Matrix multiplication advancement could lead to faster, more efficient AI models At the heart of AI, matrix math has just seen its biggest boost "in more than a decade.” ...

Photonic accelerators have been widely designed to accelerate some specific categories of computing in the optical domain, especially matrix multiplication, to address the growing demand for ...

The most widely used matrix-matrix multiplication routine is GEMM (GEneral Matrix Multiplication) from the BLAS (Basic Linear Algebra Subroutines) library. And these days it can be found being used in ...

Matrix multiplication is at the heart of many machine learning breakthroughs, and it just got faster—twice. Last week, DeepMind announced it discovered a more efficient way to perform matrix ...

Mathematics DeepMind AI finds new way to multiply numbers and speed up computers Matrix multiplication - where two grids of numbers are multiplied together - forms the basis of many computing ...

Today, DeepMind unveiled AlphaTensor, the “first artificial intelligence system" to shed light on a 50-year-old open question in mathematics.

A new technical paper titled “Scalable MatMul-free Language Modeling” was published by UC Santa Cruz, Soochow University, UC Davis, and LuxiTech. “Matrix multiplication (MatMul) typically dominates ...

Real PIM systems can provide high levels of parallelism, large aggregate memory bandwidth and low memory access latency, thereby being a good fit to accelerate the widely-used, memory-bound Sparse ...