Principle:Intel Ipex llm Pipeline Parallel Init
| Knowledge Sources | |
|---|---|
| Domains | Distributed_Computing, Inference |
| Last Updated | 2026-02-09 00:00 GMT |
Overview
Technique for initializing pipeline parallelism communication across multiple Intel GPUs for distributed model inference.
Description
Pipeline Parallel Initialization sets up the inter-GPU communication layer required to distribute model layers across multiple Intel XPU devices. It relies on torch.distributed (initialized by mpirun) and configures IPEX-LLM's internal pipeline parallel communication. This must be called before model loading, as the model needs to know how many pipeline stages (GPUs) are available to distribute its layers.
Usage
Use this as the first API call in any multi-GPU pipeline parallel inference script, after the MPI environment is set up by mpirun. Must be called before AutoModelForCausalLM.from_pretrained with pipeline_parallel_stages.
Theoretical Basis
# Abstract pipeline parallel concept (NOT real implementation)
# Given a model with L layers and N GPUs:
# GPU 0: layers 0..L/N-1
# GPU 1: layers L/N..2L/N-1
# ...
# GPU N-1: layers (N-1)*L/N..L-1
# Forward pass: data flows GPU0 -> GPU1 -> ... -> GPUN-1
# Only last GPU produces output tokens