Julia high performance : optimizations, distributed computing, multithreading, and GPU programming with Julia 1.0 and beyond
著者
書誌事項
Julia high performance : optimizations, distributed computing, multithreading, and GPU programming with Julia 1.0 and beyond
Packt Publishing, 2019
2nd ed
大学図書館所蔵 全4件
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内容説明・目次
内容説明
Design and develop high-performance programs in Julia 1.0
Key Features
Learn the characteristics of high-performance Julia code
Use the power of the GPU to write efficient numerical code
Speed up your computation with the help of newly introduced shared memory multi-threading in Julia 1.0
Book DescriptionJulia 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.
What you will learn
Understand how Julia code is transformed into machine code
Measure the time and memory taken by Julia programs
Create fast machine code using Julia's type information
Define and call functions without compromising Julia's performance
Accelerate your code via the GPU
Use tasks and asynchronous IO for responsive programs
Run Julia programs on large distributed clusters
Who this book is forThis book is for beginners and intermediate Julia programmers who are interested in high-performance technical programming. A basic knowledge of Julia programming is assumed.
目次
Table of Contents
Julia is Fast
Analyzing Performance
Type, 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
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