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Efficient complementary resistive switch-based crossbar array Booth multiplier

机译:基于互补电阻开关的高效纵横制布斯乘法器

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Recent advances of memristive devices allow high endurance, non-volatile storage and low leakage power. Thus, these devices are suitable candidates for in-memory computing. Several recent studies explored the usage of memristive crossbar array for approximate and neuromorphic computing, including approximate matrix-vector multiplication. However, accurate digital circuit realization using device-level simulation, accounting for more realistic ReRANI device behavior, is only studied for adder circuits so far. In this paper, we report the first study of a multiplier scheme with complementary resistive switch-based crossbar arrays. An efficient mapping of Booth multiplication algorithm with different area-timing trade-offs, is discussed. Simulation studies are performed using 4-bit numbers to validate our approach.
机译:忆阻器件的最新进展允许高耐久性,非易失性存储和低泄漏功率。因此,这些设备是内存中计算的合适候选者。最近的一些研究探索了忆阻交叉开关阵列在近似和神经形态计算中的用途,包括近似矩阵向量乘法。但是,到目前为止,仅针对加法器电路研究了使用器件级仿真实现的精确数字电路实现(考虑到更现实的ReRANI器件行为)。在本文中,我们报告了对基于互补电阻开关的交叉开关阵列的乘法器方案的首次研究。讨论了具有不同区域时序权衡的布斯乘法算法的有效映射。仿真研究使用4位数字进行,以验证我们的方法。

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