What role is left for decentralized GPU networks in AI?

As AI demand shifts from training to inference, decentralized networks emerge as a complementary layer for idle consumer hardware.
GitHub

Can Large Language Models Predict Parallel Code Performance?

We took this version of HeCBench and are modifying it to build the CUDA and OMP codes to gather their roofline performance data. So far we have a large portion of the CUDA and OMP codes building ...

Moore’s law: the famous rule of computing has reached the end of the road, so what comes next?

This phenomenon became known as Moore’s Law, after the businessman and scientist Gordon Moore. Moore’s Law summarised the ...
IEEE

cuFastTuckerPlusTC: a Stochastic Parallel Sparse FastTucker Decomposition Using GPU Tensor Cores

Abstract: Sparse tensors are prevalent in real-world applications, often characterized by their large-scale, high-order, and high dimensional nature. Directly handling raw tensors is impractical due ...
ExtremeTech

AMD May Not Launch More GPUs Until 2027

As if gamers needed any more reasons to be frustrated with the major hardware companies, AMD is now rumored not to be releasing any new graphics cards until sometime in 2027, after Nvidia has dropped ...
IEEE

Parallel Collaborative ADMM Privacy Computing and Adaptive GPU Acceleration for Distributed Edge Networks

Abstract: Distributed computing has been widely applied in distributed edge networks for reducing the processing burden of high-dimensional data centralization, where a high-dimensional computational ...
GitHub

IGN LiDAR HD Processing Library

A comprehensive Python library for processing French IGN LiDAR HD data into machine learning-ready datasets. Features include GPU acceleration, rich geometric features, RGB/NIR augmentation, and ...