of many partial differential equations (PDEs). It has been exhaustively studied, both theoretically and in practice, in the past several decades [1, 2, 3, 4, 5, 6, 7, 8]. MFEM is an open-source, lightweight, modular and scalable software library for finite elements, featuring arbitrary high-order finite element meshes and spaces, support for a wide variety of discretization approaches and emphasis on usability, portability, and high-performance computing (HPC) efficiency [9]. -
C/C++ Programming with Qt 5.12.6 and Opencv 4.2.0
C/C++ programming with Qt 5.12.6 and OpenCV 4.2.0 Preparation of the computer • Download http://download.qt.io/archive/qt/5.12/5.12.6/qt-opensource-windows- x86-5.12.6.exe and http://www.ensta-bretagne.fr/lebars/Share/OpenCV4.2.0.zip (contains OpenCV with extra modules built for Visual Studio 2015, 2017, 2019, MinGW Qt 5.12.6 x86, MinGW 8 x64), run Qt installer and select Qt\Qt 5.12.6\MinGW 7.3.0 32 bit and Qt\Tools\MinGW 7.3.0 32 bit options and extract OpenCV4.2.0.zip in C:\ (check that the extraction did not create an additional parent folder (we need to get only C:\OpenCV4.2.0\ instead of C:\OpenCV4.2.0\OpenCV4.2.0\), right-click and choose Run as administrator if needed). For Linux or macOS, additional/different steps might be necessary depending on the specific versions (and the provided .pro might need to be tweaked), see https://www.ensta-bretagne.fr/lebars/Share/setup_opencv_Ubuntu.pdf ; corresponding OpenCV sources : https://github.com/opencv/opencv/archive/4.2.0.zip and https://github.com/opencv/opencv_contrib/archive/4.2.0.zip ; Qt Linux 64 bit : https://download.qt.io/archive/qt/5.12/5.12.6/qt-opensource-linux-x64-5.12.6.run (for Ubuntu you can try sudo apt install qtcreator qt5-default build-essential but the version will probably not be the same); Qt macOS : https://download.qt.io/archive/qt/5.12/5.12.6/qt-opensource-mac-x64-5.12.6.dmg . -
Accelerating the LOBPCG Method on Gpus Using a Blocked Sparse Matrix Vector Product
Accelerating the LOBPCG method on GPUs using a blocked Sparse Matrix Vector Product Hartwig Anzt and Stanimire Tomov and Jack Dongarra Innovative Computing Lab University of Tennessee Knoxville, USA Email: [email protected], [email protected], [email protected] Abstract— the computing power of today’s supercomputers, often accel- erated by coprocessors like graphics processing units (GPUs), This paper presents a heterogeneous CPU-GPU algorithm design and optimized implementation for an entire sparse iter- becomes challenging. ative eigensolver – the Locally Optimal Block Preconditioned Conjugate Gradient (LOBPCG) – starting from low-level GPU While there exist numerous efforts to adapt iterative lin- data structures and kernels to the higher-level algorithmic choices ear solvers like Krylov subspace methods to coprocessor and overall heterogeneous design. Most notably, the eigensolver technology, sparse eigensolvers have so far remained out- leverages the high-performance of a new GPU kernel developed side the main focus. A possible explanation is that many for the simultaneous multiplication of a sparse matrix and a of those combine sparse and dense linear algebra routines, set of vectors (SpMM). This is a building block that serves which makes porting them to accelerators more difficult. Aside as a backbone for not only block-Krylov, but also for other from the power method, algorithms based on the Krylov methods relying on blocking for acceleration in general. The subspace idea are among the most commonly used general heterogeneous LOBPCG developed here reveals the potential of eigensolvers [1]. When targeting symmetric positive definite this type of eigensolver by highly optimizing all of its components, eigenvalue problems, the recently developed Locally Optimal and can be viewed as a benchmark for other SpMM-dependent applications. -
Eclipse Webinar
Scientific Software Development with Eclipse A Best Practices for HPC Developers Webinar Gregory R. Watson ORNL is managed by UT-Battelle for the US Department of Energy Contents • Downloading and Installing Eclipse • C/C++ Development Features • Fortran Development Features • Real-life Development Scenarios – Local development – Using Git for remote development – Using synchronized projects for remote development • Features for Utilizing HPC Facilities 2 Best Practices for HPC Software Developers webinar series What is Eclipse? • An integrated development environment (IDE) • A platform for developing tools and applications • An ecosystem for collaborative software development 3 Best Practices for HPC Software Developers webinar series Getting Started 4 Best Practices for HPC Software Developers webinar series Downloading and Installing Eclipse • Eclipse comes in a variety of packages – Any package can be used as a starting point – May require additional components installed • Packages that are best for scientific computing: – Eclipse for Parallel Application Developers – Eclipse IDE for C/C++ Developers • Main download site – https://www.eclipse.org/downloads 5 Best Practices for HPC Software Developers webinar series Eclipse IDE for C/C++ Developers • C/C++ development tools • Git Integration • Linux tools – Libhover – Gcov – RPM – Valgrind • Tracecompass 6 Best Practices for HPC Software Developers webinar series Eclipse for Parallel Application Developers • Eclipse IDE for C/C++ Developers, plus: – Synchronized projects – Fortran development -
