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build : Add Moore Threads GPU support and update GitHub workflow for MUSA build (#3069)

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* Update PATH for main/main-cuda container

Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>

* Add Dockerfile for musa, .dockerignore and update CI

Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>

* Add Moore Threads GPU Support in README.md and replace ./main with whisper-cli

Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>

* Forward GGML_CUDA/GGML_MUSA to cmake in Makefile

Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>

* Minor updates for PATH ENV in Dockerfiles

Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>

* Address comments

Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>

---------

Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>
This commit is contained in:
R0CKSTAR
2025-04-28 11:06:41 +03:00
committed by GitHub
parent f9b2dfdd8c
commit 50218b935d
7 changed files with 62 additions and 7 deletions
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README.md
+23 -2
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@@ -23,6 +23,7 @@ High-performance inference of [OpenAI's Whisper](https://github.com/openai/whisp
- [Efficient GPU support for NVIDIA](#nvidia-gpu-support)
- [OpenVINO Support](#openvino-support)
- [Ascend NPU Support](#ascend-npu-support)
- [Moore Threads GPU Support](#moore-threads-gpu-support)
- [C-style API](https://github.com/ggml-org/whisper.cpp/blob/master/include/whisper.h)
Supported platforms:
@@ -381,6 +382,25 @@ Run the inference examples as usual, for example:
- If you have trouble with Ascend NPU device, please create a issue with **[CANN]** prefix/tag.
- If you run successfully with your Ascend NPU device, please help update the table `Verified devices`.
## Moore Threads GPU support
With Moore Threads cards the processing of the models is done efficiently on the GPU via muBLAS and custom MUSA kernels.
First, make sure you have installed `MUSA SDK rc3.1.1`: https://developer.mthreads.com/sdk/download/musa?equipment=&os=&driverVersion=&version=rc3.1.1
Now build `whisper.cpp` with MUSA support:
```
cmake -B build -DGGML_MUSA=1
cmake --build build -j --config Release
```
or specify the architecture for your Moore Threads GPU. For example, if you have a MTT S80 GPU, you can specify the architecture as follows:
```
cmake -B build -DGGML_MUSA=1 -DMUSA_ARCHITECTURES="21"
cmake --build build -j --config Release
```
## FFmpeg support (Linux only)
If you want to support more audio formats (such as Opus and AAC), you can turn on the `WHISPER_FFMPEG` build flag to enable FFmpeg integration.
@@ -425,6 +445,7 @@ We have two Docker images available for this project:
1. `ghcr.io/ggml-org/whisper.cpp:main`: This image includes the main executable file as well as `curl` and `ffmpeg`. (platforms: `linux/amd64`, `linux/arm64`)
2. `ghcr.io/ggml-org/whisper.cpp:main-cuda`: Same as `main` but compiled with CUDA support. (platforms: `linux/amd64`)
3. `ghcr.io/ggml-org/whisper.cpp:main-musa`: Same as `main` but compiled with MUSA support. (platforms: `linux/amd64`)
### Usage
@@ -437,11 +458,11 @@ docker run -it --rm \
docker run -it --rm \
-v path/to/models:/models \
-v path/to/audios:/audios \
whisper.cpp:main "./main -m /models/ggml-base.bin -f /audios/jfk.wav"
whisper.cpp:main "whisper-cli -m /models/ggml-base.bin -f /audios/jfk.wav"
# transcribe an audio file in samples folder
docker run -it --rm \
-v path/to/models:/models \
whisper.cpp:main "./main -m /models/ggml-base.bin -f ./samples/jfk.wav"
whisper.cpp:main "whisper-cli -m /models/ggml-base.bin -f ./samples/jfk.wav"
```
## Installing with Conan