Summary of An Efficient Inference Framework For Early-exit Large Language Models, by Ruijie Miao et al.
An Efficient Inference Framework for Early-exit Large Language Models
by Ruijie Miao, Yihan Yan, Xinshuo Yao, Tong Yang
First submitted to arxiv on: 25 Jul 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper proposes a novel inference framework for early-exit models, which are variants of large language models (LLMs) designed for efficient inference. Early-exit models bypass subsequent layers and directly generate output tokens when confident, improving efficiency. However, existing LLM inference frameworks cannot be applied to early-exit models, making this work non-trivial. The authors address two key challenges: batch inference at iteration-level granularity and KV cache management. To achieve the former, they propose processing batches until all sequences surpass the early-exit confidence threshold. For the latter, they suggest filling the KV cache of remaining layers before iteration termination. Experimental results show that their solution achieves up to 1.25x speedup compared to the original vLLM operating at full layers. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper is about making computers work faster when processing language models. Language models are like super smart dictionaries that can understand and generate text. But, they take a lot of time to process. The authors want to make them work faster by skipping some steps when they’re sure about the answer. They came up with two ways to do this: one way is to stop processing once all the answers are found, and another way is to prepare for future questions while we’re still asking current ones. By doing this, they were able to make the computer work 1.25 times faster than before! |
Keywords
» Artificial intelligence » Inference
