Speculative Decoding: Exploiting Speculative Execution for Accelerating Seq2seq Generation

• URL: http://arxiv.org/abs/2203.16487v6
• Date: Mon, 30 Oct 2023 01:36:06 GMT
• Title: Speculative Decoding: Exploiting Speculative Execution for Accelerating Seq2seq Generation
• Authors: Heming Xia, Tao Ge, Peiyi Wang, Si-Qing Chen, Furu Wei, Zhifang Sui
• Abstract summary: We propose Speculative Decoding (SpecDec) to study exploiting the idea of speculative execution to accelerate autoregressive (AR) decoding. SpecDec has two innovations: Spec-Drafter -- an independent model specially optimized for efficient drafting, and Spec-Verification -- a reliable method for verifying the drafted tokens efficiently.
• Score: 80.2267931231335
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We propose Speculative Decoding (SpecDec), for the first time ever, to formally study exploiting the idea of speculative execution to accelerate autoregressive (AR) decoding. Speculative Decoding has two innovations: Spec-Drafter -- an independent model specially optimized for efficient and accurate drafting -- and Spec-Verification -- a reliable method for verifying the drafted tokens efficiently in the decoding paradigm. Experimental results on various seq2seq tasks including machine translation and abstractive summarization show our approach can achieve around $5\times$ speedup for the popular Transformer architectures with comparable generation quality to beam search decoding, refreshing the impression that the draft-then-verify paradigm introduces only $1.4\times$$\sim$$2\times$ speedup. In addition to the remarkable speedup, we also demonstrate 3 additional advantages of SpecDec, revealing its practical value for accelerating generative models in real-world applications. Our models and codes are available at https://github.com/hemingkx/SpecDec.

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