Читать книгу Algorithms For Dummies - John Paul Mueller, John Mueller Paul, Luca Massaron - Страница 15

General-purpose processors, CPUs, started out as a means to solve problems using algorithms. However, their general-purpose nature also means that a CPU can perform a great many other tasks, such as moving data around or interacting with external devices. A general-purpose processor does many things well, which means that it can perform the steps required to complete an algorithm, but not necessarily fast. Owners of early general-purpose processors could add math coprocessors (special math-specific chips) to their systems to gain a speed advantage (see https://www.computerhope.com/jargon/m/mathcopr.htm for details). Today, general-purpose processors have the math coprocessor embedded into them, so when you get an Intel i9 processor, you actually get multiple processors in a single package.

A GPU is a special-purpose processor with capabilities that lend themselves to faster algorithm execution. For most people, GPUs are supposed to take data, manipulate it in a special way, and then display a pretty picture onscreen. However, any computer hardware can serve more than one purpose. It turns out that GPUs are particularly adept at performing data transformations, which is a key task for solving algorithms in many cases. It shouldn’t surprise you to discover that people who create algorithms spend a lot of time thinking outside the box, which means that they often see methods of solving issues in nontraditional approaches.

The point is that CPUs and GPUs form the most commonly used chips for performing algorithm-related tasks. The first performs general-purpose tasks quite well, and the second specializes in providing support for math-intensive tasks, especially those that involve data transformations. Using multiple cores makes parallel processing (performing more than one algorithmic step at a time) possible. Adding multiple chips increases the number of cores available. Having more cores adds speed, but a number of factors keeps the speed gain to a minimum. Using two i9 chips won’t produce double the speed of just one i9 chip.