Compute Unified Device Architecture (CUDA) was developed as a GPU parallel programming platform and API, primarily designed for use with C/C++. Over the years, fundamental linear algebra ...

UC Santa Cruz researchers show that it is possible to eliminate the most computationally expensive element of running large language models, called matrix multiplication, while maintaining performance ...

#How To Use: 1-Start by changing the N_DIM definition in the code to the wanted matrix dimensions. 2-replace the matrix file and change the name of the file in "the read_mat_from_file ()" function.

Introduction 📚 This repository contains an optimized CUDA-based Matrix Multiplication code written in C++. The code leverages the power of GPU parallel computing to speed up matrix multiplication ...

Multiplying Matrices Matrix multiplication is one of the most fundamental and ubiquitous operations in all of mathematics. To multiply a pair of n -by- n matrices, each with n2 elements, you multiply ...

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