arXiv:2604.09752v1 Announce Type: cross
Abstract: During the deployment of Large Language Models (LLMs), the autoregressive decoding phase on heterogeneous NPU platforms (e.g., Ascend 910B) faces severe memory-bound challenges. This study reveals the “Model Scaling Paradox” caused by the static deployment of single-sized models. It also points out the kernel synchronization overhead of fine-grained speculative decoding citeleviathan2023fast, chen2023speculative under NPU computational graph compilation, and the severe limitations of purely relying on micro-level acceleration algorithms like Prompt LookUp Decoding (PLD)
Dissecting polycomb complexes for enhanced fetal hemoglobin production
Polycomb repressive complexes PRC1 and PRC2 regulate diverse developmental processes, including the fetal-to-adult switch in hemoglobin production, a process whose reversal is a goal for


