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相关概念视频

Long-Term Memory01:18

Long-Term Memory

105
Long-term memory is a relatively permanent type of memory, capable of storing vast amounts of information over extended periods. Its storage capacity is generally considered unlimited.
Long-term memory can be categorized into two primary types: explicit and implicit memory. Explicit memory, also known as declarative memory, involves the conscious recollection of information that we deliberately try to remember, recall, and articulate. This type of memory encompasses specific facts, events, and...
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Reproductive Cloning01:27

Reproductive Cloning

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Reproductive cloning is the process of producing a genetically identical copy—a clone—of an entire organism. While clones can be produced by splitting an early embryo—similar to what happens naturally with identical twins—cloning of adult animals is usually done by a process called somatic cell nuclear transfer (SCNT).
Somatic Cell Nuclear Transfer
In SCNT, an egg cell is taken from an animal and its nucleus is removed, creating an enucleated egg. Then a somatic...
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Cloning of Dolly the Sheep01:08

Cloning of Dolly the Sheep

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The first successfully cloned mammal was Dolly, a sheep, born on 5th July 1996 at Roslin Institute, Scotland. The cloned sheep was named after the American singer Dolly Parton. Dolly lived for seven years and died of respiratory complications, which is speculated to be due to the actual age of her DNA. Because the DNA in cloned cells belongs to an older individual,  the cloned individual’s life expectancy may be affected. Indeed, analysis of Dolly’s DNA revealed shorter...
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相关实验视频

Updated: May 30, 2025

Author Spotlight: Automated Deep Brain Stimulation for Parkinson's Disease - Exploring the Possibilities and Challenges of Home Monitoring
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物理非克隆内存计算,同时保护私人数据和深度学习模型.

Wenshuo Yue1,2, Kai Wu3, Zhiyuan Li1

  • 1Beijing Advanced Innovation Center for Integrated Circuits, School of Integrated Circuits, Peking University, Beijing, China.

Nature communications
|January 25, 2025
PubMed
概括
此摘要是机器生成的。

电阻随机访问内存计算内存提供了高效的神经网络加速,但有风险的数据提取. RePACK 方案通过保护输入,重量和结构来增强安全性,从而提高了清单复杂性,以获得更安全的边缘AI.

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科学领域:

  • 计算机工程 计算机工程
  • 硬件安全 硬件安全
  • 人工智能的人工智能

背景情况:

  • 使用电阻随机访问存储器 (ReRAM) 的内存计算 (CIM) 加快边缘设备上的神经网络,提高能源效率.
  • ReRAM的非易失性质带来安全风险,允许在计算过程中潜在地提取敏感的神经网络重量.

研究的目的:

  • 提出一个强大的数据保护方案,RePACK,用于基于ReRAM的CIM系统中安全的神经网络计算.
  • 保护神经网络输入数据,存储的权重和结构信息免受未经授权的提取.

主要方法:

  • 开发了RePACK,这是一个三重数据保护方案,集成了双方排序编码策略.
  • 整合了完全在芯片上的物理不可克隆功能 (PUF) 以提高安全性.
  • 在40nm的ReRAM CIM芯片上实现并评估了RePACK系统.

主要成果:

  • 成功保护神经网络输入,重量和结构信息.
  • 在128列CIM核心中,编号复杂度显著增加到5.77 × 10^75.
  • 在物理硬件原型上验证了RePACK系统的有效性.

结论:

  • RePACK提供了一种可行的解决方案,用于增强边缘神经网络的基于ReRAM的CIM系统的安全性.
  • 这项工作有助于开发安全,强大和高效的边缘AI加速器,可能支持诸如联合学习之类的应用程序.