Concurrency versus parallelism 9 Note It doesn't help that concurrent is defined in the dictionary as operating or occurring at the same time, which doesn't really help us much when trying to describe how it differs from parallel. For me, this first clicked when I started to understand why we want to make a distinction between parallel and concurrent in the first place! The why has everything to do with resource utilization and efficiency. Efficiency is the (often measurable) ability to avoid wasting materials, energy, effort, money, and time in doing something or in producing a desired result. Parallelism is increasing the resources we use to solve a task. It has nothing to do with efficiency. Concurrency has everything to do with efficiency and resource utilization. Concurrency can never make one single task go faster. It can only help us utilize our resources better and thereby finish a set of tasks faster. Let's draw some parallels to process economics In businesses that manufacture goods, we often talk about LEAN processes. This is pretty easy to compare with why programmers care so much about what we can achieve if we handle tasks concurrently. Let's pretend we're running a bar. We only serve Guinness beer and nothing else, but we serve our Guinness to perfection. Y es, I know, it's a little niche, but bear with me. Y ou are the manager of this bar, and your goal is to run it as efficiently as possible. Now, you can think of each bartender as a CPU core, and each order as a task. To manage this bar, you need to know the steps to serve a perfect Guinness: Pour the Guinness draught into a glass tilted at 45 degrees until it's 3-quarters full (15 seconds). Allow the surge to settle for 100 seconds. Fill the glass completely to the top (5 seconds). Serve. Since there is only one thing to order in the bar, customers only need to signal using their fingers how many they want to order, so we assume taking new orders is instantaneous. To keep things simple, the same goes for payment. In choosing how to run this bar, you have a few alternatives. Alternative 1-Fully synchronous task execution with one bartender Y ou start out with only one bartender (CPU). The bartender takes one order, finishes it, and progresses to the next. The line is out the door and going two blocks down the street-great! One month later, you're almost out of business and you wonder why.