This project explores the optimization of matrix multiplication using parallel computing techniques such as multithreading. Traditional matrix multiplication has a time complexity of O(n³), which ...

The purpose of this project is to compare execution time and performance of matrix multiplication across different approaches. The program provided with this research is written in CUDA and is ...

Matrix multiplication is one of the most commonly used algorithm in many applications including operations on relations in relational database system. In this paper, the authors study and evaluate the ...

Mathematicians love a good puzzle. Even something as abstract as multiplying matrices (two-dimensional tables of numbers) can feel like a game when you try to find the most efficient way to do it.

Abstract: It is known that the methods of distributed arithmetic can significantly improve the computational efficiency of calculating the inner products of two vectors. High efficiency is achieved in ...

Abstract: Trends in AI implementations, such as machine learning and deep learning, have been widely used in various studies. At the heart of AI computations such as speech recognition, image ...

Researchers at MIT's Computer Science & Artificial Intelligence Lab (CSAIL) have open-sourced Multiply-ADDitioN-lESS (MADDNESS), an algorithm that speeds up machine learning using approximate matrix ...