并行搜索和人工智能应用中出现的非易失性TCAM的趋势

Chip Pub Date : 2022-06-01 DOI:10.1016/j.chip.2022.100012

Ke-Ji Zhou , Chen Mu , Bo Wen , Xu-Meng Zhang , Guang-Jian Wu , Can Li , Hao Jiang , Xiao-Yong Xue , Shang Tang , Chi-Xiao Chen , Qi Liu

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引用次数: 3

摘要

在本文中，我们回顾了使用新兴的非易失性三元内容可寻址存储器(TCAM)的并行搜索和人工智能(AI)应用的最新趋势。首先，讨论了用于实现非易失性TCAM的四种典型新兴存储器的原理和发展。然后，分析了基于sram的TCAM和非易失性TCAM并行搜索的原理和挑战。最后，提出了用于人工智能应用的非易失性TCAM的研究趋势和挑战，包括面向计算机科学和面向神经科学的计算。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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The trend of emerging non-volatile TCAM for parallel search and AI applications

In this paper, we review the recent trends in parallel search and artificial intelligence (AI) applications using emerging non-volatile ternary content addressable memory (TCAM). Firstly, the principle and development of four typical emerging memory used to implement the non-volatile TCAM are discussed. Then, we analyze the principle and challenges of SRAM-based TCAM and non-volatile TCAM for the parallel search. Finally, the research trends and challenges of non-volatile TCAM used for AI application are presented, which include computer-science oriented and neuroscience oriented computing.

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来源期刊

Chip

CiteScore

2.80

自引率

0.00%

发文量