Exécution de notre outil de synthèse sur un nouvel article
Vérifiez l’article ci-dessous, puis lancez sa synthèse.
d-HNSW: A High-performance Vector Search Engine on Disaggregated Memory
Fei Fang (University of California, Santa Cruz), Yi Liu (University of California, Santa Cruz), Chen Qian (University of California, Santa Cruz)
ACM SIGMETRICS Performance Evaluation Review
DOI: 10.1145/3820171.3806852 (Computer Science)
Licence : CC BY-NC-ND
Résumé : We present d-HNSW, an RDMA-based vector search engine for disaggregated memory that overcomes network bottlenecks and layout fragmentation through hardware-algorithm co-designed representative index caching, RDMA-friendly remote storage layout, query-aware loading, and pipelined execution.
Publié le 20 Jul. 2026