Conveyor: Efficient Tool-aware LLM Serving with Tool Partial Execution
Keywords: Large language models, External Tools
TL;DR: Efficient Tool Support in LLM serving systems
Abstract: The complexity of large language model (LLM) serving workloads has substantially increased due to the integration with external tool invocations, such as ChatGPT plugins. In this paper, we identify a new opportunity for efficient LLM serving for requests that trigger tools: tool partial execution alongside LLM decoding. To this end, we design Conveyor, an efficient LLM serving system optimized for handling requests involving external tools. We introduce a novel interface for tool developers to expose partial execution opportunities to the LLM serving system and a request scheduler that facilitates partial tool execution. Our results demonstrate that tool partial execution can reduce request completion latency by up to 38.8%.
Primary Area: infrastructure, software libraries, hardware, systems, etc.
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Submission Number: 8289
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