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cs.DC2025
Near-Zero-Overhead Freshness for Recommendation Systems via Inference-Side Model Updates
Wenjun Yu, Sitian Chen, Cheng Chen +1
Deep Learning Recommendation Models (DLRMs) underpin personalized services but face a critical freshness-accuracy tradeoff due to massive parameter synchronization overheads. Produ…
cs.DC2024
FlowWalker: A Memory-efficient and High-performance GPU-based Dynamic Graph Random Walk Framework
Junyi Mei, Shixuan Sun, Chao Li +9
Dynamic graph random walk (DGRW) emerges as a practical tool for capturing structural relations within a graph. Effectively executing DGRW on GPU presents certain challenges. First…