Monitor GPUs in Kubernetes using NVIDIA DCGM. This is an exporter for a Prometheus monitoring solution in Kubernetes.

dcgm-exporter

The NVIDIA Kubernetes Device Plugin registers GPUs as compute resources in the Kubernetes cluster.

k8s-device-plugin

gpu-operator-validator

Build and Run GPU Accelerated Docker Containers.

container-toolkit

Plugin for the Kubernetes Node Feature Discovery for adding GPU node labels.

gpu-feature-discovery

Triton Inference Server is an open source software that lets teams deploy trained AI models from any framework, from local or cloud storage and on any GPU- or CPU-based infrastructure in the cloud, data center, or embedded devices.

tritonserver

Provision NVIDIA GPU Driver as a Container

driver

Manages NVIDIA Driver upgrades in Kubernetes cluster.

k8s-driver-manager

CUDA is a parallel computing platform and programming model that enables dramatic increases in computing performance by harnessing the power of the NVIDIA GPUs.

cuda

Docker containers distributed as part of the TAO Toolkit package

tao-toolkit

Deploy and Manage NVIDIA GPU resources in Kubernetes.

gpu-operator

Manage and Monitor GPUs in Cluster Environments.

dcgm

PyTorch is a GPU accelerated tensor computational framework. Functionality can be extended with common Python libraries such as NumPy and SciPy. Automatic differentiation is done with a tape-based system at the functional and neural network layer levels.

pytorch

TensorFlow is an open source platform for machine learning. It provides comprehensive tools and libraries in a flexible architecture allowing easy deployment across a variety of platforms and devices.

tensorflow

Manage MIG partitions in Kubernetes with a simple label change to a node.

k8s-mig-manager

NVIDIA TensorRT is a C++ library that facilitates high-performance inference on NVIDIA graphics processing units (GPUs). TensorRT takes a trained network and produces a highly optimized runtime engine that performs inference for that network.

tensorrt

NVIDIA Optimized Deep Learning Framework, powered by Apache MXNet is a deep learning framework that allows you to mix the flavors of symbolic programming and imperative programming to maximize efficiency and productivity.

mxnet

DeepStream SDK delivers a complete streaming analytics toolkit for AI based video and image understanding and multi-sensor processing. This container is for NVIDIA Enterprise GPUs.

deepstream

NVIDIA NeMo™ framework supports enterprise development of LLMs and generative AI models with automated data processing, model training techniques, and flexible deployment options.

nemo

Allegro Trains delivers an optimized, seamless, and scalable solution for training on DGX machines with ML-Ops and experiment management features.

trains-agent

Riva Speech Skills is a scalable Conversational AI service platform.

riva-speech

NVIDIA L4T is a Linux based software distribution for the NVIDIA Jetson embedded computing platform.

l4t-base

The NVIDIA HPC-Benchmarks collection provides four accelerated HPC benchmarks: HPL-NVIDIA, HPL-MxP-NVIDIA, HPCG-NVIDIA, and STREAM.

hpc-benchmarks

The RAPIDS suite of software libraries gives you the freedom to execute end-to-end data science and analytics pipelines entirely on GPUs.

notebooks

DOCA Telemetry Service (DTS) is a DOCA Service for collecting and exporting telemetry data. Both predefined and user-defined telemetry counters are available and the export is made by Prometheus or Fluent Bit.

doca_telemetry

Python Basic - AI Workbench Default Container (Beta)

python-basic

Python with CUDA 12.0 - AI Workbench Default Container (Beta)

python-cuda120

Python with CUDA 12.2 - AI Workbench Default Container (Beta)