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 thread-safe list

In the sequential data structures we have studied so far, the data is stored in an array (or at least a conceptual array made up of memory blocks). Now we will consider a very different type of data structure where the data is linked together by pointers. The simplest example is a list where each element is allocated separately, but everything we learn here applies to other nodal containers such as trees, graphs, or any other data structure where each element is allocated separately, and the data is linked together by pointers.

For simplicity, we will consider a singly linked list; in STL, it is available as std::forward_list:

Figure 7.24 – Singly-linked list with iterators

Because each element is allocated separately, it can also be deallocated individually. Often, a lightweight allocator is used for these data structures, where the memory is allocated in large blocks that are partitioned into node-sized fragments. When a node...