This chapter has provided an introductory look at the parallel computing facilities incorporated into the Julia language. While we haven't covered much detail in this chapter, you have hopefully seen how easy it is to get started with distributed computation in Julia. We hope you will be able to apply these basic principles to your problem in order to create scalable distributed solutions.
Julia 1.0 High Performance - Second Edition
By :
Julia 1.0 High Performance - Second Edition
By:
Overview of this book
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.
Table of Contents (19 chapters)
Title Page
Copyright and Credits
Dedication
About Packt
Foreword
Contributors
Preface
Free Chapter
Julia is Fast
Analyzing Performance
Types, Type Inference, and Stability
Making Fast Function Calls
Fast Numbers
Using Arrays
Accelerating Code with the GPU
Concurrent Programming with Tasks
Threads
Distributed Computing with Julia
Licences
Other Books You May Enjoy
Customer Reviews