Lately, we have been hearing more and more about GPUs. Now they are becoming an integral part of laptops and computers to enhance user’s experience. But this debate has risen to a level where there is high talk to replace CPU with GPU. Can they really replace entirely is a very important question and we do not have the full answer to this. Although GPUs are now becoming more important and important. We can safely say in the future their usage will increase exponentially with the advancement in the field of AI. If we want to see the true potential of GPU we have to see the comparison between CPU and GPU.
The main difference between GPU and CPU is the architecture. Because of that architecture GPU and CPU can perform certain tasks that suit best them. On the surface level, they both are silicon microprocessors that need a cooling fan. But on their microarchitecture level, we will find some fundamental differences, and because of these differences GPU and CPU can be differentiated and their tasks differ widely.
Many people keep swiss army knives with them all the time because they are very handy and they can perform a lot of diversified tasks. But if the doctor has to perform the surgery he would not be able to do that with the swiss army knife. A doctor would use a scalpel and other surgical instruments. These surgical instruments perform very limited tasks, but they are best in their respective tasks. The same analogy applies to CPU and GPU. Like swiss knife CPU can do lot more tasks but GPU can perform one task which is very specialized – GRAPHICS.
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Difference between GPU and CPU
The above picture shows the very integral differences of GPU and CPU on the micro-level. So we can see CPU has different parts that help to do different tasks. The same goes for GPU, it has different architecture at the micro level which helps it to perform different tasks. Modern CPUs are equipped to do a lot of tasks. They can perform financial functions, write scripts, visual editing, and illustration. So these are very random tasks and CPUs are made in a way they can handle all this randomness without exploding. On the other hand, GPUs are made for very specialized tasks. This specialized task is rendering graphics it means doing millions of very same calculations in parallel. CPUs are versatile but they are less efficient whereas GPUs is one purpose thing but very efficient.
GPUs have a lot of computing units which helps to do a lot of mathematical functions at the same time that helps to show better graphics. Now doing these repetitive tasks are the very reasons for GPU’s popularity. Tasks that are repetitive in nature can be performed by GPU is a very efficient and fast method.
We talked a lot about GPU and CPU and their functionalities. In this paragraph, we will discuss obvious differences. CPU refers to central processing unit whereas GPU stands for Graphics processing unit. CPU is responsible for the complete functionality of the computer but GPU is mainly responsible for the graphics and how it shows to the user. CPU needs more memory than GPU. Because the CPU is receiving commands and then giving commands to respective parts like the human brain. It needs short-term memory of what has been managed and what needs to be done. So CPU has a cache that behaves like short-term memory.
However, GPU is just giving command for display unit and doing a lot of mathematical calculations but they do not need to be saved in the memory. CPU has fewer cores that actually do the work of computers, but they are very powerful. GPU has a lot of cores, but their strength is very weak compared to CPU cores. One of the main goals of the CPU is to reduce the latency. It works on the principle of being very fast. GPU focuses on high throughput. This will give you an overall idea of how GPU is different from CPU to its cores.
GPU in Gaming & AI
GPU is not a new concept to gamers but it is their necessity. There are games that need better and better GPUs for showing better graphics. Companies like Intel, AMD, and Nvidia release a new and better version of the graphics card on yearly basis. In the last 5 years, this concept of GPU got high momentum because of high demand from the game makers. Let’s see where this bull run of GPU take us and what will be the future of graphics card.
The new and promising endeavor of GPU is its usability in AI and machine learning programming. AI has to do a lot of calculations along with the using functions of the CPU. So developers are integrating more and more GPU with AI devices and robots. With the promising result of using GPU with CPU, encouraged programmers and developers to use GPU. Because of this GPUs are on the rise and there are becoming more and more popular every day.
At the end we reach to the conclusion that it depends on you. What you do and what are your digital needs according to that, you can equip GPU to your system or what GPU, you should choose.
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