ipex-llm/docker/llm/inference/xpu/docker
Shaojun Liu 5aa3e427a9
Fix docker images (#11362)
* Fix docker images

* add-apt-repository requires gnupg, gpg-agent, software-properties-common

* update

* avoid importing ipex again
2024-06-20 15:44:55 +08:00
..
benchmark.sh Quickstart: Run PyTorch Inference on Intel GPU using Docker (on Linux or WSL) (#10970) 2024-05-14 12:58:31 +08:00
chat.py Fix docker images (#11362) 2024-06-20 15:44:55 +08:00
Dockerfile Fix docker images (#11362) 2024-06-20 15:44:55 +08:00
README.md verify xpu-inference image and refine document (#10593) 2024-03-29 16:11:12 +08:00

Build/Use IPEX-LLM xpu image

Build Image

docker build \
  --build-arg http_proxy=.. \
  --build-arg https_proxy=.. \
  --build-arg no_proxy=.. \
  --rm --no-cache -t intelanalytics/ipex-llm-xpu:2.1.0-SNAPSHOT .

Use the image for doing xpu inference

To map the xpu into the container, you need to specify --device=/dev/dri when booting the container.

An example could be:

#/bin/bash
export DOCKER_IMAGE=intelanalytics/ipex-llm-xpu:2.1.0-SNAPSHOT

sudo docker run -itd \
        --net=host \
        --device=/dev/dri \
        --memory="32G" \
        --name=CONTAINER_NAME \
        --shm-size="16g" \
        $DOCKER_IMAGE

After the container is booted, you could get into the container through docker exec.

To verify the device is successfully mapped into the container, run sycl-ls to check the result. In a machine with Arc A770, the sampled output is:

root@arda-arc12:/# sycl-ls
[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, 13th Gen Intel(R) Core(TM) i9-13900K 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]
[ext_oneapi_level_zero:gpu:0] Intel(R) Level-Zero, Intel(R) Arc(TM) A770 Graphics 1.3 [1.3.26241]

To run inference using IPEX-LLM using xpu, you could refer to this documentation.