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中国物理学会期刊

基于3D-NAND的神经形态计算

CSTR: 32037.14.aps.71.20220974

3D-NAND flash memory based neuromorphic computing

CSTR: 32037.14.aps.71.20220974
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  • 神经形态芯片是一种新兴的AI芯片. 神经形态芯片基于非冯·诺依曼架构, 模拟人脑的结构和工作方式, 相比冯·诺依曼架构的AI芯片, 神经形态芯片在效率和能耗上有显著的优势. 3D-NAND闪存工艺成熟并且存储密度极高, 基于3D-NAND的神经形态芯片受到许多研究者的关注. 然而由于该技术的专利性质, 少有基于3D-NAND神经形态计算的硬件实现. 本文综述了用3D-NAND实现神经形态计算的工作, 介绍了其中前向传播和反向传播的机制, 并提出了目前3D NAND在器件、结构和架构上需要的改进以适用于未来的神经形态计算.

     

    A neuromorphic chip is an emerging AI chip. The neuromorphic chip is based on non-Von Neumann architecture, and it simulates the structure and working principle of the human brain. Compared with non-Von Neumann architecture AI chips, the neuromorphic chips have significant improvement of efficiency and energy consumption advantages. The 3D-NAND flash memory has the merits of a mature process and ultra-high storage density, and recently it attracted many researchers’ attention. However, owing to the proprietary nature of the technology, there are few hardware implementations. This paper reviews the present research status of neuromorphic computing by using the 3D-NAND flash memory, introduces the forward propagation and backward propagation schemes, and proposes several improvements on the device, structure, and architecture of 3D NAND for neuromorphic computing.

     

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