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Haskell High Performance Programming

You're reading from   Haskell High Performance Programming Write Haskell programs that are robust and fast enough to stand up to the needs of today

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Product type Paperback
Published in Sep 2016
Publisher Packt
ISBN-13 9781786464217
Length 408 pages
Edition 1st Edition
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Author (1):
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Samuli Thomasson Samuli Thomasson
Author Profile Icon Samuli Thomasson
Samuli Thomasson
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Table of Contents (16) Chapters Close

Preface 1. Identifying Bottlenecks 2. Choosing the Correct Data Structures FREE CHAPTER 3. Profile and Benchmark to Your Heart's Content 4. The Devil's in the Detail 5. Parallelize for Performance 6. I/O and Streaming 7. Concurrency and Performance 8. Tweaking the Compiler and Runtime System (GHC) 9. GHC Internals and Code Generation 10. Foreign Function Interface 11. Programming for the GPU with Accelerate 12. Scaling to the Cloud with Cloud Haskell 13. Functional Reactive Programming 14. Library Recommendations Index

Chapter 5. Parallelize for Performance

Nowadays, as single processor cores are not getting much faster, CPU manufacturers instead keep increasing the number of cores in processors, implying that high-performance programs must accordingly exploit more and more parallelism to keep up with this breadth-wise hardware development.

Turns out, one of Haskell's strongest aspects, referential transparency, is very valuable for parallelization. Automatically knowing that some distinct expressions won't interact with each other means they are safe to execute simultaneously. Note that parallelism is very different from concurrency, which usually refers to interacting processes (they aren't necessarily executed in parallel).

In this chapter, we will cover what the Haskell ecosystem currently has to offer for parallelism: a powerful parallel runtime system, fairly high-level abstractions for parallel evaluation, data parallel programming, and diagnostic tools for parallel programs...

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