New Linear-complexity Multiplication (L-Mul) algorithm claims it can reduce energy costs by 95% for element-wise tensor multiplications and 80% for dot products in large language models. It maintains ...

First of all, thank you very much for the PyTorch Geometric build, I use it all the time and it's very smooth! When debugging the base code, I noticed that for sparse matrix multiplication, you call ...

DeepMind’s paper also pointed out that AlphaTensor discovers a richer space of matrix multiplication algorithms than previously thought — up to thousands for each size.

The BRMerge accumulation method follows the row-wise dataflow. It first accesses the B matrix, generates the intermediate lists for one output row, and stores these intermediate lists in a consecutive ...

Sparse general matrix multiplication (SpGEMM) is a fundamental building block for many real-world applications. Since SpGEMM is a well-known memory-bounded application with vast and irregular memory ...

I have implemented a custom convolutional operator with Unfold+matrix multiplication+Fold as described in the pytorch documentation, under Unfold examples here: Ideally, this should be the same thing ...