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cs.AR2026
Co-Designing Graph-based Approximate Nearest Neighbor Search at Billion Scale for Processing-in-Memory
Sitian Chen, Yusen Li, Yao Chen +3
Approximate Nearest Neighbor Search (ANNS) is a core primitive in modern AI systems, and graph-based methods currently offer the best accuracy-efficiency trade-off at scale. The wo…
cs.AR2024
UpANNS: Enhancing Billion-Scale ANNS Efficiency with Real-World PIM Architecture
Sitian Chen, Amelie Chi Zhou, Yucheng Shi +2
Approximate Nearest Neighbor Search (ANNS) is a critical component of modern AI systems, such as recommendation engines and retrieval-augmented large language models (RAG-LLMs). Ho…