Triton Inference Server Release 20.11
The Triton Inference Server container image, release 20.11, is available on NGC and is open source on GitHub.
Contents of the Triton Inference Server container
The Triton Inference Server Docker image contains the inference server executable and related shared libraries in /opt/tritonserver.
- Ubuntu 18.04 including Python 3.6
- NVIDIA CUDA 11.1.0 including cuBLAS 11.2.1
- NVIDIA cuDNN 8.0.4
- NVIDIA NCCL 2.8.2 (optimized for NVLink™ )
- MLNX_OFED 5.1
- OpenMPI 4.0.5
- TensorRT 7.2.1
Driver Requirements
Release 20.11 is based on NVIDIA CUDA 11.1.0, which requires NVIDIA Driver release 455 or later. However, if you are running on Tesla (for example, T4 or any other Tesla board), you may use NVIDIA driver release 418.xx, 440.30, or 450.xx. The CUDA driver's compatibility package only supports particular drivers. For a complete list of supported drivers, see the CUDA Application Compatibility topic. For more information, see CUDA Compatibility and Upgrades.
GPU Requirements
Release 20.11 supports CUDA compute capability 6.0 and higher. This corresponds to GPUs in the NVIDIA Pascal, Volta, Turing, and Ampere Architecture GPU families. Specifically, for a list of GPUs that this compute capability corresponds to, see CUDA GPUs. For additional support details, see Deep Learning Frameworks Support Matrix.
Key Features and Enhancements
This Inference Server release includes the following key features and enhancements.
- ONNX Runtime backend updated to use ONNX Runtime 1.5.3.
- The PyTorch backend is moved to a dedicated repo: triton-inference-server/pytorch_backend.
- The Caffe2 backend is removed. Caffe2 models are no longer supported.
- Fixed handling of failed model reloads. If a model reload fails, the currently loaded version of the model will remain loaded and its availability will be uninterrupted.
- Releasing Triton ModelAnalyzer in the Triton SDK container and as a PIP package available in NVIDIA PyIndex.
- Refer to the 20.11 column of the Frameworks Support Matrix for container image versions that the 20.11 inference server container is based on.
- Ubuntu 18.04 with October 2020 updates.
NVIDIA Triton Inference Server Container Versions
The following table shows what versions of Ubuntu, CUDA, Triton Inference Server, and TensorRT are supported in each of the NVIDIA containers for Triton Inference Server. For older container versions, refer to the Frameworks Support Matrix.
| Container Version | Triton Inference Server | Ubuntu | CUDA Toolkit | TensorRT |
|---|---|---|---|---|
| 20.11 | 2.5.0 |
18.04 |
NVIDIA CUDA 11.1.0 | TensorRT 7.2.1 |
| 20.10 | 2.4.0 | |||
| 20.09 | 2.3.0 | NVIDIA CUDA 11.0.3 | TensorRT 7.1.3 | |
| 20.08 | ||||
| 20.07 | 1.15.0 | NVIDIA CUDA 11.0.194 | ||
| 20.06 | 1.14.0 | NVIDIA CUDA 11.0.167 | TensorRT 7.1.2 | |
| 20.03.1 | 1.13.0 | NVIDIA CUDA 10.2.89 | TensorRT 7.0.0 | |
| 20.03 | 1.12.0 | |||
| 1.11.0 | ||||
| 1.10.0 | ||||
| 1.9.0 | TensorRT 6.0.1 | |||
| 1.8.0 | ||||
| 19.10 | 1.7.0 | NVIDIA CUDA 10.1.243 | ||
| 19.09 | 1.6.0 | |||
| 19.08 | 1.5.0 | TensorRT 5.1.5 |
Known Issues
- Some versions of Google Kubernetes Engine (GKE) contain a regression in the handling of LD_LIBRARY_PATH that prevents the inference server container from running correctly (see issue 141255952). Use a GKE 1.13 or earlier version or a GKE 1.14.6 or later version to avoid this issue.