In industrial recommendation systems, the shift toward Generative Retrieval (GR) is replacing traditional embedding-based nearest neighbor search with Large Language Models (LLMs). These models ...

Add a description, image, and links to the sparse-matrix-vector-multiplication topic page so that developers can more easily learn about it.

Abstract: The rising popularity of deep learning algorithms demands special accelerators for matrix-matrix multiplication. Most of the matrix multipliers are designed based on the systolic array ...

The Nature Index 2025 Research Leaders — previously known as Annual Tables — reveal the leading institutions and countries/territories in the natural and health sciences, according to their output in ...

Performing dense*sparse matrix multiplication using a CuSparseMatrixCOO does not yield the correct result. In the example below, dense*sparse spmm is performed ...

Discovering faster algorithms for matrix multiplication remains a key pursuit in computer science and numerical linear algebra. Since the pioneering contributions of Strassen and Winograd in the late ...

Abstract: Sparse general matrix-matrix multiplication, SpGEMM, is one of the most fundamental yet challenging sparse computation kernels. Due to its irregular computation pattern, SpGEMM frequently ...

I'm getting ready to start working on a C/C++ project that will be building and solving large tri-diagonal, block tri-diagonal and triangular matrices. I know there are a lot of libraries available ...