Nvidia created the first graphics card with Tensor Cores that is much better than CUDA cores, Tensor Cores include a mixed-precision mechanism, and it accelerates the calculation while providing consistent speed and performance. These cores work on deep learning performance that is more reliable and professional than CUDA Cores.
Tensor Cores in Graphics Card
The definition of the Tensor cores is simple but to understand it seems quite complex, a tensor is a mathematical object that defines the relations of other mathematical objects that are linked together, logical, yes, it is but you will understand it after going through the detailed image.
In the above picture, an array of dimensions and an array of numbers are stated.
0 dimension = 1 Tensor that consists of value (any) it is 4 here
It will change on 1 Dimension, 2 Dimension, and 3 Dimension.
Nvidia said that the Volta chips are intended to enable real-time AI applications, like autonomous vehicles, robotics, and computer games. So far, Volta is only available in a handful of high-end Tesla cars and robots. It isn’t clear when this chip will come to a consumer device. However, Nvidia claims that it has created an AI model that will reduce the processing time for deep learning algorithms.
Deep learning algorithms are used to perform tasks that are similar to human thinking. These algorithms were first used for facial recognition. Now, they can help computers understand speech, recognize objects, and translate from one language to another. Volta will allow developers to use these algorithms faster and with less power consumption.
NVidia introduced their first 256 GEMMs per cycle GPU when Ampere Architecture first came into the A100 data center graphics processor, it was the plus move by Nvidia that helped users to access more data with the ability to handle sparse tensors (matrices that contain a lot of zeros) at a gigantic speed, this is one step ahead of CUDA cores, though CUDA works for the same cause but Tensors are more powerful assisted with AI technology.
It is good to know that programmers can easily access to the tensor cores provided by Turing, Volta, or Ampere chip, the code is modified to narrate the API and drivers about the new settings, consider one thing, there should be a dimension of 8 using the matrices system.
What are Tensor Cores in Graphics Card? FAQs:
Which GPUs have tensor cores?
There are tons of GPUs that contain Tensor cores these days, All cards contain almost the same Tensor Cores. The RTX 2060 to RTX 3090 contains Tensor Cores.
How many tensor cores in 3090 RTX?
There are 336 Tensor Cores in RTX 3090 graphics card.
How many tensor cores in 3080 RTX?
There are 272 Tensor Cores in 3080 RTX graphics Card.
How many tensor cores in 3060 RTX?
112 Tensor Cores in 3060 RTX graphics cards.
How many tensor cores in 2080 ti?
Surprisingly, 2080 Ti graphics cards contain 576 Tensor Cores.