At this point, if you have had some experience in parallel programming, you might be wondering whether concurrency is any different from parallelism. The key difference between concurrent and parallel programming is that, while in parallel programs there are a number of processing flows (mainly CPUs and cores) working independently all at once, there might be different processing flows (mostly threads) accessing and using a shared resource at the same time in concurrent programs.

Since this shared resource can be read and overwritten by any of the different processing flows, some form of coordination is required at times, when the tasks that need to be executed are not entirely independent from one another. In other words, it is important for some tasks to be executed after the others, to ensure that the programs will produce the correct results.

The preceding figure illustrates the difference between concurrency and parallelism: while in the upper section, parallel activities (in this case, cars) that do not interact with each other can run at the same time, in the lower section, some tasks have to wait for others to finish before they can be executed.

We will look at more examples of these distinctions later on.