Mis on Tensor Cores ja milliseid operatsioone nad kiirendavad?

Tensor Cores are specialized hardware blocks in modern GPUs (e.g., NVIDIA Volta, Turing, Ampere), designed to accelerate tensor operations, especially in machine learning tasks.

They are optimized for performing matrix operations with low precision (FP16, INT8), significantly increasing performance during training and inference of neural networks.

The main operations that accelerate Tensor Cores are:

• Matrix multiplication (Matrix Multiply)
• Matrix accumulation (Matrix Accumulate)

This allows for faster computations in deep neural networks, especially in convolutional and fully connected layers.

Example: when training a deep learning model using frameworks that support Tensor Cores (such as TensorFlow, PyTorch), matrix calculations are performed faster, reducing training time.