Abstract
This letter presents a computing-in-memory (CIM) static random-access memory (SRAM) using efficient data processing and conversion circuits to enhance the throughput, energy, and area efficiency performance. The proposed unified charge-processing network simultaneously provides both signal processing and data conversion functions with maximum resource utilization, realizing significant performance improvements in energy and area efficiency by 37.5% and 15.4%, respectively. Measurement results from a prototype fabricated in a 28-nm CMOS technology show that the proposed CIM SRAM achieves a high throughput of 186.18 GOPS, with energy and area efficiencies of 41.87 TOPS/W and 3288.4 GOPS/mm2, which demonstrates the performance improvements of 2.26×, 1.12×, and 2.89×, respectively, when compared with the state-of-the-art results. The proposed CIM SRAM can achieve 88.87% classification accuracy on the CIFAR-10 dataset.
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CITATION STYLE
Hsu, Y. T., Yao, C. Y., Wu, T. Y., Chiueh, T. D., & Liu, T. T. (2021). A High-Throughput Energy-Area-Efficient Computing-in-Memory SRAM Using Unified Charge-Processing Network. IEEE Solid-State Circuits Letters, 4, 146–149. https://doi.org/10.1109/LSSC.2021.3103759
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