SCORPIO: Serving the Right Requests at the Right Time for Heterogeneous SLOs in LLM Inference
Existing Large Language Model (LLM) serving systems prioritize maximum throughput. They often neglect Service Level Objectives (SLOs) such as Time to First Token (TTFT) and Time Per Output Token (TPOT), which leads to suboptimal SLO attainment. This paper introduces SCORPIO, an SLO-oriented LLM serving system designed to maximize system goodput and SLO attainment for workloads with heterogeneous SLOs. Our core insight is to exploit SLO heterogeneity for adaptive scheduling across admission control, queue management, and batch selection. SCORPIO features a TTFT Guard, which employs least-deadline-first reordering and rejects unattainable requests, and a TPOT Guard, which utilizes a VBS-based admission control and a novel credit-based batching mechanism. Both guards are supported by a predictive module. Evaluations demonstrate that SCORPIO improves system goodput by up to 14.4X and SLO adherence by up to 46.5% compared to state-of-the-art baselines.
Code (0)
등록된 구현이 없습니다.
Tasks
Language ModelingLanguage ModellingLarge Language ModelManagementSchedulingMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Thinking Short and Right Over Thinking Long: Serving LLM Reasoning Efficiently and Accurately
Recent advances in test-time scaling suggest that Large Language Models (LLMs) can gain better capabilities by generating Chain-of-Thought reasoning (analogous to human thinking) to respond a given request, and meanwhile…
Avoiding Copyright Infringement via Large Language Model Unlearning
Pre-trained Large Language Models (LLMs) have demonstrated remarkable capabilities but also pose risks by learning and generating copyrighted material, leading to significant legal and ethical concerns. In real-world sce…
General KnowledgeLanguage ModelingLanguage ModellingLarge Language Model+1Towards Bridging the Gaps between the Right to Explanation and the Right to be Forgotten
The Right to Explanation and the Right to be Forgotten are two important principles outlined to regulate algorithmic decision making and data usage in real-world applications. While the right to explanation allows indivi…
Decision MakingSHIELD: Evaluation and Defense Strategies for Copyright Compliance in LLM Text Generation
Large Language Models (LLMs) have transformed machine learning but raised significant legal concerns due to their potential to produce text that infringes on copyrights, resulting in several high-profile lawsuits. The le…
Text GenerationNovel scorpion detection system combining computer vision and fluorescence
In this work, a fully automatic and real-time system for the detection of scorpions was developed using computer vision and deep learning techniques. This system is based on the implementation of a double validation proc…