Chapter 1. An Introduction to Parallel and Distributed Computing
The first modern digital computer was invented in the late 30s and early 40s (that is, arguably, the Z1 from Konrad Zuse in 1936), probably before most of the readers of this book—let alone the author—were born. These last seventy odd years have seen computers become faster and cheaper at an amazing rate, which was unique across industries. Just think that today's smartphones (for example, the latest iPhones or Android phones) are faster than the fastest computer in the world from just 20 years ago. Not to mention, the amazing feat of miniaturization: those supercomputers used to take up entire rooms; now they fit in our pockets.
These years have also seen, among others, two key inventions relevant to the topic at hand. One is the ability to cram more than one processor on a single motherboard (and even multiple CPU cores on a single processor). This development was crucial in allowing computations to be performed truly concurrently. As we know, processors are able to perform only one task at a time; however, as we will see later on in the chapter, they are fast enough to give the illusion of being able to run multiple tasks at the same time. To be able to perform more than one action exactly at the same time, you need access to more than one processor.
The other critical invention is high-speed computer networking. This allowed, for the first time, a potentially enormous number of computers to communicate with each other. These networked machines can either be located in the same office/building (the so-called Local Area Network (LAN)) or be spread out across different buildings, cities, or even across the planet (that is, WAN or wide area networking).
By now, most of us are familiar with multiprocessor/multicore computers, and indeed, the chances are pretty high that the phone in our pocket, the tablet in our hands, or the laptop we take on the road has a handful of cores already. The graphics card, also called Graphics Processing Unit (GPU) in these devices is more often than not massively parallel, with hundreds or even thousands of processing units. Computer networks too are all around us, starting from the most famous of them all: the Internet, to the Wi-Fi in our homes and coffee shops and the 4G mobile networks our phones use.
In the rest of this chapter, we will lay some working definitions of the topics that we will explore in the rest of the book. We will be introducing the concepts of parallel and distributed computing. We will give some examples of each that are taken from familiar topics and technologies. Some general advantages and disadvantages of each architecture and programming paradigm will be discussed as well.
Before proceeding with our definitions and a little bit of theory, let's clarify a possible source of confusion. In this and the following chapters, we will use the term processor and the term CPU core (or even simply core) interchangeably, unless otherwise specified. This is, of course, technically incorrect; a processor has one or more cores, and a computer has one or more processors as cores do not exist in isolation. Depending on the algorithm and its performance requirements, running on multiple processors or on a single processor using multiple cores can make a bit of difference in speed, assuming, of course, that the algorithm can be parallelized in the first place. For our intents and purposes, however, we will ignore these differences and refer to more advanced texts for further exploration of this topic.
