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

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4b/4b/8b Precision Charge-Domain 8T-SRAM Based CiM for CNN Processing
Title:
4b/4b/8b Precision Charge-Domain 8T-SRAM Based CiM for CNN Processing
Journal Title:
2023 IEEE 5th International Conference on Artificial Intelligence Circuits and Systems (AICAS)
Keywords:
Publication Date:
07 July 2023
Citation:
Zang, Q., Goh, W. L., Chong, Y. S., Do, A. T. (2023, June 11). 4b/4b/8b Precision Charge-Domain 8T-SRAM Based CiM for CNN Processing. 2023 IEEE 5th International Conference on Artificial Intelligence Circuits and Systems (AICAS). https://doi.org/10.1109/aicas57966.2023.10168593
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, 2 N 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.
License type:
Publisher Copyright
Funding Info:
This research / project is supported by the A*STAR - Spin-Orbit Technologies for intelligence at the Edge (SpOT-LITE)
Grant Reference no. : A18A6b0057
Description:
© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
ISSN:
2834-9857
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