Abstract: Half-precision matrix multiply has played a key role in the training of deep learning models. The newly designed Nvidia Tensor Cores offer the native instructions for half-precision small ...

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 ...

Hi, thanks for your great work on Transformer Engine! I am working on a project that requires high-performance batched matrix multiplication (i.e., 3D tensor multiplication) where all inputs are ...

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 ...

AlphaTensor, builds upon AlphaZero, an agent that has shown superhuman performance on board games, like chess, Go and shogi, and this work shows the journey of AlphaZero from playing games to tackling ...

Abstract: Multi-dimensional arrays, or tensors, are increasingly found in fields such as signal processing and recommender systems. Real-world tensors can be enormous in size and often very sparse.

Researchers have created a new system that automatically produces code optimized for sparse data. We live in the age of big data, but most of that data is "sparse." Imagine, for instance, a massive ...

We live in the age of big data, but most of that data is "sparse." Imagine, for instance, a massive table that mapped all of Amazon's customers against all of its products, with a "1" for each product ...

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 ...