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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

Concurrent Programming with Tasks

Most programs in Julia run on a single thread, on a single processor core. In other words, most processing in Julia is synchronous. But we know that a modern computer can appear to do many things in parallel. It can play music while you are writing a report, run your tests when you are typing code, or run a web server in the background. There are many layers to achieving this level of multiprocessing. In this chapter, we will look at concurrent primitives that make it possible to run parallel, or seemingly parallel operations, without the full complexities of shared memory multithreading. We will discuss how the concept of co-operative multitasking, implemented as tasks and asynchronous I/O, helps create responsive programs. The following are the topics we will cover in this chapter:

  • Tasks
  • Controlling tasks with the @sync and @async macros...
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