MFEM: a Modular Finite Element Methods Library
MFEM: A Modular Finite Element Methods Library Robert Anderson1, Andrew Barker1, Jamie Bramwell1, Jakub Cerveny2, Johann Dahm3, Veselin Dobrev1,YohannDudouit1, Aaron Fisher1,TzanioKolev1,MarkStowell1,and Vladimir Tomov1 1Lawrence Livermore National Laboratory 2University of West Bohemia 3IBM Research July 2, 2018 Abstract MFEM is a free, lightweight, flexible and scalable C++ library for modular finite element methods that features arbitrary high-order finite element meshes and spaces, support for a wide variety of discretization approaches and emphasis on usability, portability, and high-performance computing efficiency. Its mission is to provide application scientists with access to cutting-edge algorithms for high-order finite element meshing, discretizations and linear solvers. MFEM also enables researchers to quickly and easily develop and test new algorithms in very general, fully unstructured, high-order, parallel settings. In this paper we describe the underlying algorithms and finite element abstractions provided by MFEM, discuss the software implementation, and illustrate various applications of the library. Contents 1 Introduction 3 2 Overview of the Finite Element Method 4 3Meshes 9 3.1 Conforming Meshes . 10 3.2 Non-Conforming Meshes . 11 3.3 NURBS Meshes . 12 3.4 Parallel Meshes . 12 3.5 Supported Input and Output Formats . 13 1 4 Finite Element Spaces 13 4.1 FiniteElements....................................... 14 4.2 DiscretedeRhamComplex ................................ 16 4.3 High-OrderSpaces ..................................... 17 4.4 Visualization . 18 5 Finite Element Operators 18 5.1 DiscretizationMethods................................... 18 5.2 FiniteElementLinearSystems . 19 5.3 Operator Decomposition . 23 5.4 High-Order Partial Assembly . 25 6 High-Performance Computing 27 6.1 Parallel Meshes, Spaces, and Operators . 27 6.2 Scalable Linear Solvers . -
XAMG: a Library for Solving Linear Systems with Multiple Right-Hand
XAMG: A library for solving linear systems with multiple right-hand side vectors B. Krasnopolsky∗, A. Medvedev∗∗ Institute of Mechanics, Lomonosov Moscow State University, 119192 Moscow, Michurinsky ave. 1, Russia Abstract This paper presents the XAMG library for solving large sparse systems of linear algebraic equations with multiple right-hand side vectors. The library specializes but is not limited to the solution of linear systems obtained from the discretization of elliptic differential equations. A corresponding set of numerical methods includes Krylov subspace, algebraic multigrid, Jacobi, Gauss-Seidel, and Chebyshev iterative methods. The parallelization is im- plemented with MPI+POSIX shared memory hybrid programming model, which introduces a three-level hierarchical decomposition using the corre- sponding per-level synchronization and communication primitives. The code contains a number of optimizations, including the multilevel data segmen- tation, compression of indices, mixed-precision floating-point calculations, arXiv:2103.07329v1 [cs.MS] 12 Mar 2021 vector status flags, and others. The XAMG library uses the program code of the well-known hypre library to construct the multigrid matrix hierar- chy. The XAMG’s own implementation for the solve phase of the iterative methods provides up to a twofold speedup compared to hypre for the tests ∗E-mail address: [email protected] ∗∗E-mail address: [email protected] Preprint submitted to Elsevier March 15, 2021 performed. Additionally, XAMG provides extended functionality to solve systems with multiple right-hand side vectors. Keywords: systems of linear algebraic equations, Krylov subspace iterative methods, algebraic multigrid method, multiple right-hand sides, hybrid programming model, MPI+POSIX shared memory Nr. -
Jedit: Isabelle/Jedit
