difference between CPU and GPU

Difference between CPU and GPU

Today, in this article I am going to tell you about one of the most asked question on the planet which is “What is the difference bet CPU and GPU?”. Well, there are lots of articles and videos are present on the internet that usually just makes difference table of difference between CPU and GPU but. I am going to take this discussion in deep with a long example. Hope you will find your answer.

What is GPU?

GPU stands for Graphics Processing Unit. It is responsible for rendering. Everything you see on the monitor as a result of your GPUs labor. From simple things like images and videos to more complex things like video games, professional animation software, 3d rendering and so on.

GPUs and Graphics Cards are technically not the exact thing. For example, the R-TX 2080 is a GPU, a chip developed by Nvidia with its own specs like CUDA cores and so on. This is the part that does the actual calculations necessary to render and then display something to your monitor. Graphics Cards on the other hand are all based on this GPU. They all have the chip inside them but they vary in other regards like cooling and V-ROM. While there is only a single R-TX 2080 GPU, there are numerous graphics cards that utilize this GPU. Some faster, some slower, some with two fans, some three you get it.

You may also come across the term EGPU which stands for External Graphics Processing Unit. This actually refers to a separate enclosure that houses only a graphics card. The graphics card in question is like any other but instead of bunking in a PC case with all the other hardware components it prefers to chill. It also connects to the PC by a Thunderbolt 3 connection instead of a PCI Express by 16 connection, that all the other graphics cards use. This connection is slower but it’s an excellent solution if you want to equip your laptop with some extra performance.

Now besides, the normal GPU speed in the form of regular graphics cards but with their own Batcaves we also have integrated GPUs. These GPUs are mostly integrated with the CPU but they can also be integrated into a motherboard. So, this is where the difference between GPUs and Graphics Cards come in. Integrated GPUs have the chip and nothing else. They not even have their own dedicated VRAM. So, instead they have to use regular system RAM. They are way cheaper than actual graphics cards but they are also way less powerful and best suited for casual users.

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A graphics processor is a specialist processor that is designed to make processing of three-dimensional images more efficient than other forms of processor. It is a digital world. It’s all 1s and 0s, adds and minuses. And if you do lots of adds, you can turn it into a multiply. But actually, a graphics processor takes a very specialist workload and does it much more efficiently.

What is CPU?

CPU stands for Central Processing Unit. It is also commonly referred to as a processor but in the most basic sense, a CPU is just an extremely powerful calculator. Powerful means, it is able to handle countless computations and calculations at any given moment. It is also the brain of every computer in the sense that it tells all the other components what to do.

Nowadays CPUs are made up of billions of tiny transistors and divided into several cores. Each of these cores is capable of handling a single task at any time but in case of single core CPUs that you think fully don’t have to deal with anymore. Even in smartphones they are only capable of handling a single task at a time and the way they gave off the illusion of multitasking was by switching between tasks really quickly.

Besides cores, one of the most prominent specifications of any CPU is its clock speed. This speed is measured in GigaHertz where each Hertz equates to one instruction. So, if you have a three GigaHertz CPU, it can handle three billion instructions each second. So, obviously the faster the clock speed, the more powerful your PC will be. Each CPU has a core clock speed which is the default factory clock, but many CPUs can be overclocked so is to be even faster. Be warned however, that doing this will make the CPU generate more heat. So, if you plan on overclocking you would better make sure to have great cooling solution, that can keep up with this extra heat. But of course, the most important component for gaming is still the GPU and not the CPU. As I have said that the CPU is the brains of the computer that tells all the other components what to do that includes the GPU as well.

So, if you have a ridiculously powerful GPU and a CPU that’s underpowered by comparison, the CPU will not be able to get the most out of that GPU.

Difference between CPU and GPU

What are the fundamental differences between a central processing unit and a graphics processing unit? Well, fundamentally, we are here to put pixels on screens. So, at the end of the day, we are here to execute some commands whose purpose is to say that pixel on that screen is that color. And usually that’s presented to us as: Here is some data. So, usually there’s a three-dimensional model.

difference between CPU and GPU

Let’s take an example, as you can see in above image, the table is located on the ground. There is a square on it which is a few feet off the ground and it’s X thickness and it’s got some legs and it’s at this position. There are some chairs in the room. There are the walls all around. There is a three-dimensional model. So, first of all, you get given a bunch of coordinates and say the following things are at the following places. And then you say give them some more data, which is the chair is a brown at front and grey at its back and the table is a sort of brown. And so you get given some color information, which is what we call textures.

