| .. | ||
| chat.py | ||
| Dockerfile | ||
| README.md | ||
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.