jEdit ∀ = Isabelle α λ β → Isabelle/jEdit Makarius Wenzel 5 December 2013 Abstract Isabelle/jEdit is a fully-featured Prover IDE, based on Isabelle/Scala and the jEdit text editor. This document provides an overview of general principles and its main IDE functionality. i Isabelle's user interface is no advance over LCF's, which is widely condemned as \user-unfriendly": hard to use, bewildering to begin- ners. Hence the interest in proof editors, where a proof can be con- structed and modified rule-by-rule using windows, mouse, and menus. But Edinburgh LCF was invented because real proofs require millions of inferences. Sophisticated tools | rules, tactics and tacticals, the language ML, the logics themselves | are hard to learn, yet they are essential. We may demand a mouse, but we need better education and training. Lawrence C. Paulson, \Isabelle: The Next 700 Theorem Provers" Acknowledgements Research and implementation of concepts around PIDE and Isabelle/jEdit has started around 2008 and was kindly supported by: • TU M¨unchen http://www.in.tum.de • BMBF http://www.bmbf.de • Universit´eParis-Sud http://www.u-psud.fr • Digiteo http://www.digiteo.fr • ANR http://www.agence-nationale-recherche.fr Contents 1 Introduction1 1.1 Concepts and terminology....................1 1.2 The Isabelle/jEdit Prover IDE..................2 1.2.1 Documentation......................3 1.2.2 Plugins...........................4 1.2.3 Options..........................4 1.2.4 Keymaps..........................5 1.2.5 Look-and-feel.......................5 2 Prover IDE functionality7 2.1 File-system access.........................7 2.2 Text buffers and theories....................8 2.3 Prover output..........................9 2.4 Tooltips and hyperlinks.................... -
The WAF Build System
The WAF build system The WAF build system Sebastian Jeltsch Electronic Vision(s) Kirchhoff Institute for Physics Ruprecht-Karls-Universität Heidelberg 31. August 2010 Sebastian Jeltsch The WAF build system 31. August 2010 1 / 19 The WAF build system Introduction WorkBuildflow Sebastian Jeltsch The WAF build system 31. August 2010 2 / 19 make = major pain What we expect from our build system: flexibility integration of existing workflows access to well established libraries extensibility power usability The WAF build system Introduction WorkBuildflow For us: low-level code many many layers Sebastian Jeltsch The WAF build system 31. August 2010 3 / 19 What we expect from our build system: flexibility integration of existing workflows access to well established libraries extensibility power usability The WAF build system Introduction WorkBuildflow For us: low-level code many many layers make = major pain Sebastian Jeltsch The WAF build system 31. August 2010 3 / 19 The WAF build system Introduction WorkBuildflow For us: low-level code many many layers make = major pain What we expect from our build system: flexibility integration of existing workflows access to well established libraries extensibility power usability Sebastian Jeltsch The WAF build system 31. August 2010 3 / 19 The WAF build system Introduction Autotools (GNU Build System) GNU Build System + few dependencies on user side (shell scripts) developer autoscan ed + generates standard make files + widely used configure.ac Makefile.am – platform dependent (bash aclocal autoheader automake scripts) aclocal.m4 config.h.in Makefile.in – autoconf-configure is slow autoconf Often: tconfigure >> tmake. – another scripting language configure Makefile make user Sebastian Jeltsch The WAF build system 31. -
Kdesrc-Build Script Manual
kdesrc-build Script Manual Michael Pyne Carlos Woelz kdesrc-build Script Manual 2 Contents 1 Introduction 8 1.1 A brief introduction to kdesrc-build . .8 1.1.1 What is kdesrc-build? . .8 1.1.2 kdesrc-build operation ‘in a nutshell’ . .8 1.2 Documentation Overview . .9 2 Getting Started 10 2.1 Preparing the System to Build KDE . 10 2.1.1 Setup a new user account . 10 2.1.2 Ensure your system is ready to build KDE software . 10 2.1.3 Setup kdesrc-build . 12 2.1.3.1 Install kdesrc-build . 12 2.1.3.2 Prepare the configuration file . 12 2.1.3.2.1 Manual setup of configuration file . 12 2.2 Setting the Configuration Data . 13 2.3 Using the kdesrc-build script . 14 2.3.1 Loading project metadata . 14 2.3.2 Previewing what will happen when kdesrc-build runs . 14 2.3.3 Resolving build failures . 15 2.4 Building specific modules . 16 2.5 Setting the Environment to Run Your KDEPlasma Desktop . 17 2.5.1 Automatically installing a login driver . 18 2.5.1.1 Adding xsession support for distributions . 18 2.5.1.2 Manually adding support for xsession . 18 2.5.2 Setting up the environment manually . 19 2.6 Module Organization and selection . 19 2.6.1 KDE Software Organization . 19 2.6.2 Selecting modules to build . 19 2.6.3 Module Sets . 20 2.6.3.1 The basic module set concept . 20 2.6.3.2 Special Support for KDE module sets . -
1. Install Homebrew 2. Install Cmake 3. Build and Run the Opengl Program
