Matrix Multiplication
Matrix multiplication is the binary operation where each element of the result is the dot product of a row from the first matrix and a column from the second. It is the single most important operation in neural networks.
What is Matrix Multiplication?
Matrix multiplication is the binary operation where each element of the result is the dot product of a row from the first matrix and a column from the second. It is the single most important operation in neural networks.
Matrix multiplication is the binary operation where each element of the result is the dot product of a row from the first matrix and a column from the second. It is the single most important operation in neural networks.
Where is it used?
Every linear layer, embedding lookup (as matmul with one-hot), attention score computation (Q×K^T), and feed-forward network in GPT/Llama is implemented as matrix multiplication.
How to build it
Use `torch.matmul(a, b)` or the `@` operator on two 2D tensors, verify the inner dimensions match, and benchmark `torch.matmul` on GPU to see why BLAS-accelerated matmul drives modern AI.
Code
A practical example: