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 ...

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 ...

Abstract: Sparse Matrix-Multivector (SpMM) multiplication is a key kernel for deep learning models and scientific computing applications. However, achieving high performance for SpMM on GPUs is ...

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 ...

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 ...

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 ...

In this lesson, you'll be introduced to the basic mathematical entities used in linear algebra. We'll also look at how these entities are created (and later manipulated) in Python using NumPy. A ...

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 ...