Architecture of Advanced Numerical Analysis Systems: Designing a Scientific Computing System using OCaml
- Length: 485 pages
- Edition: 1
- Language: English
- Publisher: Apress
- Publication Date: 2022-12-27
- ISBN-10: 1484288521
- ISBN-13: 9781484288528
- Sales Rank: #0 (See Top 100 Books)
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.
Cover Front Matter 1. Introduction 2. Core Optimizations 3. Algorithmic Differentiation 4. Mathematical Optimization 5. Deep Neural Networks 6. Computation Graph 7. Performance Accelerators 8. Compiler Backends 9. Composition and Deployment 10. Distributed Computing 11. Testing Framework Back Matter
Donate to keep this site alive
How to download source code?
1. Go to: https://github.com/Apress
2. In the Find a repository… box, search the book title: Architecture of Advanced Numerical Analysis Systems: Designing a Scientific Computing System using OCaml
, sometime you may not get the results, please search the main title.
3. Click the book title in the search results.
3. Click Code to download.
1. Disable the AdBlock plugin. Otherwise, you may not get any links.
2. Solve the CAPTCHA.
3. Click download link.
4. Lead to download server to download.