GORIO: GPU-Centered Remote I/O for Graph ANNS over NVMe-oF

GORIO addresses the problem that graph-based approximate nearest neighbor search (ANNS) vector indexes often exceed GPU memory, and existing CPU-centered remote I/O over NVMe-oF is poorly matched to GPU graph traversal. The method keeps all query evolution, page-miss generation, and resume decisions on the GPU, using the CPU only as an NVMe-oF transport proxy, with a two-layer design for GPU-direct remote I/O and ANNS-specific scheduling. On a SIFT1M DiskANN-style workload over RDMA NVMe-oF, GORIO achieves 1.31× speedup over the state-of-the-art remote-I/O reference and 3.73× over the direct remote page-cache path. This matters because it provides a concrete GPU-centered remote I/O substrate that significantly accelerates graph ANNS for vector databases and retrieval-augmented generation services.