6 papers
SMetric: Rethink LLM Scheduling for Serving Agents with Balanced Session-centric Scheduling
Jiahao Wang, Kaizhan Lin, Kaixi Zhang +7
LLM scheduling is critical to serving, yet it remains unclear how well existing designs fit agentic serving--with LLM requests issued by agents instead of humans. This shifts the w…
Simple is Better: Multiplication May Be All You Need for LLM Request Scheduling
Dingyan Zhang, Jinbo Han, Kaixi Zhang +6
High-quality LLM request scheduling requires meeting two key objectives: ensuring the routed instance has KVCache to accelerate request execution, and ensuring that the workload is…
Efficient Vector Search in the Wild: One Model for Multi-K Queries
Yifan Peng, Jiafei Fan, Xingda Wei +7
Learned top-K search is a promising approach for serving vector queries with both high accuracy and performance. However, current models trained for a specific K value fail to gene…
KVCache Cache in the Wild: Characterizing and Optimizing KVCache Cache at a Large Cloud Provider
Jiahao Wang, Jinbo Han, Xingda Wei +6
Serving large language models (LLMs) is important for cloud providers, and caching intermediate results (KV$) after processing each request substantially improves serving throughp…
LSMGraph: A High-Performance Dynamic Graph Storage System with Multi-Level CSR
Song Yu, Shufeng Gong, Qian Tao +9
The growing volume of graph data may exhaust the main memory. It is crucial to design a disk-based graph storage system to ingest updates and analyze graphs efficiently. However, e…
Characterizing the Dilemma of Performance and Index Size in Billion-Scale Vector Search and Breaking It with Second-Tier Memory
Rongxin Cheng, Yifan Peng, Xingda Wei +4
Vector searches on large-scale datasets are critical to modern online services like web search and RAG, which necessity storing the datasets and their index on the secondary storag…