This collection contains performance-optimized Deep Learning frameworks.
Deep Learning Frameworks Collection
This collection provides performance-optimized Deep Learning Frameworks containers to AI practitioners for developing and deploying their solutions on any GPU-accelerated on-prem, cloud, and edge systems.
These containers from the NGC catalog are optimized for GPU acceleration, and contain a validated set of libraries that enable and optimize GPU performance. These containers also contains software for accelerating ETL (DALI, RAPIDS), Training (cuDNN, NCCL), and Inference (TensorRT) workloads.
NVIDIA releases a new version of these containers monthly with optimized libraries, giving users higher training and inference performance on the same GPU-powered system.
Visit each DLFW container page to view detailed instructions on running the specific container.
Resources
See the latest Release Notes on NVIDIA Optimized Frameworks Release Notes page.
For a full list of the supported software and specific versions that come packaged with this framework based on the container image, see the Frameworks Support Matrix.
License
By pulling and using the container, you accept the terms and conditions of this End User License Agreement and Product-Specific Terms.
- AI
- Automatic Speech Recognition
- Computer Vision
- Conversational AI
- CUDA
- CUDA Toolkit
- DL
- Graph Neural Networks
- Inference
- Natural Language Processing
- Natural Language Understanding
- NVIDIA AI
- Object Detection
- PyTorch
- Question Answering
- RAPIDS
- Recommendation
- Recommender Systems
- Speech to Text
- TensorFlow
- TensorRT
- Text to Speech
- Translation