GitHub

Towards GPU-Native SfM for the Deep Learning Era

Note: The project requires an NVIDIA GPU with CUDA support. The code is tested on Ubuntu 20.04 with CUDA 12.1 and PyTorch 2.3.1. Windows system is strongly ...
IEEE

High Performance Unstructured SpMM Computation Using Tensor Cores

High-performance sparse matrix-matrix (SpMM) multiplication is paramount for science and industry, as the ever-increasing sizes of data prohibit using dense data structures. Yet, existing hardware, ...
The Next Platform

Tensordyne Converts AI Matrix Math To Logs To Crank Up Inference Oomph

Transformations are the key to such codes, and they rely on math that predates computing as we know it by centuries. There ...
CNBC

Upstart chipmakers keep challenging Nvidia. This time it's Microsoft-backed D-Matrix

D-Matrix says its chips can run inference workloads 10 times faster and using five times less energy than a standalone graphics processing unit from Nvidia. Like Cerebras, D-Matrix is trying to prove ...
IEEE

Sparse Antenna Array with Metagratings for Wide-angle Beamforming and Grating-lobe Suppression

Abstract: This work presents a metagrating (MG)-assisted sparse array based on a unified analytical and practical design framework. A Floquet-Bloch (F-B) modal approach is developed with practical ...