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 performance begins with the CPU but does not end there

In the previous chapter, we studied the CPU resources and the ways to use them for optimal performance. In particular, we observed that CPUs have the ability to do quite a lot of computation in parallel (instruction-level parallelism). We demonstrated it on multiple benchmarks, which show that the CPU can do many operations per cycle without any performance penalty: adding and subtracting two numbers, for example, takes just as much time as only adding them.

You might have noticed, however, that these benchmarks and examples have one rather unusual property. Consider the following example:

        for (size_t i = 0; i < N; ++i) {
            a1 += p1[i] + p2[i];
            a2 += p1[i] * p2[i];
           ...