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

Summary


Now we have learned to write programs with Accelerate that run using the interpreter, and to compile and run them on CUDA-enabled GPUs. We know that Accelerate uses a code generator of its own internally. We understand it's crucial to write code that can efficiently reuse cached CUDA kernels, because their compilation is very expensive. We also learned that tuples are a free abstraction in Accelerate, although GPUs themselves don't directly support tupled elements.

In the next chapter, we will dive into Cloud Haskell and distributed programming using Haskell. It turns out Haskell is a pretty well-suited language for programming distributed systems. Cloud Haskell is an effort that streamlines building distributed applications, providing an abstraction over the network layer, among other things.