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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.DC2025
NM-SpMM: Accelerating Matrix Multiplication Using N:M Sparsity with GPGPU
Cong Ma, Du Wu, Zhelang Deng +11
Deep learning demonstrates effectiveness across a wide range of tasks. However, the dense and over-parameterized nature of these models results in significant resource consumption…