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Design of an Area-Efficient Computing in Memory Platform Based on STT-MRAM

机译:基于STT-MRAM的存储器平台中区域有效计算的设计

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In the era of big data, the memory wall between the processor and the memory as well as leakage current have become major bottlenecks of the traditional CMOS-based Von-Neumann computer architecture. Computing-in-memory (CiM) based on non-volatile memories (NVMs) is considered a promising method to solve the above-mentioned issues in computing systems. In this article, we propose a CiM platform based on spin-transfer torque magnetic random access memory (STT-MRAM). On the basis of the conventional CiM with AND/OR logic functions, the full-adder (FA) arithmetic operation is achieved with slight circuits modification by exploiting majority logic. Due to the parallel processing of carry and sum operations in multi-bit FA operation, the latency overhead caused by the two-step scheme is acceptable. The hybrid spintronic/CMOS simulations on the 40 nm technology node prove the functionality and performance of the proposed CiM platform.
机译:在大数据的时代,处理器和存储器之间的存储壁以及泄漏电流已成为传统CMOS的VON-Neumann计算机架构的主要瓶颈。基于非易失性存储器(NVMS)的计算内存(CIM)被认为是解决计算系统中的上述问题的有希望的方法。在本文中,我们提出了一种基于旋转传输扭矩磁随机存取存储器(STT-MRAM)的CIM平台。在传统CIM的基础上具有和/或逻辑功能,通过利用多数逻辑来实现全加法器(FA)算术运算。由于在多比特FA操作中的携带和和操作的并行处理,由两步方案引起的延迟开销是可接受的。 40 nm技术节点上的混合闪光/ CMOS模拟证明了所提出的CIM平台的功能和性能。

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