Kaldi Release 22.10

The NVIDIA container image for Kaldi, release 22.10 is available on NGC.

Contents of the Kaldi container

This container image contains the complete source of the version of Kaldi in the /opt/kaldi directory. The container also includes the following:

• Ubuntu 20.04 including Python 3.8
• NVIDIA CUDA® 11.8.0
• NVIDIA cuBLAS 11.11.3.6
• NVIDIA cuDNN 8.6.0.163
• NVIDIA NCCL 2.15.5
• rdma-core 36.0

• Nsight Compute 2022.3.0.22

• Nsight Systems 2022.4.2.1

• GDRCopy 2.3
• NVIDIA HPC-X 2.12.2tp1 with UCX 1.14.0
• NVIDIA TensorRT™ 8.5.0.12 for x64 Linux
• NVIDIA DALI® 1.18.0

Driver Requirements

Release 22.10 is based on CUDA 11.8.0, which requires NVIDIA Driver release 520 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), or 515.65 (or later R515). 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 11.8. For a complete list of supported drivers, see the CUDA Application Compatibility topic. For more information, see CUDA Compatibility and Upgrades.

GPU Requirements

Release 22.10 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. 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 Kaldi release includes the following key features and enhancements.

• Kaldi container image version 22.10 is based on Kaldi 26b9f648.
• Ubuntu 20.04 with September 2022 updates.

Packaged scripts

The Kaldi container comes with the following scripts:

• /workspace/nvidia-examples/librispeech/prepare_data.sh, which downloads a trained model and data.
• /workspace/nvidia-examples/librispeech/run_benchmark.sh, which runs inference on the trained model and data.

  Setting the ONLINE=1 environment variable makes the benchmark script run in online mode.

NVIDIA Kaldi Container Versions

The following table shows what versions of Ubuntu, CUDA, Kaldi, and TensorRT are supported in each of the NVIDIA containers for Kaldi. For older container versions, refer to the Frameworks Support Matrix.

Known Issues

None.