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

Chapter 3. Profile and Benchmark to Your Heart's Content

So far we haven't used much else but heap usage statistics to gauge the performance of Haskell programs. For a quick overview of the overall performance of a program, a simple +RTS -s is often sufficient. However, often it is necessary to know which parts of the code specifically are taking up the most time and space.

In this chapter we extend our toolset with more sophisticated profiling and benchmarking facilities. We will learn to inspect and set cost centres, to benchmark robustly when semantics are mostly lazy. Finally we'll also look at monitoring performance while the program is still running.

  • Profiling time, allocation and space usage

  • Profiling the heap: break-downs and subset selection

  • Benchmarking Haskell programs with the criterion library

  • Monitoring still-executing programs in real-time with ekg