Distributed training is a model training paradigm that involves spreading training workload across multiple worker nodes, therefore significantly improving the speed of training and model accuracy.

* Pre-train a GPT-2 (~124M-parameter) language model using PyTorch and Hugging Face Transformers. * Distribute training across multiple GPUs with Ray Train with minimal code changes. * Stream training ...

Abstract: We develop a distributed-memory algorithm to embed nodes of a graph into a low-dimensional vector space. Our distributed algorithm, called DistFNE, is based on a force-directed layout that ...

Abstract: To address the problem of personalized and ability-aware shared control for distributed drive electric vehicles, this paper proposes a hierarchical shared control framework that ...

Protocol project, hosted by the Linux Foundation, today announced major adoption milestones at its one-year mark, with more than 150 organizations supporting the standard, deep integration across ...