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HDA-MoE is presented, a framework that optimizes MoE execution on NMP architectures through hybrid parallel deployment and runtime scheduling and integrates an offline hybrid parallel mapping algorithm with an online dynamic and adaptive scheduling mechanism to reduce communication overhead while improving computation utilization.
C2C-Explorer boosts LLM inference efficiency, achieving a 44.1% increase in goodput and a staggering 98.4% reduction in memory usage.
