The CPU and GPU are the two central processors that exist on every PC. And the first one is responsible for all types of tasks while the second is special in graphics enhancements. Therefore, it is logical that there are large differences between them. Although both comes out by the same essential elements, the transistors. In this section, we will give a review of the general architecture of CPU and GPU to understand their big differences.
How is the CPU different from the GPU?
Both the GPU and the CPU are processors that are made up of a lot of transistors. Commonly we can say that the transistors perform mathematical operations and read data in the binary program. That language consists of zeros and ones . and computers are the only one here that is capable of understanding. Beyond that, everything is different.
First, we focus on the CPU which is the general purpose processor. And this means that it can do all kinds of calculations, the CPU is unique for serial processing of the data. This last one implies the presence of high processing core in a tiny space. Therefore, it can execute a reduced number of programs at the same time. However, these programs are enormously complex and include significant amounts of instructions.
Why There Are So Many Cores In GPU?
On the other hand, we have the graphic processor or GPU that is much more specialized for tasks that need a high level of parallelism. The GPU is made up of thousands of cores inside. These are the cores that are much smaller and therefore can perform a much smaller number of operations.
That makes a GPU optimized to process significant amounts of data and perform the same specific operations over and over again. A GPU is able of running thousands of programs at a time. Traditionally applications running a GPU consist of a single instruction and multiple data.
The GPU is on the graphics card, and its ability to work in parallel is so high that can multiply by 100 or even much more the performance that can reach a CPU in operations specialized in vectors and arrays, this is geometric operations.
Initially, GPUs were used only for graphics processing. But the important evolution they have undergone has made their capacities increase significantly, so today there are many fields in which you can take advantage of their great ability to work in parallel. For Example, in scientific research with model simulation, artificial intelligence or the mining of cryptones.
There is nothing better than the following video to understand the big difference between a CPU and GPU. Here, first we will see a small robot drawing a face, second, we see a big machine that represents the GPU, and it does Something much more involved in less time.
Difference between CPU and GPU Video