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F# High Performance

F# High Performance

By : Kusumawardhono
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F# High Performance

F# High Performance

5 (1)
By: Kusumawardhono

Overview of this book

F# is a functional programming language and is used in enterprise applications that demand high performance. It has its own unique trait: it is a functional programming language and has OOP support at the same time. This book will help you make F# applications run faster with examples you can easily break down and take into your own work. You will be able to assess the performance of the program and identify bottlenecks. Beginning with a gentle overview of concurrency features in F#, you will get to know the advanced topics of concurrency optimizations in F#, such as F# message passing agent of MailboxProcessor and further interoperation with .NET TPL. Based on this knowledge, you will be able to enhance the performance optimizations when implementing and using other F# language features. The book also covers optimization techniques by using F# best practices and F# libraries. You will learn how the concepts of concurrency and parallel programming will help in improving the performance. With this, you would be able to take advantage of multi-core processors and track memory leaks, root causes, and CPU issues. Finally, you will be able to test their applications to achieve scalability.
Table of Contents (9 chapters)
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Chapter 3. Optimizing Data Structures

It is common in many applications to leverage all kind of objects that are used as data. The types of data can be primitive, object reference, and collection types. F# itself has its own unique types, especially collection types.

These types, especially when doing many computing-intensive operations, are crucial. Optimizations need not only relate to the location of the value of data stored according to the types, but also how we access them can have a big impact on overall performance.

The deciding factors determining the best types to use, besides the memory locations, can vary. This is why it is quite hard to measure qualitatively. Measuring quantitatively can be tricky, although the statistical numbers may be informative.

We shall use the knowledge gained in Chapter 2, Performance Measurement relating to the qualitative understanding of the internals of running F# code (the IL, tooling, and the GC) and have quantitative measures (the execution...

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