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

The ghost in the machine

In the last two chapters, we have learned how complex the path from the initial data to the final result can be on a modern computer. Sometimes the machine does precisely what the code prescribes: read the data from memory, do the computations as written, save the results back to memory. More often than not, however, it goes through some strange intermediate states we don't even know about. Read from memory does not always read from memory: instead of executing instructions as written, the CPU may decide to execute something else, speculatively, because it thinks you will need it, and so on. We have tried to confirm by direct performance measurements that all of those things really do exist. By necessity, these measurements are always indirect: the hardware optimizations and transformations of the code are designed to deliver the correct result, after all, only faster.

In this section, we show yet more observable evidence of the hardware operations...