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Modeling and Designing of a PVT Auto-tracking Timing-speculative SRAM

机译:PVT自动跟踪时序推测性SRAM的建模与设计

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In the low supply voltage region, the performance of 6T cell SRAM degrades seriously, which takes more time to achieve the sufficient voltage difference on bitlines. Timing- speculative techniques are proposed to boost the SRAM frequency and the throughput with speculatively reading data in an aggressive timing and correcting timing failures in one or more extended cycles. However, the throughput gains of timing- speculative SRAM are affected by the process, voltage and temperature (PVT) variations, which causes the timing design of speculative SRAM to be either too aggressive or too conservative.(p)(/p)This paper first proposes a statistical model to abstract the characteristics of speculative SRAM and shows the presence of an optimal sensing time that maximizes the overall throughput. Then, with the guidance of the performance model, a PVT auto-tracking speculative SRAM is designed and fabricated, which can dynamically self-tune the bitline sensing to the optimal time as the working condition changes. According to the measurement results, the maximum throughput gain of the proposed 28nm SRAM is 1.62X compared to the baseline at 0.6V VDD.
机译:在低电源电压区域,6T单元SRAM的性能严重下降,这需要更多时间才能在位线上获得足够的电压差。提出了时序推测技术来提高SRAM的频率和吞吐量,以一种积极的方式推测性地读取数据,并在一个或多个扩展周期内纠正时序故障。但是,时序推测SRAM的吞吐量增益受制程,电压和温度(PVT)变化的影响,这导致推测SRAM的时序设计过于激进或过于保守。首先提出了一个统计模型来抽象推测性SRAM的特性,并说明了最佳传感时间的存在,该时间可以使整体吞吐量最大化。然后,在性能模型的指导下,设计并制造了PVT自动跟踪推测性SRAM,它可以随着工作条件的变化而动态地将位线感测自调整到最佳时间。根据测量结果,与在0.6V VDD时的基线相比,建议的28nm SRAM的最大吞吐量增益为1.62倍。

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