Modern games have amazing graphics especially on the PC but no ever computer can handle these graphics why is graphics cards obviously a good graphics card can go a very long way in providing us with extremely high graphic game experiences. But how what exactly is a GPU and how exactly is it different from a CPU why do we need one. Today game ranks ask the question how do graphics cards work so when new battlefield games come out what does everybody talked about immediately the graphics of course the graphics it’s the thing you see first no matter what you don’t get to see something else and say you’ve seen the game. Visually what a game looks like matters a great deal to us and while I like to talk about art style a lot there’s a lot of technical Jargon behind. What goes on in order to bring you representations of what’s going on in an imaginary world so to start off computers a CPU and a GPU when described sound pretty similar a CPU and GPU.
Both do math they both solve problems and give you results that looks entirely different on a screen that it does inside a series of transistors and wires and processors bouncing electrical signals around saying yes or no over and over and over again at incredible rates so to put it in the most simple possible words a CPU. It can do things in a much more linear way than a GPU, a CPU may have a few course – 48 however many the number isn’t really relevant but that’s the number of streams of operations that a CPU can do at a time one per core. Now it’s important that a CPU exists because some things that are very complex need a more dedicated architecture to continue to process those operations but the way a GPU works through technologies like Cuba. Compute unified device architecture which was actually developed by in video and therefore not the only technology like this but the principles that apply to Cuba basically apply to most GPU technology. If not all is kind of like and when I say kind of I mean kind of like a lot of little CPUs, now the reason I say kind of and not exactly like is because the course of a CPU can all be dedicated towards different problems. Whereas all of the sub course of a cubic or have to be dedicated to a parallel problem like, I don’t know graphics and that’s over simplifying it just a little bit as graphics are several sub routines but essentially a lot of little cores are solving somewhat simpler problems than what a cpu might be used for much faster. Because there’s lots of them and what I mean by a simpler problem is like geometry in all honesty a geometry problem is really just a few computation and if you have a ton of course dedicated to it at once it’s going to get solved very fast.
Geometry is just shapes and trajectories and variables that affect placement and angle and things like that easier things to do but when presented with a limited amount of course what kind of clogged up the workflow let’s say you’ve got an eight core cpu and you’ve got a hundred different geometry problems to solve well. They take up a court until you get through the hundred but imagine if you send the same set of geometry problems to a multi core graphics card with hundreds of sub course ones that are made for a specific purpose and that purpose is geometry to tackle that geometry as fast as it can with a horde of processors. Well that would be generally looked at as a much more efficient with doing things wouldn’t it and that’s why a GPU is so much better at rendering graphics than a CPU sure there’s nothing that would stop you from playing a game on a CPU but there’s a reason why the CPU is generally used for things like artificial intelligence because they’re much more complex operations that take a longer period of time to do. When you have a limited number of data streams you want to be using the data streams in the most optimized way and if you have one type of processor that has a limited amount of cores that are all held up on specific things you would probably want to throw the more complex. Singular operations towards that whereas if you have geometry oriented problems that can be solved quickly. You have a lot of those problems you would probably want to solve those with lots and lots of small cores and they’re all geometry oriented and therefore easier to solve by a GPU.
So I’d like to send them that direction and it will handle it much faster than if I sent them towards the CPU, I don’t know if you remember it I do it was a while back it’s okay if you don’t know it’s important to say that you couldn’t just throw anything you wanted a GPU. Do it faster that’s just not true complex problems often involve multiple threads of information going on at once and as I said on a GPU the problems have to be parallel. Well if the problem diverts in some way from what one would consider parallel it’s not something that a GPU is going to do very fast at all. The main reason it’s so good for graphics is it can do so much of one thing at once graphics routines are fairly straightforward and don’t go into uncharted territory too often. It’s not trying to simulate anything other than fairly straightforward processes. If I drop an item it falls okay, if wind hits the cloth it does moving. If you look at the Sun there’s a lens flare that type of stuff in which the result is always going to be the same or very similar and stuff that is going to need to be done a lot like we’re all the vertices are and how many faces are painted in between them a vertex being a corner. On a shape and a face being a surface that’s drawn between three vertices that may be smooth or textured or utterly flat given that way cool retro look.
Essentially now you know what a GPU is and why one uses it and what it does granted this are actually a simplified version of all of this and there’s a lot of theory that can be talked about. I’m sure that will actually get into deeper conversation if we all meet in a small conversation and open our big traps to talk with each other.
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