Principle:Intel Ipex llm Offline Batch Inference
| Knowledge Sources | |
|---|---|
| Domains | NLP, Inference |
| Last Updated | 2026-02-09 00:00 GMT |
Overview
Method for generating text completions from multiple prompts in a single batch using the vLLM engine with sampling parameters.
Description
Offline batch inference processes a list of prompts through the vLLM engine simultaneously, leveraging continuous batching and PagedAttention for maximum throughput. SamplingParams controls the generation behavior (temperature, top-p, max tokens). The generate() method returns RequestOutput objects containing the prompt, generated text, and token-level information.
Usage
Use this for bulk text generation tasks such as dataset creation, evaluation, or benchmarking where real-time latency is not critical and throughput is the priority.
Theoretical Basis
# Abstract batch inference logic (NOT real implementation)
1. Create SamplingParams with temperature, top_p, max_tokens
2. Submit all prompts to vLLM engine
3. Engine schedules requests with continuous batching
4. PagedAttention manages KV cache across requests
5. Return completions as List[RequestOutput]