General

Multithreading, parallelism, and concurrency, in particular, are quite new topics in C++; therefore, more and more best practices will be discovered in the coming years. Consider the rules in this chapter not as a complete list, but rather as a necessary starting point that will evolve over time. This holds particularly true for the parallel STL. At the time of writing this course (08/2017), the new C++17 standard - including the parallel algorithms - hasn’t been published yet; therefore, it is too early to formulate best practices for it.

Let’s start with a few very general best practices that will apply to atomics and threads.

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Code Reviews

Code reviews should be part of each professional software development process; this holds especially true when you deal with concurrency. Concurrency is inherently complicated and requires a lot of thoughtful analysis and experience.

To make the review most effective, send the code you want to discuss to the reviewers before the review. Explicitly state which invariants should apply to your code. The reviewers should have enough time to analyze the code before the official review starts.

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Minimize Data Sharing of Mutable Data

You should minimize data sharing of mutable data for two reasons: performance and safety. Safety is mainly about data races. Let me focus on performance in this paragraph. I will deal with correctness in the following best practices section.

You may have heard of Amdahl’s law. It predicts the theoretical maximum speedup you can get using multiple processors. The law is quite simple: If p is the proportion of your code that can run concurrently, you will get a maximum speedup of $\frac{1}{1-p}$ ...