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 introductory chapter, we have discussed why the interest in software performance and efficiency is on the rise despite the rapid advances in the raw computational power of modern computers. Specifically, we have learned why, in order to understand the factors limiting performance and how to overcome them, we need to return to the basic elements of computing and understand how computers and programs work at a low level: understanding the hardware and using it efficiently, understanding concurrency, understanding the C++ language features and the compiler optimizations, and their impact on performance.

This low-level knowledge is necessarily very detailed and specific, but we have a plan for dealing with that: as we learn specific facts about the processors or compilers, we will also learn the process by which we have arrived at these conclusions. Thus, at its deepest level, this book is about learning how to learn.

We have further understood that the notion of performance is meaningless without defining the metrics by which this performance is measured. The need to evaluate the performance against the specific metrics implies that any work on performance is driven by data and measurements. Indeed, the next chapter is dedicated to measuring performance.