This PyG container release is intended for use on the NVIDIA® Ampere Architecture GPU, NVIDIA A100, and the associated NVIDIA CUDA® 12 and NVIDIA cuDNN 8 libraries.
Driver Requirements
Release 23.01 is based on CUDA 12.0.1, which requires NVIDIA Driver release 525 or later. However, if you are running on a data center GPU (for example, T4 or any other data center GPU), you can use NVIDIA driver release 450.51 (or later R450), 470.57 (or later R470), 510.47 (or later R510), 515.65 (or later R515), or 525.85 (or later R525). The CUDA driver's compatibility package only supports particular drivers. Thus, users should upgrade from all R418, R440, and R460 drivers, which are not forward-compatible with CUDA 12.0. For a complete list of supported drivers, see the CUDA Application Compatibility topic. For more information, see CUDA Compatibility and Upgrades.
Contents of the PyG container
This container image includes the complete source of the NVIDIA version of DGL in /opt/pyg/pytorch_geometric. It is prebuilt and installed as a system Python module
The container also includes the following:
- torch-geometric 2.2.0
- RAPIDS 22.12
- NVIDIA CUDA® 12.0.1
- NVIDIA cuBLAS from CUDA 12.0.1
- NVIDIA cuDNN 8.7.0
- NVIDIA NCCL 2.16.5 (optimized for NVIDIA NVLink®)
- Apex
- rdma-core 36.0
- NVIDIA HPC-X 2.13
- OpenMPI 4.1.4+
- GDRCopy 2.3
- TensorBoard 2.9.0
- Nsight Compute 2022.4.1.6
- Nsight Systems 2022.5.1
- NVIDIA TensorRT™ 8.5.2.2
- Torch-TensorRT 1.4.0dev0
- NVIDIA DALI® 1.21.0
- MAGMA 2.6.2
- JupyterLab 2.3.2 including Jupyter-TensorBoard
- PyTorch quantization wheel 2.1.2
- TransformerEngine 0.4
GPU Requirements
Release 23.01 supports CUDA compute capability 6.0 and later. This corresponds to GPUs in the NVIDIA Pascal, NVIDIA Volta™, NVIDIA Turing™, NVIDIA Ampere architecture, and NVIDIA Hopper™ architecture families. For a list of GPUs to which this compute capability corresponds, see CUDA GPUs. For additional support details, see Deep Learning Frameworks Support Matrix.
Key Features and Enhancements
This PyG release includes the following key features and enhancements.
- PyG container image version 23.01 is based on PyTorch Geometric 2.2.0. The major features of the release can be found in the PyG release notes.
NVIDIA PyG Container Versions
The following table shows what versions of Ubuntu, CUDA, PyG (PyTorch Geometric), and PyTorch are supported in each of the NVIDIA containers for PyG.
| Container Version | Ubuntu | CUDA Toolkit | PyG | PyTorch |
|---|---|---|---|---|
| 23.01 | 20.04 | NVIDIA CUDA 12.0.1 | 2.2.0 | 23.01 |
Known Issues
None.