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Ocaml Scientific Computing


Ocaml Scientific Computing
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Ocaml Scientific Computing


Ocaml Scientific Computing
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Author : Liang Wang
language : en
Publisher: Springer Nature
Release Date : 2022-05-26

Ocaml Scientific Computing written by Liang Wang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-26 with Computers categories.


This book is about the harmonious synthesis of functional programming and numerical computation. It shows how the expressiveness of OCaml allows for fast and safe development of data science applications. Step by step, the authors build up to use cases drawn from many areas of Data Science, Machine Learning, and AI, and then delve into how to deploy at scale, using parallel, distributed, and accelerated frameworks to gain all the advantages of cloud computing environments. To this end, the book is divided into three parts, each focusing on a different area. Part I begins by introducing how basic numerical techniques are performed in OCaml, including classical mathematical topics (interpolation and quadrature), statistics, and linear algebra. It moves on from using only scalar values to multi-dimensional arrays, introducing the tensor and Ndarray, core data types in any numerical computing system. It concludes with two more classical numerical computing topics, the solution of Ordinary Differential Equations (ODEs) and Signal Processing, as well as introducing the visualization module we use throughout this book. Part II is dedicated to advanced optimization techniques that are core to most current popular data science fields. We do not focus only on applications but also on the basic building blocks, starting with Algorithmic Differentiation, the most crucial building block that in turn enables Deep Neural Networks. We follow this with chapters on Optimization and Regression, also used in building Deep Neural Networks. We then introduce Deep Neural Networks as well as topic modelling in Natural Language Processing (NLP), two advanced and currently very active fields in both industry and academia. Part III collects a range of case studies demonstrating how you can build a complete numerical application quickly from scratch using Owl. The cases presented include computer vision and recommender systems. This book aims at anyone with a basic knowledge of functional programming and a desire to explore the world of scientific computing, whether to generally explore the field in the round, to build applications for particular topics, or to deep-dive into how numerical systems are constructed. It does not assume strict ordering in reading – readers can simply jump to the topic that interests them most.



Architecture Of Advanced Numerical Analysis Systems


Architecture Of Advanced Numerical Analysis Systems
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Author : Liang Wang
language : en
Publisher: Apress
Release Date : 2022-12-27

Architecture Of Advanced Numerical Analysis Systems written by Liang Wang and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-27 with Computers categories.


This unique open access book applies the functional OCaml programming language to numerical or computational weighted data science, engineering, and scientific applications. This book is based on the authors' first-hand experience building and maintaining Owl, an OCaml-based numerical computing library. You'll first learn the various components in a modern numerical computation library. Then, you will learn how these components are designed and built up and how to optimize their performance. After reading and using this book, you'll have the knowledge required to design and build real-world complex systems that effectively leverage the advantages of the OCaml functional programming language. What You Will Learn Optimize core operations based on N-dimensional arrays Design and implement an industry-level algorithmic differentiation module Implement mathematical optimization, regression, and deep neural network functionalities based on algorithmic differentiation Design and optimize a computation graph module, and understand the benefits it brings to the numerical computing library Accommodate the growing number of hardware accelerators (e.g. GPU, TPU) and execution backends (e.g. web browser, unikernel) of numerical computation Use the Zoo system for efficient scripting, code sharing, service deployment, and composition Design and implement a distributed computing engine to work with a numerical computing library, providing convenient APIs and high performance Who This Book Is For Those with prior programming experience, especially with the OCaml programming language, or with scientific computing experience who may be new to OCaml. Most importantly, it is for those who are eager to understand not only how to use something, but also how it is built up.



Architecture Of Advanced Numerical Analysis Systems


Architecture Of Advanced Numerical Analysis Systems
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Author : LIANG. ZHAO WANG (JIANXIN.)
language : en
Publisher:
Release Date : 2023

Architecture Of Advanced Numerical Analysis Systems written by LIANG. ZHAO WANG (JIANXIN.) and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with categories.




