## deepspeed docker image build

```shell
docker-compose -f docker-compose_pytorch1.13.yml build
docker-compose -f docker-compose_pytorch2.3.yml build
```

## test command

```shell
docker run -it --gpus all --name deepspeed_test --shm-size=1gb --rm hotwa/deepspeed:latest /bin/bash
```

## [查询GPU 架构 给变量赋值](https://blog.csdn.net/zong596568821xp/article/details/106411024)

```shell
git clone https://github.com/NVIDIA-AI-IOT/deepstream_tlt_apps.git
cd deepstream_tlt_apps/TRT-OSS/x86
nvcc deviceQuery.cpp -o deviceQuery
./deviceQuery
```

H100 输出

```shell
(base) root@node19:~/bgpt/deepstream_tlt_apps/TRT-OSS/x86# ./deviceQuery
Detected 8 CUDA Capable device(s)

Device 0: "NVIDIA H100 80GB HBM3"
  CUDA Driver Version / Runtime Version          12.4 / 10.1
  CUDA Capability Major/Minor version number:    9.0

Device 1: "NVIDIA H100 80GB HBM3"
  CUDA Driver Version / Runtime Version          12.4 / 10.1
  CUDA Capability Major/Minor version number:    9.0

Device 2: "NVIDIA H100 80GB HBM3"
  CUDA Driver Version / Runtime Version          12.4 / 10.1
  CUDA Capability Major/Minor version number:    9.0

Device 3: "NVIDIA H100 80GB HBM3"
  CUDA Driver Version / Runtime Version          12.4 / 10.1
  CUDA Capability Major/Minor version number:    9.0

Device 4: "NVIDIA H100 80GB HBM3"
  CUDA Driver Version / Runtime Version          12.4 / 10.1
  CUDA Capability Major/Minor version number:    9.0

Device 5: "NVIDIA H100 80GB HBM3"
  CUDA Driver Version / Runtime Version          12.4 / 10.1
  CUDA Capability Major/Minor version number:    9.0

Device 6: "NVIDIA H100 80GB HBM3"
  CUDA Driver Version / Runtime Version          12.4 / 10.1
  CUDA Capability Major/Minor version number:    9.0

Device 7: "NVIDIA H100 80GB HBM3"
  CUDA Driver Version / Runtime Version          12.4 / 10.1
  CUDA Capability Major/Minor version number:    9.0

```