NVIDIA Cloud Functions (NVCF)
…It provides a single unified API for distributed multi-node inference that simplifies scaling and operations for even the most complex workloads and accelerates time to market. NVIDIA Cloud Functions Key Features…
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What other optimizers does NVIDIA support for research?
In addition to Muon, NVIDIA also supports many other optimizers for the research community to explore, including: The ultimate form of orthogonalized optimizer MOP (Momentum Orthogonalized by Polar decomposition) An advanced SOAP variant that updates eigen basis per step with eigen decomposition plus KL correction in REKLS
Advancing Emerging Optimizers for Accelerated LLM Training with NVIDIA Megatron | NVIDIA Technical BlogValidate Kubernetes for GPU Infrastructure with Layered, Reproducible Recipes | NVIDIA Technical Blog
…The project supports community contributions, enables organization-specific extensions, and updates recipes as new validated configurations are available, with ongoing development for broader platform and workload support. AI-generated content may summarize…
Unlock Exascale Performance on NVIDIA GB200 NVL72 with Slurm Topology-Aware Job Scheduling | NVIDIA Technical Blog
…His current role focuses on advancing AI platforms and infrastructure to optimize machine learning pipelines, improve developer productivity, and support innovative AI solutions. His expertise includes managing geo-distributed teams and scaling…
Accelerating Federated Learning Research with AI Agents and NVIDIA FLARE Auto-FL | NVIDIA Technical Blog
…A task profile can define a supported strategy surface with FedAvg, FedOpt-style server updates, FedAdam, SCAFFOLD, median aggregation, and FedProx hooks. Auto-FL can also support bounded architecture search. That matters…
Unlock Massive Token Throughput with GPU Fractioning in NVIDIA Run:ai | NVIDIA Technical Blog
…This is particularly impactful for inference workloads, where smaller, concurrent requests can share GPU resources without significant performance degradation. Memory isolation is enforced at runtime while compute cycles are distributed fairly among…
Federated Learning Without the Refactoring Overhead Using NVIDIA FLARE | NVIDIA Technical Blog
…A practical federated computing platform needs to support: No data copy: Data stays local, and only model updates (or equivalent signals) move. Compliance posture: Deployment and governance controls that support sovereignty and…
Build and Stream Browser-Based XR Experiences with NVIDIA CloudXR.js | NVIDIA Technical Blog
…Developers can integrate CloudXR.js with various web frameworks and utilize provided WebGL and React sample clients for rapid prototyping, while production deployments are supported with Docker, WebSocket proxy configurations, and compatibility…
Automate Kubernetes AI Cluster Health with NVSentinel | NVIDIA Technical Blog
…If your environment supports the GPU Operator and DCGM, NVSentinel can monitor and act on GPU-level faults. Supported NVIDIA hardware includes all data center GPUs supported by DCGM, such as: NVIDIA…
Scaling Autonomous AI Agents and Workloads with NVIDIA DGX Spark | NVIDIA Technical Blog
…Scaling is now supported up to four DGX Spark nodes with low-latency RoCE communication, allowing fine-tuning and inference on models up to 700B parameters; near-linear performance scaling is achievable…
Advancing AI Infrastructure for Agentic AI with NVIDIA DOCA In-Silicon Security | NVIDIA Technical Blog
…As AI factories scale to support increasingly distributed and autonomous workloads, network communication becomes a critical attack surface. DOCA Flow enables security policies to be enforced directly within the infrastructure layer, preventing…