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Julia High Performance

You're reading from   Julia High Performance Optimizations, distributed computing, multithreading, and GPU programming with Julia 1.0 and beyond

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Product type Paperback
Published in Jun 2019
Publisher Packt
ISBN-13 9781788298117
Length 218 pages
Edition 2nd Edition
Languages
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Author (1):
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Avik Sengupta Avik Sengupta
Author Profile Icon Avik Sengupta
Avik Sengupta
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Toc

Table of Contents (13) Chapters Close

Preface 1. Julia is Fast FREE CHAPTER 2. Analyzing Performance 3. Types, Type Inference, and Stability 4. Making Fast Function Calls 5. Fast Numbers 6. Using Arrays 7. Accelerating Code with the GPU 8. Concurrent Programming with Tasks 9. Threads 10. Distributed Computing with Julia 11. Licences
12. Other Books You May Enjoy

ArrayFire

The ArrayFire library provides a high-level abstraction that makes writing massively parallel programs much simpler to write. The underlying library is written in C++, and the Julia wrapper provides an Array abstraction that allows idiomatic Julia programs to be executed on the GPU. 

To begin, install the ArrayFire library for your operating system from https://arrayfire.com/download/ and install it on your GPU machine. Once installed, ArrayFire provides a wrapper around an array that copies data from the CPU to the GPU, and performs operations on that data on the GPU cores. It really is that simple.

In the following example, we create a random 2D matrix, copy it to the GPU, multiply it by itself, and then copy the result back to the main memory:

julia> using ArrayFire

julia> a=rand(1000,1000);
1000×1000 Array{Float64,2}:
...

julia&gt...
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