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

Pipelining and branches

Here is our understanding of the efficient use of a processor so far: first, the CPU can do multiple operations at once, such as add and multiply at the same time. Not taking advantage of this capability is like leaving free computing power on the table. Second, the factor that limits our ability to maximize efficiency is how fast we can produce the data to feed into these operations. Specifically, we are constrained by the data dependencies: if one operation computed the value that the next operation uses as an input, the two operations must be executed sequentially. The workaround to this dependency is pipelining: when executing loops or long sequences of code, the processor will interleave separate computations such as loop iterations, as long as they have at least some operations that can be executed independently.

However, pipelining has an important precondition as well. Pipelining plans ahead: in order to interleave code from several loop iterations...