C3SRAM:基于电容耦合计算的内存计算SRAM宏

Zhewei Jiang, Shihui Yin, Jae-sun Seo, Mingoo Seok
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引用次数: 1

摘要

这封信介绍了C3SRAM,一种内存计算SRAM宏,它利用模拟混合信号电容耦合计算来执行二进制深度神经网络的xnor和累积操作。256 × 64 C3SRAM宏同时断言所有256行,每列配备一个ADC,在一个周期内实现完全并行的向量矩阵乘法。C3SRAM在MNIST和CIFAR-10数据集上的准确率分别达到了98.3%和85.5%,达到了672 TOPS/W和1638 GOPS。实现了比传统数字处理器低3975倍的能量延迟积。
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C3SRAM: In-Memory-Computing SRAM Macro Based on Capacitive-Coupling Computing
This letter presents C3SRAM, an in-memory-computing SRAM macro, which utilizes analog-mixed-signal capacitive-coupling computing to perform XNOR-and-accumulate operations for binary deep neural networks. The 256 × 64 C3SRAM macro asserts all 256 rows simultaneously and equips one ADC per column, realizing fully parallel vector-matrix multiplication in one cycle. C3SRAM demonstrates 672 TOPS/W and 1638 GOPS, and achieves 98.3% accuracy for MNIST and 85.5% for CIFAR-10 dataset. It achieves 3975× smaller energy-delay product than conventional digital processors.
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