Book Image

The Art of Writing Efficient Programs

By : Fedor G. Pikus
3 (2)
Book Image

The Art of Writing Efficient Programs

3 (2)
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)
1
Section 1 – Performance Fundamentals
7
Section 2 – Advanced Concurrency
11
Section 3 – Designing and Coding High-Performance Programs

Performance trade-offs

Design is often the art of compromise; there are competing goals and requirements that must be balanced. In this section, we are going to talk specifically about performance-related trade-offs. You will make many such decisions when designing high-performance systems. Here are some to be aware of.

Interface design

We have witnessed the benefits of exposing implementation as little as possible throughout this chapter. But there is a tension between the freedom to optimize that we gain in doing so vs. the cost of very abstract interfaces.

This tension requires making trade-offs between optimizing different components: an interface that does not restrict the implementation in any way usually limits the client quite severely. For example, let us revisit our collection of points. What can we do without restricting its implementation? We cannot allow any insertions except at the end (the implementation may be a vector, and copying half the collection is unacceptable...