Add deepspeed autotp example readme (#9289)

* Add deepspeed autotp example readme

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Yang Wang 2023-10-28 04:04:38 +08:00 committed by GitHub
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# Run BigDL-LLM on Multiple Intel GPUs using DeepSpeed AutoTP
This example demonstrates how to run BigDL-LLM optimized low-bit model on multiple [Intel GPUs](../README.md) by leveraging DeepSpeed AutoTP.
## 0. Requirements
To run this example with BigDL-LLM on Intel GPUs, we have some recommended requirements for your machine, please refer to [here](../README.md#recommended-requirements) for more information. For this particular example, you will need at least two GPUs on your machine.
## Example:
### 1. Install
```bash
conda create -n llm python=3.9
conda activate llm
# below command will install intel_extension_for_pytorch==2.0.110+xpu as default
# you can install specific ipex/torch version for your need
pip install --pre --upgrade bigdl-llm[xpu] -f https://developer.intel.com/ipex-whl-stable-xpu
pip install oneccl_bind_pt==2.0.100 -f https://developer.intel.com/ipex-whl-stable-xpu
pip install git+https://github.com/microsoft/DeepSpeed.git@78c518e
pip install git+https://github.com/intel/intel-extension-for-deepspeed.git@ec33277
pip install mpi4py
```
### 2. Configures OneAPI environment variables
```bash
source /opt/intel/oneapi/setvars.sh
```
### 3. Run tensor parallel inference on multiple GPUs
You many want to change some of the parameters in the script such as `NUM_GPUS`` to the number of GPUs you have on your machine.
```
bash run.sh
```

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source bigdl-llm-init -t -g
export MASTER_ADDR=127.0.0.1
export CCL_ZE_IPC_EXCHANGE=sockets
NUM_GPUS=4
if [[ -n $OMP_NUM_THREADS ]]; then
export OMP_NUM_THREADS=$(($OMP_NUM_THREADS / 4))
export OMP_NUM_THREADS=$(($OMP_NUM_THREADS / $NUM_GPUS))
else
export OMP_NUM_THREADS=$(($(nproc) / 4))
export OMP_NUM_THREADS=$(($(nproc) / $NUM_GPUS))
fi
torchrun --standalone \
--nnodes=1 \
--nproc-per-node 4 \
--nproc-per-node $NUM_GPUS \
deepspeed_autotp.py --repo-id-or-model-path "meta-llama/Llama-2-7b-hf"