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首页> 外文期刊>IEEE Journal of Solid-State Circuits >A 7-nm Compute-in-Memory SRAM Macro Supporting Multi-Bit Input, Weight and Output and Achieving 351 TOPS/W and 372.4 GOPS
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A 7-nm Compute-in-Memory SRAM Macro Supporting Multi-Bit Input, Weight and Output and Achieving 351 TOPS/W and 372.4 GOPS

机译:一个7nm Compute-In-Memory SRAM宏支持多位输入,重量和输出,实现351个顶部/ W和372.4 GOP

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摘要

In this work, we present a compute-in-memory (CIM) macro built around a standard two-port compiler macro using foundry 8T bit-cell in 7-nm FinFET technology. The proposed design supports 1024 4 b x 4 b multiply-and-accumulate (MAC) computations simultaneously. The 4-bit input is represented by the number of read word-line (RWL) pulses, while the 4-bit weight is realized by charge sharing among binary-weighted computation caps. Each unit of computation cap is formed by the inherent cap of the sense amplifier (SA) inside the 4-bit Flash ADC, which saves area and minimizes kick-back effect. Access time is 5.5 ns with 0.8-V power supply at room temperature. The proposed design achieves energy efficiency of 351 TOPS/W and throughput of 372.4 GOPS. Implications of our design from neural network implementation and accuracy perspectives are also discussed.
机译:在这项工作中,我们在7-NM FinFET技术中使用铸造8T位单元播出围绕标准的双端口编译宏构建的内存内存(CIM)宏。所提出的设计同时支持1024 4b x 4b乘积和累积(MAC)计算。 4位输入由读字线(RWL)脉冲的数量表示,而通过二进制加权计算帽之间的电荷共享实现4比特权重。每个计算帽由4位闪存ADC内的读出放大器(SA)的固有盖形成,该磁带闪存ADC可以节省区域并最大限度地减少踢回效果。访问时间为5.5 ns,室温下有0.8V电源。所提出的设计实现了351个顶部/倍的能量效率和372.4个吞吐量的吞吐量。还讨论了我们设计从神经网络实现和准确性观点的影响。

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