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IPEX-LLM Installation: CPU

Quick Installation

Install IPEX-LLM for CPU supports using pip through:

  • For Linux users:

    pip install --pre --upgrade ipex-llm[all] --extra-index-url https://download.pytorch.org/whl/cpu
  • For Windows users:

    pip install --pre --upgrade ipex-llm[all]

Please refer to Environment Setup for more information.

Note

all option will trigger installation of all the dependencies for common LLM application development.

Important

ipex-llm is tested with Python 3.9, 3.10 and 3.11; Python 3.11 is recommended for best practices.

Recommended Requirements

Here list the recommended hardware and OS for smooth IPEX-LLM optimization experiences on CPU:

  • Hardware

    • PCs equipped with 12th Gen Intel® Core™ processor or higher, and at least 16GB RAM
    • Servers equipped with Intel® Xeon® processors, at least 32G RAM.
  • Operating System

    • Ubuntu 20.04 or later
    • CentOS 7 or later
    • Windows 10/11, with or without WSL

Environment Setup

For optimal performance with LLM models using IPEX-LLM optimizations on Intel CPUs, here are some best practices for setting up environment:

First we recommend using Conda to create a python 3.11 enviroment:

  • For Linux users:

    conda create -n llm python=3.11
    conda activate llm
    
    pip install --pre --upgrade ipex-llm[all] --extra-index-url https://download.pytorch.org/whl/cpu
  • For Windows users:

    conda create -n llm python=3.11
    conda activate llm
    
    pip install --pre --upgrade ipex-llm[all]

Then for running a LLM model with IPEX-LLM optimizations (taking an example.py an example):

  • For running on Client:

    It is recommended to run directly with full utilization of all CPU cores:

    python example.py
  • For running on Server:

    It is recommended to run with all the physical cores of a single socket:

    # e.g. for a server with 48 cores per socket
    export OMP_NUM_THREADS=48
    numactl -C 0-47 -m 0 python example.py