Abstract: Highly efficient parallel processing of photonic tensor cores is required for on-chip implementation of photonic neuromorphic algorithms. These photonic tensor cores are realized using ...

Enables TF32/BF16 Tensor Core fast paths in PyTorch via safe auto-detection, with auditable, reversible flag application and reproducible benchmarks. A reproducible performance protocol packaged as ...

Abstract: Since 2017, NVIDIA GPUs have been equipped with specialized units known as Tensor Cores, which demonstrate remarkable efficiency in processing matrix multiplications (GEMMs). Beyond GEMMs, ...

As large language model (LLM) inference demands ever-greater resources, there is a rapid growing trend of using low-bit weights to shrink memory usage and boost inference efficiency. However, these ...

This repository provides accurate tensor core models written in MATLAB. It also includes parts of the model validation data which is used to refine the models as shown in [1]. The initial analysis of ...

Calling it the largest advancement since the NVIDIA CUDA platform was inroduced in 2006, NVIDIA has launched CUDA 13.1 with CUDA Tile, which the company said introduces a virtual instruction set for ...

Google’s in-house Tensor chips have steadily improved over the years to become a reliable daily driver with solid battery efficiency. Still, performance has often been a sticking point. While previous ...

Tensor is the Pixel’s secret sauce, empowering the series with AI smarts you can’t find elsewhere and solid-enough performance and battery life to last the day. However, Google has been quieter than ...

CUDA and Tensor Cores are some of the most prominent specs on an NVIDIA GPU. These cores are the fundamental computational blocks that allow a GPU to perform a bunch of tasks such as video rendering, ...

James Ratcliff joined GameRant in 2022 as a Gaming News Writer. In 2023, James was offered a chance to become an occasional feature writer for different games and then a Senior Author in 2025. He is a ...