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Open access
Title
Architecture of advanced numerical analysis systems : designing a scientific computing system using OCaml / Liang Wang, Jianxin Zhao.
ISBN
9781484288535 (electronic bk.)
148428853X (electronic bk.)
1484288521
9781484288528
Published
[Berkeley, CA] : Apress Open, [2023]
Language
English
Description
1 online resource
Item Number
10.1007/978-1-4842-8853-5 doi
Call Number
QA76.73.O117 W36 2023
Dewey Decimal Classification
005.117
Summary
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. You will: 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.
Bibliography, etc. Note
Includes bibliographical references and index.
Access Note
Open access.
Digital File Characteristics
text file PDF
Source of Description
Description based on online resource; title from digital title page (viewed on January 19, 2023).
Available in Other Form
Print version: 9781484288528
Chapter 1: Introduction.-Chapter 2: Core Optimization
Chapter 3: Algorithm Differentiation
Chapter 4: Mathematical Optimization
Chapter 5: Deep Neural Networks
Chapter 6: Computation Graph
Chapter 7: Performance Accelerators
Chapter 8: Compiler Backends
Chapter 9: Composition and Deployment
Chapter 10: Distributed Computing
Chapter 11: Testing Framework
Appendix A: Basic Analytics Examples
Appendix B: System Conventions
Appendix C: Metric Systems and Constants
Appendix D: AlgoDiff Module
Appendix E: Neural Network Module
Appendix F: Actor System for Distributed Computing
Bibliography.