4 papers · 1 filter
d-HNSW: A High-performance Vector Search Engine on Disaggregated Memory
Fei Fang, Yi Liu, Chen Qian
Efficient vector search is essential for powering large-scale AI applications, such as LLMs. Existing solutions are designed for monolithic architectures where compute and memory a…
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…
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,…
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…