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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

CuArrays

The CuArrays package is probably the most significant part of the GPU ecosystem in Julia. It provides an array type for storing data on the GPU and operating on it. Since GPU code needs to be vectorized, an array is the primary data type that needs to be used in all cases. 

A CuArray datatype can be created by calling its constructor with a regular Julia array. Once created, GPU kernels may be called on it. The package includes kernels for basic mathematical operators, which are typically called via dot-broadcast. As with all broadcasts in Julia, the operations are fused, which means that on the GPU, a single fused kernel is run on the array, even though multiple operations exist on the source. In other words, the power, subtraction, multiplication, addition, and squaring in the following expression is all combined into a single block of processing: 

julia&gt...
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