ExeGPT: Constraint-Aware Resource Scheduling for LLM Inference

arXiv:2404.07947v1 Announce Type: cross
Abstract: This paper presents ExeGPT, a distributed system designed for constraint-aware LLM inference. ExeGPT finds and runs with an optimal execution schedule to maximize inference throughput while satisfying a given latency constraint. By leveraging the distribution of input and output sequences, it effectively allocates resources and determines optimal execution configurations, including batch sizes and partial tensor parallelism. We also introduce two scheduling strategies based on Round-Robin Allocation and Workload-Aware Allocation policies, suitable for different NLP workloads. …

abstract arxiv cs.dc cs.lg distributed distribution inference latency llm paper resources scheduling type