With AlphaTensor, DeepMind Technologies has presented an AI system that is supposed to independently find novel, efficient and provably correct algorithms for complex mathematical tasks. AlphaTensor ...

This suggests that for this specific hardware (6 physical cores), oversubscribing with more threads/processes than physical cores generally does not yield significant benefits and can be detrimental ...

We’re just a few years into the AI revolution, but AI systems are already improving decades-old computer science algorithms. Google’s AlphaEvolve AI, its latest coding agent for algorithm discovery, ...

This project implements matrix multiplication module using Verilog. It takes various approaches to solve matrix multiplication with each of it's pro's and con's explained. Matrix multiplication is a ...

Improving the efficiency of algorithms for fundamental computations can have a widespread impact, as it can affect the overall speed of a large amount of computations. Matrix multiplication is one ...

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: Matrix multiplication serves as a critical operation in neural networks and scientific computing, where algorithmic improvements can significantly impact execution speed. Existing optimized ...

Multiplying the content of two x-y matrices together for screen rendering and AI processing. Matrix multiplication provides a series of fast multiply and add operations in parallel, and it is built ...