GORIO：基于NVMe-oF的图近似近邻搜索的以GPU为中心的远程I/O
GORIO: GPU-Centered Remote I/O for Graph ANNS over NVMe-oF
AI总结：
研究针对图近似近邻搜索中大型向量索引超单GPU服务器内存问题，提出GORIO系统，将以GPU为中心的本地I/O扩展到远程存储，设计两层架构，实验表明其性能大幅提升。
摘要：
基于图的近似近邻搜索（ANNS）在向量数据库和检索增强生成服务中应用渐广，但大型向量索引常超单GPU服务器内存。NVMe over Fabrics（NVMe-oF）提供了有吸引力的存储解聚基板，然而现有远程存储路径仍以CPU为中心。本文提出GORIO，将以GPU为中心的本地I/O扩展到远程存储，并针对基于NVMe-oF的图ANNS对结果基板进行专门设计。GORIO在GPU上保留查询演化、页面缺失生成、挂起查询状态和恢复决策，而CPU仅充当NVMe-oF传输和完成代理。该设计有两层：一个GPU直接远程I/O路径，将本地页面缓存缺失转换为分阶段远程操作，以及特定于ANNS的调度机制，使图遍历与远程页面服务重叠。在通过RDMA NVMe-oF路径的SIFT1M DiskANN样式图工作负载上，GORIO比最先进的远程I/O参考路径快1.31倍，比直接远程页面缓存路径快3.73倍。这些结果展示了一个具体的以GPU为中心的图ANNS远程I/O基板。
英文摘要：
Graph-based approximate nearest neighbor search (ANNS) is increasingly used in vector databases and retrieval-augmented generation services, but large vector indexes often exceed the memory capacity of a single GPU server. NVMe over Fabrics (NVMe-oF) provides an attractive storage-disaggregation substrate, yet existing remote storage paths are still largely CPU-centered: the CPU forms I/O requests, drives transport progress, and determines when GPU computation can resume. This organization is poorly matched to graph ANNS, where the next data access is discovered inside GPU graph traversal. This paper presents GORIO, a system study that extends GPU-centered local I/O to remote storage and specializes the resulting substrate for graph ANNS over NVMe-oF. GORIO keeps query evolution, page-miss generation, pending-query state, and resume decisions on the GPU, while the CPU acts only as an NVMe-oF transport and completion proxy. The design has two layers: a GPU-direct remote I/O path that turns local page-cache misses into split-phase remote operations, and ANNS-specific scheduling mechanisms that overlap graph traversal with remote page service. On a SIFT1M DiskANN-style graph workload over an RDMA NVMe-oF path, GORIO is 1.31X faster than the state-of-the-art remote-I/O reference path and 4.89X faster than the direct remote page-cache path. These results demonstrate a concrete GPU-centered remote I/O substrate for graph ANNS.
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