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English(EN) PoTAcc: A Pipeline for End-to-End Acceleration of Power-of-Two Quantized DNNs

PoTAcc流水线在边缘设备上加速二的幂量化深度神经网络

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了PoTAcc，一个开源流水线，旨在加速资源受限的边缘设备上二的幂（PoT）量化深度神经网络（DNN）的部署。该系统通过TensorFlow Lite促进这些模型的准备和部署，支持仅CPU配置以及带有定制加速器的混合CPU-FPGA系统。评估表明，使用PoTAcc的CPU-加速器设计在特定FPGA板上与仅CPU执行相比，实现了高达3.6倍的速度提升和78%的能耗降低。 AI

影响 加速量化深度神经网络在边缘设备的部署，可能提高资源受限环境中人工智能应用的性能和能效。

排序理由 这是一篇研究论文，详细介绍了一种在边缘设备上加速量化深度神经网络的新流水线。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

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PoTAcc流水线在边缘设备上加速二的幂量化深度神经网络

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这是一篇研究论文，详细介绍了一种在边缘设备上加速量化深度神经网络的新流水线。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Rappy Saha, Jude Haris, Nicolas Bohm Agostini, David Kaeli, Jos\'e Cano ·

    PoTAcc：用于二的幂量化深度神经网络端到端加速的流水线

    arXiv:2605.06082v1 Announce Type: cross Abstract: Power-of-two (PoT) quantization significantly reduces the size of deep neural networks (DNNs) and replaces multiplications with bit-shift operations for inference. Prior work has shown that PoT-quantized DNNs can preserve accuracy…

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