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Why are GPU's much faster and more powerful than CPU's?

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Question added by Lana Oudeh , PR Coordinator , Al Ghanem
Date Posted: 2016/12/25
umar khan
by umar khan , SALES/ACCOUNTANT , MOHAMMAD HAMID ELECTRONICS

well first of all these two totaly different parts of computer

1:GPU (graphic processing unit)

2:CPU (central processing unit)

a cpu can work without gpu but gpu cannot work without cpu. a gpu is use for videos rendering and games etc.

but when i comes to cpu it is connected to every part of computer. now days cpu comes with integrated gpu but those are not powerful enough. to satisfied your need.

I hope you got the point.

Thank you.

MAHA Mahmoud Ismael Mahmoud Mahmuod
by MAHA Mahmoud Ismael Mahmoud Mahmuod , سكرتارية مكتب العميد - كلية طب الاسنان , جامعة البحر الاحمر

GPUs have high throughput, CPUs have high speed (generally speaking). There's a difference between speed and throughput

Abdullah Ghani
by Abdullah Ghani , Internal Auditor , Crowe

As GPU stands for Graphics Processing Unit, it only deals with the graphics and display. However the CPU has to control the entire system. Thats why GPU are much faster than the CPUs

Altaf  Hamed Shajahan
by Altaf Hamed Shajahan , Programme Manager - IT , ASAP - Higher Education Department, Government of Kerala

GPUs are made only with graphics processing in mind. It has only limited instruction sets to perform these specialised operations or we could say specialised hardware to perform limited operations very quickly and in parallel.

Whereas a standard CPU has to do a lot more different calculation and processing types to handle. When it comes to speed average speed per core of a GPU is less than that of a common CPU core. But total number of cores in a common GPU is almost double than that in CPU, which brings its total speed higher than CPU.

Average speed of single core of GPU < Average speed of single core of CPU

Total cores in GPU > Total cores in CPU

Speed of a GPU(many cores together) > Speed of CPU(multiple cores)

 

Deleted user
by Deleted user

GPUs tend to have thousands of relatively slow cores divided into groups that must execute in lock-step, whereas CPUs tend to have a 2-20 relatively fast cores that can execute completely independently of each other. If you have a task that can be parallelized, such as rendering graphics to a screen, running a Monte Carlo Simulation, multiplying matrices for a machine learning algorithm, or powering a database, GPUs will be much faster by virtue of their parallelism. On the other hand if you are running something that is effectively sequential, like powering a word processor, then CPUs will be faster.

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