3 papers
cs.DB2026
LAANN: I/O-Aware Look-Ahead Search for Disk-Based Approximate Nearest Neighbor Search
Dingyi Kang, Juncheng Yang, Bingzhe Li
Approximate nearest neighbor search (ANNS) is a fundamental primitive in large-scale retrieval, recommendation, and AI systems. As vector datasets grow to billions or even trillion…
cs.LG2026
MoE-Prefill: Zero Redundancy Overheads in MoE Prefill Serving
Zhaoyuan Su, Olatunji Ruwase, Karthik Ganesan +5
Production LLM workloads increasingly serve discriminative tasks, such as classification, recommendation, and verification, whose answers are read from the logits of a single prefi…
cs.DC2025
Helix: Serving Large Language Models over Heterogeneous GPUs and Network via Max-Flow
Yixuan Mei, Yonghao Zhuang, Xupeng Miao +3
This paper introduces Helix, a distributed system for high-throughput, low-latency large language model (LLM) serving in heterogeneous GPU clusters. The key idea behind Helix is to…