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Julia High Performance Optimizations Distributed Computing Multithreading And Gpu Programming With Julia 10 And Beyond Second Edition 2nd Edition Avik Sengupta Foreword By Alan Edelman

  • SKU: BELL-11819420
Julia High Performance Optimizations Distributed Computing Multithreading And Gpu Programming With Julia 10 And Beyond Second Edition 2nd Edition Avik Sengupta Foreword By Alan Edelman
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Julia High Performance Optimizations Distributed Computing Multithreading And Gpu Programming With Julia 10 And Beyond Second Edition 2nd Edition Avik Sengupta Foreword By Alan Edelman instant download after payment.

Publisher: Packt Publishing
File Extension: PDF
File size: 4.04 MB
Pages: 210
Author: Avik Sengupta; (foreword by) Alan Edelman
ISBN: 9781788292306, 9781788298117, 1788292308, 178829811X
Language: English
Year: 2019
Edition: 2

Product desciption

Julia High Performance Optimizations Distributed Computing Multithreading And Gpu Programming With Julia 10 And Beyond Second Edition 2nd Edition Avik Sengupta Foreword By Alan Edelman by Avik Sengupta; (foreword By) Alan Edelman 9781788292306, 9781788298117, 1788292308, 178829811X instant download after payment.

Julia is a high-level, high-performance dynamic programming language for numerical computing. If you want to understand how to avoid bottlenecks and design your programs for the highest possible performance, then this book is for you. The book starts with how Julia uses type information to achieve its performance goals, and how to use multiple dispatches to help the compiler emit high-performance machine code. After that, you will learn how to analyze Julia programs and identify issues with time and memory consumption. We teach you how to use Julia's typing facilities accurately to write high-performance code and describe how the Julia compiler uses type information to create fast machine code. Moving ahead, you'll master design constraints and learn how to use the power of the GPU in your Julia code and compile Julia code directly to the GPU. Then, you'll learn how tasks and asynchronous IO help you create responsive programs and how to use shared memory multithreading in Julia. Toward the end, you will get a flavor of Julia's distributed computing capabilities and how to run Julia programs on a large distributed cluster. By the end of this book, you will have the ability to build large-scale, high-performance Julia applications, design systems with a focus on speed, and improve the performance of existing programs.

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