CPU and GPU have a similar purpose but are optimized for different computing tasks. An efficient computer will need both to run properly for the device. CPU and GPU both are processor units. CPU is considered as the brain of the computer and consists of ALU which stores the information and performs the calculation and CU which performs instructions and branching. GPU is used to enhance the images, and videos of the computer, ALUs. Here this article gives information about the difference between CPU and GPU to better understand this topic.
Definition of CPU:
CPU stands for the central processing unit, It is a device that primarily acts as the brain for every embedded system. It consists of an ALU used to temporarily store the data and perform calculations and a control unit that performs instruction sequencing and branching. It also interacts with the other units of the computer such as memory, input, and output, for executing the instruction from the memory this is the reason an interface is also a crucial part of the CPU.
Definition of GPU:
GPU stands for graphics processing unit, It is a processor specially designed for computing the graphical displays. It is typically incorporated with the CPU for sharing RAM with the CPU which is good and easy work for most computing task. It is needed for high-end graphics-intensive processing. The discrete GPU unit contains its own RAM knowns s VRAM for video RAM.
The main key difference between CPU and GPU:
- CPU stands for the central processing unit, While the GPU stands for the Graphics processing unit.
- CPU consume or need more memory than GPU.
- CPU contains minute-powerful cores, while GPU contains more weak cores.
- The speed of CPU is less than GPU speed, while the GPU is faster than CPU speed.
- CPU emphasize on low latency, but the GPU emphasises on high throughput.
- CPU is suitable for serial instruction processing, while the GPU is not suitable for serial instruction processing.
- CPU is not suitable for parallel instruction processing while the GPU is suitable for parallel instruction processing.
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