High-performance matrix multiplication remains a cornerstone of numerical computing, underpinning a wide array of applications from scientific simulations to machine learning. Researchers continually ...

This repository contains Python implementations and verifications of various matrix multiplication algorithms, with a special focus on novel algorithms discovered by systems like Google DeepMind's ...

This project focuses on accelerating matrix multiplication—a core operation in many machine learning and signal processing applications—using the Gemmini hardware accelerator integrated within the ...

Abstract: Matrix multiplication is one of the main issues in matrix calculus. The multiplication of small-scale matrices does not cause any difficulties while multiplying of large-scale matrices ...

Abstract: The paper presents a novel methodology to implement resource efficient 64-bit floating point matrix multiplication algorithm using FPGA. Approach uses systolic architecture using four ...

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There has been an ever-growing demand for artificial intelligence and fifth-generation communications globally, resulting in very large computing power and memory requirements. The slowing down or ...

Researchers claim to have developed a new way to run AI language models more efficiently by eliminating matrix multiplication from the process. This fundamentally redesigns neural network operations ...

AMD software programmers have begun to distribute new fixes for the forthcoming GFX11 architecture, also known as RDNA3. According to a recent patch, AMD is working on their own instructions that can ...