4 papers
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…
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…
Arcturus: A Cloud Overlay Network for Global Accelerator with Enhanced Performance and Stability
Matthew Yang Liu, Chuang Chen, Pengcheng Lv +6
Global Accelerator (GA) services play a vital role in ensuring low-latency, high-reliability communication for real-time interactive applications. However, existing GA offerings ar…
UpDLRM: Accelerating Personalized Recommendation using Real-World PIM Architecture
Sitian Chen, Haobin Tan, Amelie Chi Zhou +2
Deep Learning Recommendation Models (DLRMs) have gained popularity in recommendation systems due to their effectiveness in handling large-scale recommendation tasks. The embedding…