The ModelCIMs framework has been developed for the training of CNNs/DNNs aware of SRAM-based compute in-memory accelerators non-idealities.
The ModelCIMs framework has been developed for the training of CNNs/DNNs aware of SRAM-based compute in-memory accelerators non-idealities.
--- Copyright/referencing ---
--- Copyright/referencing ---
Usage of this framework is subject to copyright policies. Please cite the original research paper
Usage of this framework is subject to copyright policies. Please cite the original research paper
"A. Kneip et al., A 1-to-4b 16.8-POPS/W 473-TOPS/mm2 6T-based In-Memory Computing SRAM in 22nm FD-SOI with Multi-Bit Analog Batch-Normalization, Proceedings of IEEE ESSCIRC 2022, pp. 1-4" when using it for academic or industrial purpose.
"A. Kneip et al., A 1-to-4b 16.8-POPS/W 473-TOPS/mm2 6T-based In-Memory Computing SRAM in 22nm FD-SOI with Multi-Bit Analog Batch-Normalization, Proceedings of IEEE ESSCIRC 2022, pp. 1-4" when using it for academic or industrial purpose.
