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

Optimization of conditional execution

After the unnecessary computations and inefficient use of memory, the next easiest way to write inefficient code that fails to utilize a large fraction of available computing resources is probably code that does not pipeline well. We have seen the importance of CPU pipelining in Chapter 3, CPU Architecture, Resources, and Performance Implications. We have also learned there that the worst disruptor of pipelining is usually a conditional operation, especially the one that the hardware branch predictor fails to guess.

Unfortunately, optimizing conditional code for better pipelining is one of the hardest C++ optimizations. It should be undertaken only if the profiler shows poor branch prediction. Note, however, that the number of mispredicted branches does not have to be large to be considered “poor”: a good program will typically have less than 0.1% of mispredicted branches. The misprediction rate of 1% is quite large. It is also...