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

What is needed to use concurrency effectively?

Fundamentally, using concurrency to improve performance is very simple: you really need to do just two things. The first one is to have enough work for the concurrent threads and processes to do so they are busy at all times. The second one is to reduce the use of the shared data since, as we have seen in the previous chapter, accessing a shared variable concurrently is very expensive. The rest is just a matter of the implementation.

Unfortunately, the implementation tends to be quite difficult, and the difficulty increases when the desired performance gains are larger and when the hardware becomes more powerful. This is due to Amdahl's Law, which is something every programmer working with concurrency has heard about, but not everyone has understood the full extent of its implications.

The law itself is simple enough. It states that, for a program that has a parallel (scalable) part and a single-threaded part, the maximum possible...