基于三维非易失性关联处理器的高性能节能计算单片机

IF 2 Q3 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE
Esteban Garzón;Alessandro Bedoya;Marco Lanuzza;Leonid Yavits
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引用次数: 0

摘要

本文介绍了一种单片式三维关联内存处理器(M3D AP),它将新兴的非易失性(NV)磁隧道结(MTJ)技术与大规模并行关联内存处理和 M3D 集成相结合。拟议的架构有两个单片层,第一层是 CMOS 逻辑,第二层是基于 MTJ 的内容寻址存储器(CAM)阵列。我们对基于 MTJ 的 AP 的电气特性进行了全面分析,并利用分析结果评估了 M3D AP 的性能和功耗。我们建立了一个定制的周期精确模拟器来实现和评估三维关联矩阵乘法算法,从而突出了 M3D AP 在加速人工智能应用方面的潜力。总之,我们证明了 M3D AP 的功效,并表明它有望实现高性能、高能效的内存计算。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Monolithic 3-D-Based Nonvolatile Associative Processor for High-Performance Energy-Efficient Computations
This article presents a monolithic 3-D associative in-memory processor (M3D AP) that combines emerging nonvolatile (NV) magnetic tunnel junction (MTJ) technology with massively parallel associative in-memory processing and M3D integration. The proposed architecture features two monolithic layers, with CMOS logic in the first layer and an MTJ-based content-addressable memory (CAM) array in the second layer. We conduct a thorough analysis of the electrical characteristics of the MTJ-based AP and use analysis results to evaluate the performance and power consumption of the M3D AP. We build a custom cycle-accurate simulator to implement and evaluate the 3-D associative matrix multiplication algorithm, highlighting the potential of the M3D AP for accelerating artificial intelligence applications. Overall, we demonstrate the efficacy of M3D AP and show that it holds promise for high-performance and energy-efficient in-memory computing.
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来源期刊
CiteScore
5.00
自引率
4.20%
发文量
11
审稿时长
13 weeks
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