Greedy Multi-Path Block Verification for Faster Decoding in Speculative Sampling

TL;DR

This paper introduces greedy multi-path block verification (GBV), a novel method that enhances speculative decoding efficiency by optimizing verification algorithms, leading to significant speedups in autoregressive model decoding.

Contribution

It extends block verification to off-path probabilities, formulates a greedy multi-path verification approach, and demonstrates substantial empirical improvements over existing methods.

Findings

GBV improves block verification efficiency by over 30%.

Decoding walltimes are reduced by over 15%.

On Llama-3 70B, GBV outperforms state-of-the-art methods by more than 15%.

Abstract

The goal of $L$-step speculative decoding is to accelerate autoregressive decoding of a target model by using a cheaper draft model to generate a candidate path of $L$ tokens. Based on a verification algorithm involving target and draft model probabilities, a prefix of the candidate sequence is accepted, and an additional correction token is sampled from a residual distribution to ensure that the final output adheres to the target distribution. While standard speculative decoding uses a verification algorithm which is independent at each token on the path, a recent extension called block verification uses a joint condition involving all sampled on-path probabilities. Block verification (BV) was shown to be optimal over all verification algorithms which use only on-path probabilities, improving on standard speculative decoding. In this work, we first show that block verification is optimal even over verification algorithms that use off-path probabilities, by constructing an information-agnostic linear program (LP). Further, we can extend our LP to the setting where the draft model samples multiple candidate paths, and use it to construct a natural class of multi-path block verification generalizations. While computing the optimal algorithm in this class is not tractable, by considering a stricter class of greedy algorithms, we can formulate an efficient method called greedy multi-path block verification (GBV). Empirically, GBV can improve block efficiency by over 30% and reduce decoding walltimes by over 15% relative to BV. On Llama-3 70B, GBV can improve the end-to-end decoding throughput over SOTA multi-path verification methods by more than 15%.