In-Memory Mirroring: Cloning Without Reading

Simranjeet Singh, Ankit Bende, Chandan Kumar Jha, Vikas Rana, Rolf Drechsler, Sachin Patkar, Farhad Merchant
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Abstract

In-memory computing (IMC) has gained significant attention recently as it attempts to reduce the impact of memory bottlenecks. Numerous schemes for digital IMC are presented in the literature, focusing on logic operations. Often, an application's description has data dependencies that must be resolved. Contemporary IMC architectures perform read followed by write operations for this purpose, which results in performance and energy penalties. To solve this fundamental problem, this paper presents in-memory mirroring (IMM). IMM eliminates the need for read and write-back steps, thus avoiding energy and performance penalties. Instead, we perform data movement within memory, involving row-wise and column-wise data transfers. Additionally, the IMM scheme enables parallel cloning of entire row (word) with a complexity of $\mathcal{O}(1)$. Moreover, our analysis of the energy consumption of the proposed technique using resistive random-access memory crossbar and experimentally validated JART VCM v1b model. The IMM increases energy efficiency and shows 2$\times$ performance improvement compared to conventional data movement methods.
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内存镜像不读取的克隆
最近,内存计算(IMC)受到了广泛关注,因为它试图减少内存瓶颈的影响。文献中介绍了大量数字 IMC 方案,主要集中在逻辑运算方面。为了解决这一根本问题,本文提出了内存镜像(IMM)方案。为了解决这一根本问题,本文提出了内存内镜像(IMM)技术。IMM 消除了读取和回写步骤,从而避免了能耗和性能损失。取而代之的是,我们在内存中执行数据移动,包括行向和列向数据传输。此外,IMM 方案实现了整行(字)的并行克隆,复杂度为 $/mathcal{O}(1)$。此外,我们还利用电阻式随机存取存储器交叉条和经过实验验证的 JART VCM v1b 模型分析了所提技术的能耗。与传统的数据移动方法相比,IMM 提高了能效,并将性能提高了 2 倍。
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