Papers by Sungsoo Ha

1 papers
BASS: Batched Attention-optimized Speculative Sampling (2024.findings-acl)

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Challenge: Speculative decoding has emerged as a powerful method to improve latency and throughput in hosting large language models.
Approach: They propose a batched speculative decoding system that generates sequences at an average speed of 5.8ms per token and a batch size of 8 at a 2.15 speed-up over optimized regular decoding.
Outcome: The proposed system achieves state-of-the-art latency and speed-up over optimized regular decoding.

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