3 citations · 4 across the 7 of their papers we have counts for
7 papers
Trinity: Disaggregating Vector Search from Prefill-Decode Disaggregation in LLM Serving
Yi Liu, Chen Qian
Prefill and decode (PD) disaggregation separates prompt prefill and token-by-token decode stages into distinct GPU pools and has become the dominant architecture for large-scale LL…
Fantasy: Efficient Large-scale Vector Search on GPU Clusters with GPUDirect Async
Yi Liu, Chen Qian
Vector similarity search has become a critical component in AI-driven applications such as large language models (LLMs). To achieve high recall and low latency, GPUs are utilized t…
A Distributed Learned Hash Table
Shengze Wang, Yi Liu, Xiaoxue Zhang +2
Distributed Hash Tables (DHTs) are pivotal in numerous high-impact key-value applications built on distributed networked systems, offering a decentralized architecture that avoids…
Efficient Vector Search on Disaggregated Memory with d-HNSW
Yi Liu, Fei Fang, Chen Qian
Efficient vector query processing is critical to enable AI applications at scale. Recent solutions struggle with growing vector datasets that exceed single-machine memory capacity,…
CloudQC: A Network-aware Framework for Multi-tenant Distributed Quantum Computing
Ruilin Zhou, Yuhang Gan, Yi Liu +1
Distributed quantum computing (DQC) that allows a large quantum circuit to be executed simultaneously on multiple quantum processing units (QPUs) becomes a promising approach to in…
Outback: Fast and Communication-efficient Index for Key-Value Store on Disaggregated Memory
Yi Liu, Minghao Xie, Shouqian Shi +3
Disaggregated memory systems achieve resource utilization efficiency and system scalability by distributing computation and memory resources into distinct pools of nodes. RDMA is a…