Julia High Performance: Optimizations, distributed computing, multithreading, and GPU programming with Julia 1.0 and beyond, 2nd Edition This book is in very good condition and will be shipped within 24 hours of ordering. The cover may have some limited signs of wear but the pages are clean, intact and the spine remains undamaged. This book has clearly been well maintained and looked after thus far. Money back guarantee if you are not satisfied. See all our books here, order more than 1 book and get discounted shipping. . Bestandsnummer des Verk�ufers 7719-9781788298117

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Bibliografische Details

Titel: Julia High Performance: Optimizations, ...

Verlag: Packt Publishing

Erscheinungsdatum: 2019

Einband: paperback

Zustand: Very Good

Auflage: 2. Auflage

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Inhaltsangabe:

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 Description

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.

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 for

This book is for beginners and intermediate Julia programmers who are interested in high-performance technical programming. A basic knowledge of Julia programming is assumed.

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

�ber die Autorin bzw. den Autor:

Avik Sengupta is the vice president of engineering at Julia Computing, a contributor to open source Julia, and the maintainer of several Julia packages. Avik is the co-founder of two start-ups in the financial services and AI sectors, and is a creator of large, complex trading systems for the world's leading investment banks. Prior to Julia Computing, Avik was co-founder and CTO at AlgoCircle and at Itellix, director at Lab49, and head of algorithmic solutions at Decimal Point Analytics. Avik earned his MS in computational finance at Carnegie Mellon and MBA Finance at the Indian Institute of Management in Bangalore.

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