Easily Train Models with H100 GPUs on NVIDIA DGX Cloud

Introducing Training Cluster as a Service - a new collaboration with NVIDIA

Accelerate ND-Parallel: A guide to Efficient Multi-GPU Training

NVIDIA's GTC 2025 Announcement for Physical AI Developers: New Open Models and Datasets

SUPREME: A Multi-GPU Framework for Reproducible Image Unlearning Method Evaluation

arXiv:2606. 00380v1 Announce Type: cross Abstract: Machine unlearning removes the influence of specific training data from a trained model without retraining it from scratch.

From Zero to GPU: A Guide to Building and Scaling Production-Ready CUDA Kernels

Bringing serverless GPU inference to Hugging Face users

Benchmarking Confidential GPU Inference on NVIDIA H100 under Intel TDX

arXiv:2607. 19353v1 Announce Type: new Abstract: Confidential computing is becoming a practical deployment requirement for AI inference workloads that process sensitive inputs or protect proprietary model assets.

Mistral AI partners with NVIDIA to accelerate open frontier models

Faster Training and Inference: Habana Gaudi®2 vs Nvidia A100 80GB

Extensions and limitations of the neural GPU

Waypoint-1.5: Higher-Fidelity Interactive Worlds for Everyday GPUs

Tessera: Unlocking Heterogeneous GPUs through Kernel-Granularity Disaggregation

arXiv:2604. 10180v2 Announce Type: replace-cross Abstract: Disaggregation maps parts of an AI workload to different types of GPUs, offering a path to utilize modern heterogeneous GPU clusters.