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

Summary

In this chapter, you have learned perhaps the single most important lesson in the entire book: it makes no sense to talk, or even think, about performance without referring to specific measurements. The rest is largely craftsmanship: we presented several ways to measure performance, starting from the whole program and drilling down to a single line of code.

A large high-performance project will see every tool and method you learned about in this chapter used more than once. Coarse measurements – benchmarking and profiling the entire program or large parts of it – point to the areas of the code that require further investigation. Additional rounds of benchmarking or the collection of a more detailed profile usually follow. Eventually, you will identify the parts of the code that require optimization, and the question becomes, "how do I do this faster?" At this point, you can use a micro-benchmark or another small-scale benchmark to experiment with...