Scientific Computing With Case Studies


Scientific Computing With Case Studies
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Author : Dianne P. O'Leary
language : en
Publisher: SIAM
Release Date : 2009-01-01

Scientific Computing With Case Studies written by Dianne P. O'Leary and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-01-01 with Mathematics categories.


This book is a practical guide to the numerical solution of linear and nonlinear equations, differential equations, optimization problems, and eigenvalue problems. It treats standard problems and introduces important variants such as sparse systems, differential-algebraic equations, constrained optimization, Monte Carlo simulations, and parametric studies. Stability and error analysis are emphasized, and the Matlab algorithms are grounded in sound principles of software design and understanding of machine arithmetic and memory management. Nineteen case studies provide experience in mathematical modeling and algorithm design, motivated by problems in physics, engineering, epidemiology, chemistry, and biology. The topics included go well beyond the standard first-course syllabus, introducing important problems such as differential-algebraic equations and conic optimization problems, and important solution techniques such as continuation methods. The case studies cover a wide variety of fascinating applications, from modeling the spread of an epidemic to determining truss configurations.



A First Course In Scientific Computing


A First Course In Scientific Computing
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Author : Rubin Landau
language : en
Publisher: Princeton University Press
Release Date : 2011-10-30

A First Course In Scientific Computing written by Rubin Landau and has been published by Princeton University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-10-30 with Computers categories.


This book offers a new approach to introductory scientific computing. It aims to make students comfortable using computers to do science, to provide them with the computational tools and knowledge they need throughout their college careers and into their professional careers, and to show how all the pieces can work together. Rubin Landau introduces the requisite mathematics and computer science in the course of realistic problems, from energy use to the building of skyscrapers to projectile motion with drag. He is attentive to how each discipline uses its own language to describe the same concepts and how computations are concrete instances of the abstract. Landau covers the basics of computation, numerical analysis, and programming from a computational science perspective. The first part of the printed book uses the problem-solving environment Maple as its context, with the same material covered on the accompanying CD as both Maple and Mathematica programs; the second part uses the compiled language Java, with equivalent materials in Fortran90 on the CD; and the final part presents an introduction to LaTeX replete with sample files. Providing the essentials of computing, with practical examples, A First Course in Scientific Computing adheres to the principle that science and engineering students learn computation best while sitting in front of a computer, book in hand, in trial-and-error mode. Not only is it an invaluable learning text and an essential reference for students of mathematics, engineering, physics, and other sciences, but it is also a consummate model for future textbooks in computational science and engineering courses. A broad spectrum of computing tools and examples that can be used throughout an academic career Practical computing aimed at solving realistic problems Both symbolic and numerical computations A multidisciplinary approach: science + math + computer science Maple and Java in the book itself; Mathematica, Fortran90, Maple and Java on the accompanying CD in an interactive workbook format



Introduction To Scientific Computing


Introduction To Scientific Computing
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Author : Brigitte Lucquin
language : en
Publisher: John Wiley & Sons
Release Date : 1998

Introduction To Scientific Computing written by Brigitte Lucquin and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with Differential equations, Partial categories.


This volume addresses the methods for solving partial differential equations (PDE) systems. The reader should learn how to write computer programs for the numerical analysis of practical engineering problems. Illustrated by examples, it starts by the definition of a programming environment for the solving of PDE systems by the finite element method. Programming the model problem by a finite element method is then addressed in detail. General elliptic problems and evolution problems are then dealt with. Finally, complements on numerical methods, algorithms for parallel computing and multiprocessor computers are presented.



Modern Software Tools For Scientific Computing


Modern Software Tools For Scientific Computing
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Author : E. Arge
language : en
Publisher: Springer Science & Business Media
Release Date : 1997-04

Modern Software Tools For Scientific Computing written by E. Arge and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997-04 with Computers categories.


The purpose of this book is to survey some recent advances in the development of software tools for scientific computing. This book presents 17 carefully selected and refereed chapters originally presented at the SciTools '96 Workshop in Oslo, Norway. The chapters emphasize the design of large software codes, computational efficiency, object-oriented programming in scientific computing, reliability of numerical software, and parallel computing.



