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.
What you will learn
- Program idiomatic Haskell that’s also surprisingly efficient
- Improve performance of your code with data parallelism, inlining, and strictness annotations
- Profile your programs to identify space leaks and missed opportunities for optimization
- Find out how to choose the most efficient data and control structures
- Optimize the Glasgow Haskell Compiler and runtime system for specific programs
- See how to smoothly drop to lower abstractions wherever necessary
- Execute programming for the GPU with Accelerate
- Implement programming to easily scale to the cloud with Cloud Haskell
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