NYU Tandon School of Engineering CS6533/CS4533 Zebin Xu [email protected] Compiling OpenGL Programs on macOS or Linux using CMake This tutorial explains how to compile OpenGL programs on macOS using CMake – a cross-platform tool for managing the build process of software using a compiler- independent method. On macOS, OpenGL and GLUT are preinstalled; GLEW is not needed as we will use the core profile of OpenGL 3.2 later when we use shaders; Xcode is not required unless you prefer programming in an IDE. At the end we also discuss how to compile on Linux. Contents/Steps: 1. Install Homebrew 2. Install CMake via Homebrew 3. Build and run the OpenGL program 3.1 Build via the command line by generating Unix Makefiles (without Xcode) 3.2 Build via the Xcode IDE by generating an Xcode project (so that you can write your code in Xcode if you have it installed) 4. Compilation on Linux 5. Notes 1. Install Homebrew Homebrew is a pacKage manager for macOS. If you have installed Homebrew before, sKip this step. To install Homebrew, simply paste the command from https://brew.sh into your terminal and run. Once you have installed Homebrew, type “brew” in your terminal to checK if it’s installed. We will use Homebrew to install CMake. 2. Install CMaKe I strongly suggest installing CMake via Homebrew as it will also picK up any related missing pacKages during installation (such as installing a needed command line tool for Xcode even if you don’t have Xcode). If you have installed CMake, just sKip this step. -
Set-Up Environment
Set-up Environment Note: While this instruction utilises Windows to demonstrate the installation process, it does apply to other operating systems including Mac OS and Linux. Step 1. Install MinGW on Windows (skip this step if you use Mac OS or Linux) FYI: “MinGW” is a Windows implementation of C compiler that will convert your C source code into executable files. For Mac OS and Linux, C compilers should have already been installed. If you have not already installed “MinGW” for Windows, then use the other document <Install MinGW> on the same LMS page to install it. “MinGW” needs to be installed (or is not installed correctly) if you get the following error message: 'gcc' is not recognized as an internal or external command, operable program or batch file. Step 2.1 Check if you have Java SE 11 (JDK) installed FYI: You are not required to know what “JDK” stands for and what it means. Just bear in mind that it is a prerequisite to running jEdit 5.6.0. How do I know if I have Java installed? Windows: Select from the “Control Panel” => “Programs and Features” and check if you can find an entry called “Java(TM) SE Development Kit 11.0.10 (64-bit)” (or later). If you see such an entry, everything is fine and you can go to Step 3. Otherwise, you do not have Java installed and need to go to Step 2.2 Mac OS / Linux: Open “Terminal” and type “java -version”. If you can see the line: java version “11.0.10” or later, everything is fine and you can go to Step 3. -
Course 2: «Open Source Software (OSS) Engineering Data»
Course 2: «Open Source Software (OSS) Engineering Data». 1st Day: Metrics and Tools for Software Engineering in Open Source Software 1. Open Software / Hardware Technologies: Introduction to Open Source Software and related technologies. 2. Software Engineering FLOSS: Free Libre Open Source Software in Software Engineering. 3. Metrics for Open Source Software: product and project metrics and related tooling. 2nd Day: Research based on Open Source Software Data 4. Facilitating Metric for White-Box Reuse: we will discuss a metric derived from the analysis of Open Source Project which facilitates the white-box reuse (reuse based on the source code analysis). 5. Extracting components from Open-Source: The Component Adaptation Environment Approach (COPE): we will discuss the results of the OPEN-SME EU Research Project and in particular the COPE tool for extracting reusable components from Open Source Software. 6. Software Engineering Research based on Open Source Software Data: Data, A recent example: we will discuss a recent study of open source repository mailing lists for deriving implications for the evolution of an open source project. 7. Improving Component Coupling Information with Dynamic Profiling: we will discuss how dynamic profiling of an open source program can contribute towards its comprehension. In various points during the lectures students will be asked to carry out activities. Open Software / Hardware Technologies Ioannis Stamelos, Professor Nikolaos Konofaos, Associate Professor School of Informatics Aristotle University of Thessaloniki George Kakarontzas, Assistant Professor University of Thessaly 2018-2019 1 F/OSS - FLOSS Definition ● The traditional SW development model asks for a “closed member” team that develops proprietary source code.