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CUDA version and updated installation instructions (#785)

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* CUDA version note and updated instructions in README

* ctranslate2 downgrade note, cuDNN v9 consideration

* clearer note on cuDNN v9 package
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Sidharth Rajaram
2024-05-04 01:09:59 -07:00
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@@ -75,28 +75,35 @@ Unlike openai-whisper, FFmpeg does **not** need to be installed on the system. T
GPU execution requires the following NVIDIA libraries to be installed:
* [cuBLAS for CUDA 11](https://developer.nvidia.com/cublas)
* [cuDNN 8 for CUDA 11](https://developer.nvidia.com/cudnn)
* [cuBLAS for CUDA 12](https://developer.nvidia.com/cublas)
* [cuDNN 8 for CUDA 12](https://developer.nvidia.com/cudnn)
There are multiple ways to install these libraries. The recommended way is described in the official NVIDIA documentation, but we also suggest other installation methods below.
**Note**: Latest versions of `ctranslate2` support CUDA 12 only. For CUDA 11, the current workaround is downgrading to the `3.24.0` version of `ctranslate2` (This can be done with `pip install --force-reinsall ctranslate2==3.24.0` or specifying the version in a `requirements.txt`).
There are multiple ways to install the NVIDIA libraries mentioned above. The recommended way is described in the official NVIDIA documentation, but we also suggest other installation methods below.
<details>
<summary>Other installation methods (click to expand)</summary>
**Note:** For all these methods below, keep in mind the above note regarding CUDA versions. Depending on your setup, you may need to install the _CUDA 11_ versions of libraries that correspond to the CUDA 12 libraries listed in the instructions below.
#### Use Docker
The libraries are installed in this official NVIDIA Docker image: `nvidia/cuda:11.8.0-cudnn8-runtime-ubuntu22.04`.
The libraries (cuBLAS, cuDNN) are installed in these official NVIDIA CUDA Docker images: `nvidia/cuda:12.0.0-runtime-ubuntu20.04` or `nvidia/cuda:12.0.0-runtime-ubuntu22.04`.
#### Install with `pip` (Linux only)
On Linux these libraries can be installed with `pip`. Note that `LD_LIBRARY_PATH` must be set before launching Python.
```bash
pip install nvidia-cublas-cu11 nvidia-cudnn-cu11
pip install nvidia-cublas-cu12 nvidia-cudnn-cu12
export LD_LIBRARY_PATH=`python3 -c 'import os; import nvidia.cublas.lib; import nvidia.cudnn.lib; print(os.path.dirname(nvidia.cublas.lib.__file__) + ":" + os.path.dirname(nvidia.cudnn.lib.__file__))'`
```
**Note**: Version 9+ of `nvidia-cudnn-cu12` appears to cause issues due its reliance on cuDNN 9 (Faster-Whisper does not currently support cuDNN 9). Ensure your version of the Python package is for cuDNN 8.
#### Download the libraries from Purfview's repository (Windows & Linux)
Purfview's [whisper-standalone-win](https://github.com/Purfview/whisper-standalone-win) provides the required NVIDIA libraries for Windows & Linux in a [single archive](https://github.com/Purfview/whisper-standalone-win/releases/tag/libs). Decompress the archive and place the libraries in a directory included in the `PATH`.