AIBullisharXiv – CS AI · 18h ago7/10
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Kunlun: Establishing Scaling Laws for Massive-Scale Recommendation Systems through Unified Architecture Design
Meta researchers have developed Kunlun, a scalable architecture for recommendation systems that establishes predictable scaling laws by improving model efficiency from 17% to 37% on GPU utilization. The system combines low-level optimizations like Generalized Dot-Product Attention with high-level innovations to double scaling efficiency, now deployed across Meta's advertising infrastructure.
🏢 Nvidia