Multiplication algorithm: https://en.wikipedia.org/wiki/Multiplication_algorithm

From https://news.ycombinator.com/item?id=40519828 re: LLMs and matrix multiplication with tensors:

> "You Need to Pay Better Attention" (2024) https://arxiv.org/abs/2403.01643 :

>> Our first contribution is Optimised Attention, which performs similarly to standard attention, but has 3/4 as many parameters and one matrix multiplication fewer per head. Next, we introduce Efficient Attention, which performs on par with standard attention with only 1/2 as many parameters as many parameters and two matrix multiplications fewer per head and is up to twice as fast as standard attention. Lastly, we introduce Super Attention, which surpasses standard attention by a significant margin in both vision and natural language processing tasks while having fewer parameters and matrix multiplications.

From "Transformer is a holographic associative memory" (2025) https://news.ycombinator.com/item?id=43029899 .. https://westurner.github.io/hnlog/#story-43028710 :

>>> Convolution is in fact multiplication in Fourier space (this is the convolution theorem [1]) which says that Fourier transforms convert convolutions to products.

From https://news.ycombinator.com/item?id=41322088 :

> "A carbon-nanotube-based tensor processing unit" (2024)

"Karatsuba Matrix Multiplication and Its Efficient Hardware Implementations" (2025) https://arxiv.org/abs/2501.08889 .. https://news.ycombinator.com/item?id=43372227