Speculative Decoding: Exploiting Speculative Execution for Accelerating Seq2seq Generation
Heming Xia, Tao Ge, Peiyi Wang, Si-Qing Chen, Furu Wei, Zhifang Sui
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 5x 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 1.4x~2x 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.- Anthology ID:
- 2023.findings-emnlp.257
- Volume:
- Findings of the Association for Computational Linguistics: EMNLP 2023
- Month:
- December
- Year:
- 2023
- Address:
- Singapore
- Editors:
- Houda Bouamor, Juan Pino, Kalika Bali
- Venue:
- Findings
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 3909–3925
- Language:
- URL:
- https://aclanthology.org/2023.findings-emnlp.257
- DOI:
- 10.18653/v1/2023.findings-emnlp.257
- Cite (ACL):
- Heming Xia, Tao Ge, Peiyi Wang, Si-Qing Chen, Furu Wei, and Zhifang Sui. 2023. Speculative Decoding: Exploiting Speculative Execution for Accelerating Seq2seq Generation. In Findings of the Association for Computational Linguistics: EMNLP 2023, pages 3909–3925, Singapore. Association for Computational Linguistics.
- Cite (Informal):
- Speculative Decoding: Exploiting Speculative Execution for Accelerating Seq2seq Generation (Xia et al., Findings 2023)
- PDF:
- https://preview.aclanthology.org/naacl24-info/2023.findings-emnlp.257.pdf