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The Art of Writing Efficient Programs

The Art of Writing Efficient Programs

By : Fedor G. Pikus
4.3 (24)
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The Art of Writing Efficient Programs

The Art of Writing Efficient Programs

4.3 (24)
By: Fedor G. Pikus

Overview of this book

The great free lunch of "performance taking care of itself" is over. Until recently, programs got faster by themselves as CPUs were upgraded, but that doesn't happen anymore. The clock frequency of new processors has almost peaked, and while new architectures provide small improvements to existing programs, this only helps slightly. To write efficient software, you now have to know how to program by making good use of the available computing resources, and this book will teach you how to do that. The Art of Efficient Programming covers all the major aspects of writing efficient programs, such as using CPU resources and memory efficiently, avoiding unnecessary computations, measuring performance, and how to put concurrency and multithreading to good use. You'll also learn about compiler optimizations and how to use the programming language (C++) more efficiently. Finally, you'll understand how design decisions impact performance. By the end of this book, you'll not only have enough knowledge of processors and compilers to write efficient programs, but you'll also be able to understand which techniques to use and what to measure while improving performance. At its core, this book is about learning how to learn.
Table of Contents (18 chapters)
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1
Section 1 – Performance Fundamentals
7
Section 2 – Advanced Concurrency
11
Section 3 – Designing and Coding High-Performance Programs

Summary

The last chapter of our book reviews everything we learned about the performance and what determines it, then uses this knowledge to come up with design guidelines for high-performance software systems. We have offered several recommendations for designing interfaces, data organization, components, and modules and described ways to make design decisions informed with good measurement results before we have an implementation whose performance can be measured.

Once again, we must emphasize that design for performance does not automatically yield good performance: it allows for the possibility of a high-performing implementation. The alternative is a performance-hostile design that locks in decisions constraining and preventing efficient code and data structures.

This book has been a journey: we started by learning about the performance of individual hardware components, then studied their interactions with each other and how they influence our use of programming languages...

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