DNN+NeuroSim V2.0: An End-to-End Benchmarking Framework for Compute-in-Memory Accelerators for On-chip Training

2 code implementations • 13 Mar 2020 • Xiaochen Peng, Shanshi Huang, Hongwu Jiang, Anni Lu, Shimeng Yu

Our prior work (DNN+NeuroSim V1. 1) was developed to estimate the impact of reliability in synaptic devices, and analog-to-digital converter (ADC) quantization loss on the accuracy and hardware performance of inference engines.

Benchmarking Quantization