This example demonstrates a practical pattern for running a persistent kernel on NVIDIA GPUs while hot-swapping device-side operators at runtime using NVRTC JIT and a device function-pointer jump ...

Abstract: This paper focuses on a distributed nonsmooth composite optimization problem over a multiagent networked system, in which each agent is equipped with a local Lipschitz-differentiable ...

Abstract: Distributed deep learning (DL) training constitutes a significant portion of workloads in modern data centers that are equipped with high computational capacities, such as GPU servers.

This project implements a federated learning (FL) system for Fashion-MNIST image classification, comparing federated and centralised approaches under various configurations (IID/Non-IID data, ...

Deep learning emerges as an important new resource-intensive workload and has been successfully applied in computer vision, speech, natural language processing, and so on. Distributed deep learning is ...