ipex-llm/python/llm/example/GPU/Pipeline-Parallel-Inference

Run IPEX-LLM on Multiple Intel GPUs in Pipeline Parallel Fashion

This example demonstrates how to run IPEX-LLM optimized low-bit model vertically partitioned on multiple Intel GPUs for Linux users.

Requirements

To run this example with IPEX-LLM on Intel GPUs, we have some recommended requirements for your machine, please refer to here for more information. For this particular example, you will need at least two GPUs on your machine.

Verified Models

• meta-llama/Llama-2-7b-chat-hf
• meta-llama/Llama-2-13b-chat-hf
• meta-llama/Meta-Llama-3-8B-Instruct
• Qwen/Qwen1.5-7B-Chat
• Qwen/Qwen1.5-14B-Chat
• Qwen/Qwen1.5-32B-Chat
• THUDM/chatglm3-6b
• baichuan-inc/Baichuan2-7B-Chat
• baichuan-inc/Baichuan2-13B-Chat
• microsoft/Phi-3-mini-4k-instruct
• microsoft/Phi-3-medium-4k-instruct

Example: Run pipeline parallel inference on multiple GPUs

0. Prerequisites

Please visit the Install IPEX-LLM on Linux with Intel GPU, follow Install Intel GPU Driver and Install oneAPI to install GPU driver and Intel® oneAPI Base Toolkit 2024.0.

1. Installation

conda create -n llm python=3.11
conda activate llm
# below command will install intel_extension_for_pytorch==2.1.10+xpu as default
pip install --pre --upgrade ipex-llm[xpu] --extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/
pip install oneccl_bind_pt==2.1.100 --extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/

2. Run pipeline parallel inference on multiple GPUs

For optimal performance, it is recommended to set several environment variables. We provide example usages as following:

Show Llama2 and Llama3 example

Run Llama-2-7b-chat-hf / Llama-2-13b-chat-hf / Meta-Llama-3-8B-Instruct on two Intel Arc A770

You could specify --repo-id-or-model-path in the test script to be the huggingface repo id for Llama2 / Llama3 to be downloaded, or the path to the huggingface checkpoint folder. Besides, you could change NUM_GPUS to the number of GPUs you have on your machine.

bash run_llama_arc_2_card.sh

Show Qwen1.5 example

Run Qwen1.5-7B-Chat / Qwen1.5-14B-Chat / Qwen1.5-32B-Chat on two Intel Arc A770

You could specify --repo-id-or-model-path in the test script to be the huggingface repo id for Qwen1.5 to be downloaded, or the path to the huggingface checkpoint folder. Besides, you could change NUM_GPUS to the number of GPUs you have on your machine.

pip install transformers==4.37.0
bash run_qwen1.5_arc_2_card.sh

Show chatglm example

Run chatglm3-6B on two Intel Arc A770

You could specify --repo-id-or-model-path in the test script to be the huggingface repo id for chatglm to be downloaded, or the path to the huggingface checkpoint folder. Besides, you could change NUM_GPUS to the number of GPUs you have on your machine.

bash run_chatglm_arc_2_card.sh

Show Baichuan2 example

Run Baichuan2-7B-Chat / Baichuan2-13B-Chat on two Intel Arc A770

You could specify --repo-id-or-model-path in the test script to be the huggingface repo id for Baichuan2 to be downloaded, or the path to the huggingface checkpoint folder. Besides, you could change NUM_GPUS to the number of GPUs you have on your machine.

pip install transformers==4.37.0
bash run_baichuan2_arc_2_card.sh

Show Phi3 example

Run Phi-3-mini-4k-instruct / Phi-3-medium-4k-instruct on two Intel Arc A770

You could specify --repo-id-or-model-path in the test script to be the huggingface repo id for Phi3 to be downloaded, or the path to the huggingface checkpoint folder. Besides, you could change NUM_GPUS to the number of GPUs you have on your machine.

pip install transformers==4.37.0
bash run_phi3_arc_2_card.sh

3. Sample Output

meta-llama/Llama-2-13b-chat-hf

Inference time: xxxx s
First token cost xxxx s and rest tokens cost average xxxx s
-------------------- Prompt --------------------
Once upon a time, there existed a little girl who liked to have adventures. She wanted to go to places and meet new people, and have fun
-------------------- Output --------------------
Once upon a time, there existed a little girl who liked to have adventures. She wanted to go to places and meet new people, and have fun. She was always asking her parents to take her on trips, but they were always too busy or too tired.

One day, the little girl