An Introduction To High Performance Scientific Computing


An Introduction To High Performance Scientific Computing
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Author : Lloyd Dudley Fosdick
language : en
Publisher: MIT Press
Release Date : 1996

An Introduction To High Performance Scientific Computing written by Lloyd Dudley Fosdick and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with Computers categories.


Designed for undergraduates, An Introduction to High-Performance Scientific Computing assumes a basic knowledge of numerical computation and proficiency in Fortran or C programming and can be used in any science, computer science, applied mathematics, or engineering department or by practicing scientists and engineers, especially those associated with one of the national laboratories or supercomputer centers. This text evolved from a new curriculum in scientific computing that was developed to teach undergraduate science and engineering majors how to use high-performance computing systems (supercomputers) in scientific and engineering applications. Designed for undergraduates, An Introduction to High-Performance Scientific Computing assumes a basic knowledge of numerical computation and proficiency in Fortran or C programming and can be used in any science, computer science, applied mathematics, or engineering department or by practicing scientists and engineers, especially those associated with one of the national laboratories or supercomputer centers. The authors begin with a survey of scientific computing and then provide a review of background (numerical analysis, IEEE arithmetic, Unix, Fortran) and tools (elements of MATLAB, IDL, AVS). Next, full coverage is given to scientific visualization and to the architectures (scientific workstations and vector and parallel supercomputers) and performance evaluation needed to solve large-scale problems. The concluding section on applications includes three problems (molecular dynamics, advection, and computerized tomography) that illustrate the challenge of solving problems on a variety of computer architectures as well as the suitability of a particular architecture to solving a particular problem. Finally, since this can only be a hands-on course with extensive programming and experimentation with a variety of architectures and programming paradigms, the authors have provided a laboratory manual and supporting software via anonymous ftp. Scientific and Engineering Computation series



Introduction To Scientific And Technical Computing


Introduction To Scientific And Technical Computing
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Author : Frank T. Willmore
language : en
Publisher: CRC Press
Release Date : 2016-08-19

Introduction To Scientific And Technical Computing written by Frank T. Willmore and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-19 with Computers categories.


Created to help scientists and engineers write computer code, this practical book addresses the important tools and techniques that are necessary for scientific computing, but which are not yet commonplace in science and engineering curricula. This book contains chapters summarizing the most important topics that computational researchers need to know about. It leverages the viewpoints of passionate experts involved with scientific computing courses around the globe and aims to be a starting point for new computational scientists and a reference for the experienced. Each contributed chapter focuses on a specific tool or skill, providing the content needed to provide a working knowledge of the topic in about one day. While many individual books on specific computing topics exist, none is explicitly focused on getting technical professionals and students up and running immediately across a variety of computational areas.



Introduction To High Performance Scientific Computing


Introduction To High Performance Scientific Computing
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Author : David L. Chopp
language : en
Publisher: SIAM
Release Date : 2019-03-01

Introduction To High Performance Scientific Computing written by David L. Chopp and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-01 with Mathematics categories.


Based on a course developed by the author, Introduction to High Performance Scientific Computing introduces methods for adding parallelism to numerical methods for solving differential equations. It contains exercises and programming projects that facilitate learning as well as examples and discussions based on the C programming language, with additional comments for those already familiar with C++. The text provides an overview of concepts and algorithmic techniques for modern scientific computing and is divided into six self-contained parts that can be assembled in any order to create an introductory course using available computer hardware. Part I introduces the C programming language for those not already familiar with programming in a compiled language. Part II describes parallelism on shared memory architectures using OpenMP. Part III details parallelism on computer clusters using MPI for coordinating a computation. Part IV demonstrates the use of graphical programming units (GPUs) to solve problems using the CUDA language for NVIDIA graphics cards. Part V addresses programming on GPUs for non-NVIDIA graphics cards using the OpenCL framework. Finally, Part VI contains a brief discussion of numerical methods and applications, giving the reader an opportunity to test the methods on typical computing problems.