This course was developed by members of AWS Technical Field Communities (TFC), an AWS community of technical experts. The content is intended to complement our standard training curriculum and augment your AWS learning journey. We are aware some courses have accessibility limitations and are working to address. If you require accommodation, please contact AWS Training and Certification Customer Support.
Learners will discover how AWS invented Parallel-EAGLE (P-EAGLE), a breakthrough method that parallelizes speculative decoding for large language models on Amazon SageMaker AI. The course explains how traditional approaches like EAGLE generate draft tokens sequentially -- creating latency that grows with speculation depth -- and how P-EAGLE eliminates this bottleneck by predicting all draft tokens simultaneously in a single forward pass using learnable placeholders. Participants will understand the architectural limitations of sequential drafting and how P-EAGLE transforms speculative decoding into a fully parallelized operation for improved inference throughput and reduced latency in production deployments.
