Book Image

Haskell High Performance Programming

By : Samuli Thomasson
Book Image

Haskell High Performance Programming

By: Samuli Thomasson

Overview of this book

Haskell, with its power to optimize the code and its high performance, is a natural candidate for high performance programming. It is especially well suited to stacking abstractions high with a relatively low performance cost. This book addresses the challenges of writing efficient code with lazy evaluation and techniques often used to optimize the performance of Haskell programs. We open with an in-depth look at the evaluation of Haskell expressions and discuss optimization and benchmarking. You will learn to use parallelism and we'll explore the concept of streaming. We’ll demonstrate the benefits of running multithreaded and concurrent applications. Next we’ll guide you through various profiling tools that will help you identify performance issues in your program. We’ll end our journey by looking at GPGPU, Cloud and Functional Reactive Programming in Haskell. At the very end there is a catalogue of robust library recommendations with code samples. By the end of the book, you will be able to boost the performance of any app and prepare it to stand up to real-world punishment.
Table of Contents (21 chapters)
Haskell High Performance Programming
Credits
About the Author
About the Reviewer
www.PacktPub.com
Preface
Index

Profiling time and allocations


Profiling in the presence of lazy evaluation does not differ much from profiling always-strict programs. The profiler that comes with GHC assigns time and space usages to cost centres. Cost centres annotate expressions, and can be set either manually or automatically by GHC. Cost centres can occur enclosed in other cost centres recursively, forming cost centre stacks. All time and space costs accumulate in each enclosing cost centre.

Cost centres can be set manually via annotations, or automatically by GHC via compiler flags. Depending on how often the cost centre is entered, the choice of cost centre can have a big impact on overall execution time. Fortunately, allocation profiling is not affected by chosen cost centers.

Setting cost centres manually

Let's start our profiling journey with a basic example. The following program uses the simple moving average function we wrote in the first chapter:

-- file: prof-basics.hs

sma :: [Double] -> [Double]
sma (x0...