3 papers
cs.LG2021
Mitigating Adversarial Attack for Compute-in-Memory Accelerator Utilizing On-chip Finetune
Shanshi Huang, Hongwu Jiang, Shimeng Yu
Compute-in-memory (CIM) has been proposed to accelerate the convolution neural network (CNN) computation by implementing parallel multiply and accumulation in analog domain. Howeve…
eess.SP2020
New Security Challenges on Machine Learning Inference Engine: Chip Cloning and Model Reverse Engineering
Shanshi Huang, Xiaochen Peng, Hongwu Jiang +2
Machine learning inference engine is of great interest to smart edge computing. Compute-in-memory (CIM) architecture has shown significant improvements in throughput and energy eff…
cs.ET2020
DNN+NeuroSim V2.0: An End-to-End Benchmarking Framework for Compute-in-Memory Accelerators for On-chip Training
Xiaochen Peng, Shanshi Huang, Hongwu Jiang +2
DNN+NeuroSim is an integrated framework to benchmark compute-in-memory (CIM) accelerators for deep neural networks, with hierarchical design options from device-level, to circuit-l…