ipex-llm/python/llm/example/GPU/Speculative-Decoding

Self-Speculative Decoding for Large Language Model FP16 Inference using IPEX-LLM on Intel GPUs

You can use IPEX-LLM to run FP16 inference for any Huggingface Transformer model with self-speculative decoding on Intel GPUs. This directory contains example scripts to help you quickly get started to run some popular open-source models using self-speculative decoding. Each model has its own dedicated folder, where you can find detailed instructions on how to install and run it.

Verified Hardware Platforms

• Intel Data Center GPU Max Series

Recommended Requirements

To apply Intel GPU acceleration, there’re several steps for tools installation and environment preparation. See the GPU installation guide for mode details.

Step 1, only Linux system is supported now, Ubuntu 22.04 is prefered.

Step 2, please refer to our driver installation for general purpose GPU capabilities.

Note

: IPEX 2.1.10+xpu requires Intel GPU Driver version >= stable_775_20_20231219.

Step 3, you also need to download and install Intel® oneAPI Base Toolkit. OneMKL and DPC++ compiler are needed, others are optional.

Note

: IPEX 2.1.10+xpu requires Intel® oneAPI Base Toolkit's version == 2024.0.

Best Known Configuration on Linux

For optimal performance on Intel Data Center GPU Max Series, it is recommended to set several environment variables.

export LD_PRELOAD=${LD_PRELOAD}:${CONDA_PREFIX}/lib/libtcmalloc.so
export SYCL_PI_LEVEL_ZERO_USE_IMMEDIATE_COMMANDLISTS=1
export ENABLE_SDP_FUSION=1