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English(EN) SSDi8: Accurate and Efficient 8-bit Quantization for State Space Duality

SSDi8框架通过8位量化增强Mamba-2架构

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了SSDi8，一种专门针对Mamba-2架构的结构化状态空间对偶（SSD）的新型8位量化框架。该方法旨在减少Mamba-2集成循环和注意力模式所带来的内存和延迟开销。SSDi8通过重新构建计算以重用量化激活并自适应地量化通道变化的激活来实现这一点。实验表明，在W4A8和W8A8设置下，SSDi8在保持与FP16相当的准确性的同时，速度提升高达1.4倍，并且已成功部署在Orin NX等资源受限的设备上。 AI

影响 这项量化技术可以使Mamba-2等先进序列模型在边缘设备上更高效地部署。

排序理由 这是一篇详细介绍模型量化新技术的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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SSDi8框架通过8位量化增强Mamba-2架构

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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Hyunwoo Kim, Byoungchan Ko, Minseok Kang, Minwoo Kim, Dongjin Lee, Jaehoon Lee, Sungroh Yoon, Dahuin Jung ·

    SSDi8：状态空间对偶的精确高效8位量化

    arXiv:2608.21952v1 Announce Type: new Abstract: Recent advances in sequence modeling have highlighted Mamba as a state space architecture offering efficient long-range dependency modeling and providing a viable alternative to Transformers. Building upon this, Mamba-2 introduces t…

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