The geometry of the scene is usually broken up into triangles because triangles is nice and simple. We are very simple people. We can’t cope with complicated stuff. A triangle, three points, always has to be flat. You have never seen a triangle that isn’t flat. And so you divide complex surfaces up into triangles and then you have some information about what colors those triangles are. So you say, right, okay, I’ve got the geometry. I’ve got the color. What do we do next?

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Well, you put some lights in the scene. So there’s some lights in the ceiling which are shedding some light in certain directions. And then you need a camera. So you say the camera is located at some place in the room. So now you have to do some three-dimensional geometry to say well, what does it look like in the camera? And the first thing you observe is, about half the room, you can’t see. So, I don’t have to calculate everything that’s behind you. The only thing that I have to calculate are the bits you can see. And you project it so that it goes into the two-dimensional scree. And then you move the camera around, usually, to get sort of a real impression of moving through the scene. So, there’s a lot of different types of calculation involved in that. First is loads of three-dimensional matrix arithmetic. You know, XYZ coordinates, sometimes four-dimensional arrays with XYZ and transparency information. And lots and lots of RGB, red, green, blue, color.

So, a device that’s really good at matrix arithmetic is a good start. Floating point, because the position of all of these things are usually expressed as floating point. And then finally, you’ve got this unit in the back which says, oh well, I’ve got lots and lots of pixels to deal with, so we need to run through that and get them all into a buffer in memory.

So, some of that’s really quite different from a CPU. A lot of three-dimensional plane equations have to be solved. So, for example, here’s the table, here’s the floor. Well, which bits of the floor and which bits of the table can I see? So you have to do a lot of matrix solving to work that one out. And that’s the difference in the problem that gets given to us, right?

The difference in the design is: We say, well actually, I can do loads of this in parallel. Actually, I can do a lot of these quick calculations in parallel because they don’t depend on each other. So, every time you hear the phrase, “For every vertex in the geometry, do blah.” “For every pixel in the screen, do foo.” You can actually say, well actually, that’s a million pixels. I can actually calculate them in batches of 256 or something like that. So, we extract the parallelism out of the algorithm, and we design a processor that is actually very good at parallel processing.

So, the difference between a CPU and a GPU predominately is, yes, there’s some really fixed function blocks which we do very efficiently compared to a CPU, which does everything itself. But also, we are very good at extracting parallelism. So, if I want to multiply three floating point numbers together, I’ll do it more slowly than a CPU. But if you ask me to multiply a million three floating point numbers together, then the length of time it takes me to do a million will be a lot shorter than the time it takes a CPU to do a million.

So, we don’t care so much about how long anything individually takes. What we work on is the bulk throughput, and it’s a different end to the problem. And of course, there are blurred areas, and some people are now saying Well, actually there’s some sort of computing I could do that would do better on a GPU than on a CPU. And so you get this whole thing called GPU computing coming along where people are not actually doing graphics, but they’re doing throughput computing. And actually, that’s been quite interesting hearing. I think one of the ones that somebody suggested was people doing Bitcoin mining with GPUs because it’s just lots and lots of maths, and also, image processing.

So, in modern devices, you tend to have quite a poor lens, or a poor sensor, and you’re trying to take pictures that are as good as that camera you’re holding in your hand that costs thousands. And actually, that takes an awful lot of image clean-up. So, there’s an awful lot of computing that’s taking place on those digital images. And it turns out that actually a lot of those go quite well when executed on GPUs, not executed on CPUs.

Conclusion

So, to summarize, we have discussed the details about GPU and CPU. Then the difference between CPU and GPU. The biggest difference between CPU and GPU is that, the CPU is the brains of the computer that tells everything else what to do like calculations and all that stuff. The GPU is essentially the graphics card which is used to handle much more complex task like videos, images etc. At the moment, the only two names in the CPU business are Intel and AMD and in the GPU business these are Nvidia and once again AMD if you like to know which company is better in which field. So, this is all about in this article. I tried my best to explain you the difference between CPU and GPU. Hope you gained some knowledge. Thanks for reading stay blessed!

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Awais Nazar

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