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

Data dependencies and pipelining

Our analysis of the CPU capabilities so far has shown that the processor can execute multiple operations at once as long as the operands are already in the registers: we can evaluate a fairly complex expression that depends on just two values in exactly as much time as it takes to add these values. The depends on just two values qualifier is, unfortunately, a very serious restriction. We now consider a more realistic code example, and we don't have to make many changes to our code:

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

Recall that the old code had the same loop with a simpler body: a1 += (p1[i] + p2[i]);. Also, p1[i] is just an alias for the vector element v1[i], same for p2 and v2. Why is this code more complex? We have already seen that the processor can do addition, subtraction, and multiplication in a single cycle, and the expression still depends on just two values...