Abstract: We propose an efficient quantum subroutine for matrix multiplication that computes a state vector encoding the entries of the product of two matrices in superposition. The subroutine ...

Have you ever faced the daunting task of identifying and prioritizing risks in a project, only to feel overwhelmed by the sheer complexity of it all? Whether you’re managing a multi-million-dollar ...

Have you ever found yourself wrestling with Excel formulas, wishing for a more powerful tool to handle your data? Or maybe you’ve heard the buzz about Python in Excel and wondered if it’s truly the ...

Google DeepMind’s AI systems have taken big scientific strides in recent years — from predicting the 3D structures of almost every known protein in the universe to forecasting weather more accurately ...

Abstract: While the Karatsuba algorithm reduces the complexity of large integer multiplication, the extra additions required minimize its benefits for smaller integers of more commonly-used bitwidths.

Discover how nvmath-python leverages NVIDIA CUDA-X math libraries for high-performance matrix operations, optimizing deep learning tasks with epilog fusion, as detailed by Szymon Karpiński.

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 ...