High-performance STT-MRAM Logic-in-Memory Scheme Utilizing Data Read Features

Kai Liu, Bi Wu, Haonan Zhu, Weiqiang Liu
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Abstract

In the Big Data era, enormous amounts of data processing have caused an intolerable 'memory wall' challenge for traditional Von Neumann architectures. Therefore, more advanced Logic-in-memory (LiM) computing architectures are proposed with integrated computing and memory units that reduce data migration. The emerging non-volatile memory STT-MRAM, with its fast access speed, near-zero leakage power consumption and high density is one of the most competitive carriers for LiM architectures. This work introduces the principle of LiM and proposes four basic logic operations (XNOR, XOR, AND and OR) based on STT-MRAM. Incorporating the reading characteristics of STT-MRAM and slight modifications to the peripheral circuitry, these operations achieve significant optimisation in terms of latency and energy consumption. From the experimental results, the proposed scheme can reduce the latency of XOR, AND and OR operations at least by 99.3%, 82.2% and 80.2% compared with the existing design. Also, 500 Monte Carlo samples prove the feasibility and robustness of the proposed scheme.
利用数据读取功能的高性能STT-MRAM逻辑内存方案
在大数据时代,海量的数据处理给传统的冯·诺依曼架构带来了难以忍受的“内存墙”挑战。因此,更先进的内存逻辑(LiM)计算架构被提出,它集成了计算和存储单元,以减少数据迁移。新兴的非易失性存储器STT-MRAM以其快速的存取速度、接近于零的泄漏功耗和高密度是LiM架构中最具竞争力的载体之一。本文介绍了LiM的原理,提出了基于STT-MRAM的四种基本逻辑运算(XNOR、XOR、and和OR)。结合STT-MRAM的读取特性和对外围电路的轻微修改,这些操作在延迟和能耗方面实现了显著的优化。实验结果表明,与现有设计相比,该方案可将异或、与和或操作的延迟分别降低99.3%、82.2%和80.2%。500个蒙特卡罗样本验证了该方案的可行性和鲁棒性。
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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