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Simultaneous Token Generation in Batched Decoding
During the decoding phase of a batched inference process, a Large Language Model generates tokens simultaneously for all the sequences within the batch. This generation process continues until the token generation for the longest sequence in the batch reaches completion.
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Foundations of Large Language Models
Ch.5 Inference - Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
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Aggregated Architecture for Prefilling and Decoding
Static Batching
A technology company is optimizing its popular chatbot service, which is powered by a large language model and handles thousands of simultaneous user queries. To manage this high load, their engineers implement a system that waits to collect several user queries and processes them together as a single group in one computational step. Which of the following outcomes is the most direct and significant advantage of this approach?
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Efficiency of Sequential vs. Batched Processing
Throughput-Latency Trade-off in LLM Inference
Simultaneous Token Generation in Batched Decoding
Sequence Concatenation in Disaggregated Inference