4 papers
InSituANN: Revisiting IVF for PCIe-Efficient Billion-Scale Vector Search
Yuemeng Xu, Zongxi Liu, Junyu Long +7
Approximate nearest neighbor search (ANNS) over billion-scale vector datasets has become a foundational operator for modern retrieval systems, powering large-scale recommendation,…
CuckooGraph: A Scalable and Space-Time Efficient Data Structure for Large-Scale Dynamic Graphs
Zhuochen Fan, Yalun Cai, Zirui Liu +4
Graphs play an increasingly important role in various big data applications. However, existing graph data structures cannot simultaneously address the performance bottlenecks cause…
CAFE: Towards Compact, Adaptive, and Fast Embedding for Large-scale Recommendation Models
Hailin Zhang, Zirui Liu, Boxuan Chen +4
Recently, the growing memory demands of embedding tables in Deep Learning Recommendation Models (DLRMs) pose great challenges for model training and deployment. Existing embedding…
Experimental Analysis of Large-scale Learnable Vector Storage Compression
Hailin Zhang, Penghao Zhao, Xupeng Miao +4
Learnable embedding vector is one of the most important applications in machine learning, and is widely used in various database-related domains. However, the high dimensionality o…