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

Chapter 6: Concurrency and Performance

In the last chapter, we learned about the fundamental factors that affect the performance of concurrent programs. Now it is time to put this knowledge to practical use and learn about developing high-performance concurrent algorithms and data structures for thread-safe programs.

On the one hand, to take full advantage of concurrency, one must take a high-level view of the problem and the solution strategy: data organization, work partitioning, sometimes even the definition of what constitutes a solution are the choices that critically affect the performance of the program. On the other hand, as we have seen in the last chapter, the performance is greatly impacted by low-level factors such as the arrangement of the data in the cache, and even the best design can be ruined by poor implementation. These low-level details are often difficult to analyze, hard to express in code, and require very careful coding. This is not the kind of code you...