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A Robust Dual Reference Computing-in-Memory Implementation and Design Space Exploration Within STT-MRAM

机译:STT-MRAM中的稳健的双引用内存中计算实现和设计空间探索

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Due to the "memory wall" in conventional Von-Neumann computer architectures, the limited bandwidth between processors and memories has become one of the most critical bottlenecks to improve system performance. With the emerging of non-volatile memories, the computing-in-memory (CIM) paradigm has regained interest to tackle the issue at the architecture level. CIM can effectively alleviate the stress on the limitted bandwidth by performing logic operations within memories. However, CIMs are not yet studied carefully at the circuit level, and even its reliability and performance. In this paper, we proposed a CIM implementation: dual reference (DualRef) scheme at the circuit level within STT-MRAM (Spin Transfer Torque Magnetic Random Access Memory) array. Simulations were carried out to verify the functionality and assess the reliability and performance of DualRef scheme in terms of operation error rate, sensing margin, operation delay and dynamic energy consumption. Simulation results validate DualRef scheme and reveal that it is reliable to perform bitwise logic opertions within STT-MRAM while the TMR (Tunnel Magnetoresistance Ratio) varying between 100% and 300% and supply voltage Vdd varying from 0.9V to 1.2V. This work provides a robust circuitry scheme and design space to effectively implement CIM in STT-MRAM.
机译:由于常规Von-Neumann计算机体系结构中的“内存墙”,处理器和内存之间有限的带宽已成为提高系统性能的最关键的瓶颈之一。随着非易失性存储器的兴起,内存计算(CIM)范式重新引起了人们的兴趣,以在体系结构级别解决该问题。通过在内存中执行逻辑运算,CIM可以有效地减轻对有限带宽的压力。但是,尚未在电路级别,甚至在可靠性和性能方面仔细研究CIM。在本文中,我们提出了一种CIM实现:在STT-MRAM(自旋传递扭矩磁性随机存取存储器)阵列中的电路级采用双参考(DualRef)方案。进行了仿真,以验证DualRef方案的功能,并从操作错误率,感测余量,操作延迟和动态能耗方面评估DualRef方案的可靠性和性能。仿真结果验证了DualRef方案,并表明在TMR(隧道磁阻比)在100%至300%之间变化并且电源电压Vdd在0.9V至1.2V之间变化的情况下,在STT-MRAM中执行按位逻辑运算是可靠的。这项工作为有效地在STT-MRAM中实现CIM提供了强大的电路方案和设计空间。

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