4b/4b/8b Precision Charge-Domain 8T-SRAM Based CiM for CNN Processing

Qibang Zang, W. Goh, Y. Chong, A. Do
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Abstract

Compute-in-memory (CiM) is a promising solution for solving the bottleneck of frequent data movement between the memory and processor in Von-Neumann architecture. In conventional multi-bit CiM architecture, when computing N-bit input and N-bit weight MAC operation, 2N 1 cycles are needed for N-bit input modulation and normally 3-4−cycles with complex switch operation are needed for N-bit weight realization, which significantly degrades the final throughput and power efficiency. In this work, a C-2C DAC built in the 8T SRAM CiM array is designed for 4-bit weight and 4-bit input MAC operation, which can be completed in just one cycle. In the final power efficiency evaluation, our 4b/4b/8b CiM architecture attained up to 640 TOPS/W (normalized to 1b/1b/1b precision) which is a 6-10 times improvement as compared to the conventional multi-bit CiM architectures. The proposed architecture with 4b/4b/8b precision can provide 91.47% and 68.10% accuracy on CIFAR-10 and CIFAR-100 dataset classification, respectively.
基于4b/4b/8b精密电荷域8T-SRAM的CiM用于CNN处理
内存计算(CiM)是解决冯-诺伊曼体系结构中数据在存储器和处理器之间频繁移动的瓶颈的一种很有前途的解决方案。在传统的多位CiM架构中,当计算n位输入和n位权重MAC操作时,n位输入调制需要2N个1周期,而n位权重实现通常需要3-4个−周期,且开关操作复杂,这大大降低了最终吞吐量和功耗效率。在这项工作中,构建在8T SRAM CiM阵列中的C-2C DAC设计用于4位重量和4位输入MAC操作,只需一个周期即可完成。在最终的功率效率评估中,我们的4b/4b/8b CiM架构达到了640 TOPS/W(归一化到1b/1b/1b精度),与传统的多位CiM架构相比,提高了6-10倍。本文提出的4b/4b/8b精度架构在CIFAR-10和CIFAR-100数据集分类上的准确率分别为91.47%和68.10%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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