ASiM, a PyTorch-based simulator for SRAM analog compute-in-memory, reveals that ADC readout noise of about 1 LSB can severely degrade DNN inference accuracy, especially for Transformers and ImageNet, and that hybrid analog-digital execution or majority voting mitigates this.
14.6 a 28nm 64kb bit- rotated hybrid-cim macro with an embedded sign-bit-processing array and a multi-bit-fusion dual-granularity cooperative quantizer,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.AR 1years
2024 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
ASiM: Modeling and Analyzing Inference Accuracy of SRAM-Based Analog CiM Circuits
ASiM, a PyTorch-based simulator for SRAM analog compute-in-memory, reveals that ADC readout noise of about 1 LSB can severely degrade DNN inference accuracy, especially for Transformers and ImageNet, and that hybrid analog-digital execution or majority voting mitigates this.