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The Art of Writing Efficient Programs

The Art of Writing Efficient Programs

By : Fedor G. Pikus
4.3 (24)
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The Art of Writing Efficient Programs

The Art of Writing Efficient Programs

4.3 (24)
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)
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1
Section 1 – Performance Fundamentals
7
Section 2 – Advanced Concurrency
11
Section 3 – Designing and Coding High-Performance Programs

Learning about concurrency and order

As the reader was reminded earlier in this chapter, any program that accesses any shared data without access synchronization (mutexes or atomic accesses, usually) has undefined behavior that is usually called a data race. This seems simple enough, at least in theory. But our motivational example was too simple: it had just one variable shared between threads. There is more to concurrency than locking shared variables, as we are about to see.

The need for order

Now consider this example known as the producer-consumer queue. Let us say that we have two threads. The first thread, the producer, prepares some data by constructing objects. The second thread, the consumer, processes the data (does work on each object). For simplicity, let us say that we have a large memory buffer that is initially uninitialized and the producer thread constructs new objects in the buffer as if they were array elements:

size_t N;     /...
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