doc for Multi gpu selection (#9414)

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Xin Qiu 2023-11-20 09:25:58 +08:00 committed by GitHub
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- entries:
- file: doc/LLM/Overview/KeyFeatures/inference_on_gpu
- file: doc/LLM/Overview/KeyFeatures/finetune
- file: doc/LLM/Overview/KeyFeatures/multi_gpus_selection
- file: doc/LLM/Overview/examples
title: "Examples"
subtrees:

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@ -5,6 +5,10 @@ BigDL-LLM not only supports running large language models for inference, but als
* |inference_on_gpu|_
* `Finetune (QLoRA) <./finetune.html>`_
* `Multi GPUs selection <./multi_gpus_selection.html>`_
.. |inference_on_gpu| replace:: Inference on GPU
.. _inference_on_gpu: ./inference_on_gpu.html
.. |multi_gpus_selection| replace:: Multi GPUs selection
.. _multi_gpus_selection: ./multi_gpus_selection.html

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@ -14,6 +14,8 @@ You may run the LLMs using ``bigdl-llm`` through one of the following APIs:
* |inference_on_gpu|_
* `Finetune (QLoRA) <./finetune.html>`_
* `Multi GPUs selection <./multi_gpus_selection.html>`_
.. |transformers_style_api| replace:: ``transformers``-style API
.. _transformers_style_api: ./transformers_style_api.html
@ -26,3 +28,6 @@ You may run the LLMs using ``bigdl-llm`` through one of the following APIs:
.. |inference_on_gpu| replace:: Inference on GPU
.. _inference_on_gpu: ./inference_on_gpu.html
.. |multi_gpus_selection| replace:: Multi GPUs selection
.. _multi_gpus_selection: ./multi_gpus_selection.html

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# Multi Intel GPUs selection
In [Inference on GPU](inference_on_gpu.md) and [Finetune (QLoRA)](finetune.md), you have known how to run inference and finetune on Intel GPUs. In this section, we will show you two approaches to select GPU devices.
## List devices
The `sycl-ls` tool enumerates a list of devices available in the system. You can use it after you setup oneapi environment:
```bash
source /opt/intel/oneapi/setvars.sh
sycl-ls
```
If you have two Arc770 GPUs, you can get something like below:
```
[opencl:acc:0] Intel(R) FPGA Emulation Platform for OpenCL(TM), Intel(R) FPGA Emulation Device 1.2 [2023.16.7.0.21_160000]
[opencl:cpu:1] Intel(R) OpenCL, Intel(R) Core(TM) i9-14900K 3.0 [2023.16.7.0.21_160000]
[opencl:gpu:2] Intel(R) OpenCL Graphics, Intel(R) Arc(TM) A770 Graphics 3.0 [23.17.26241.33]
[opencl:gpu:3] Intel(R) OpenCL Graphics, Intel(R) Arc(TM) A770 Graphics 3.0 [23.17.26241.33]
[opencl:gpu:4] Intel(R) OpenCL Graphics, Intel(R) UHD Graphics 770 3.0 [23.17.26241.33]
[ext_oneapi_level_zero:gpu:0] Intel(R) Level-Zero, Intel(R) Arc(TM) A770 Graphics 1.3 [1.3.26241]
[ext_oneapi_level_zero:gpu:1] Intel(R) Level-Zero, Intel(R) Arc(TM) A770 Graphics 1.3 [1.3.26241]
[ext_oneapi_level_zero:gpu:2] Intel(R) Level-Zero, Intel(R) UHD Graphics 770 1.3 [1.3.26241]
```
This output shows there are two Arc A770 GPUs on this machine.
## Devices selection
To enable xpu, you should convert your model and input to xpu by below code:
```
model = model.to('xpu')
input_ids = tokenizer.encode(prompt, return_tensors="pt").to('xpu')
```
To select the desired devices, there are two ways: one is changing the code, another is adding an environment variable. See:
### 1. Select device in python
To specify a xpu, you can change the `to('xpu')` to `to('xpu:[device_id]')`, this device_id is counted from zero.
If you you want to use the second device, you can change the code like this:
```
model = model.to('xpu:1')
input_ids = tokenizer.encode(prompt, return_tensors="pt").to('xpu:1')
```
### 2. OneAPI device selector
Device selection environment variable, `ONEAPI_DEVICE_SELECTOR`, can be used to limit the choice of Intel GPU devices. As upon `sycl-ls` shows, the last three lines are three Level Zero GPU devices. So we can use `ONEAPI_DEVICE_SELECTOR=level_zero:[gpu_id]` to select devices.
For example, you want to use the second A770 GPU, you can run the python like this:
```
ONEAPI_DEVICE_SELECTOR=level_zero:1 python generate.py
```
`ONEAPI_DEVICE_SELECTOR=level_zero:1` in upon command only affect in current python program. Also, you can export the environment, then run your python:
```
export ONEAPI_DEVICE_SELECTOR=level_zero:1
python generate.py
```