47 citations · 140 across the 19 of their papers we have counts for
7 papers · 1 filter
Pruning Coherent Integrated Photonic Neural Networks Using the Lottery Ticket Hypothesis
Sanmitra Banerjee, Mahdi Nikdast, Sudeep Pasricha +1
Singular-value-decomposition-based coherent integrated photonic neural networks (SC-IPNNs) have a large footprint, suffer from high static power consumption for training and infere…
CHAMP: Coherent Hardware-Aware Magnitude Pruning of Integrated Photonic Neural Networks
Sanmitra Banerjee, Mahdi Nikdast, Sudeep Pasricha +1
We propose a novel hardware-aware magnitude pruning technique for coherent photonic neural networks. The proposed technique can prune 99.45% of network parameters and reduce the st…
ReaLPrune: ReRAM Crossbar-aware Lottery Ticket Pruned CNNs
Biresh Kumar Joardar, Janardhan Rao Doppa, Hai Li +2
Training machine learning (ML) models at the edge (on-chip training on end user devices) can address many pressing challenges including data privacy/security, increase the accessib…
Multi-Objective Optimization of ReRAM Crossbars for Robust DNN Inferencing under Stochastic Noise
Xiaoxuan Yang, Syrine Belakaria, Biresh Kumar Joardar +5
Resistive random-access memory (ReRAM) is a promising technology for designing hardware accelerators for deep neural network (DNN) inferencing. However, stochastic noise in ReRAM c…
Optimizing Coherent Integrated Photonic Neural Networks under Random Uncertainties
Sanmitra Banerjee, Mahdi Nikdast, Krishnendu Chakrabarty
We propose an optimization method to improve power efficiency and robustness in silicon-photonic-based coherent integrated photonic neural networks. Our method reduces the network…
Exploring the Mysteries of System-Level Test
Ilia Polian, Jens Anders, Steffen Becker +7
System-level test, or SLT, is an increasingly important process step in today's integrated circuit testing flows. Broadly speaking, SLT aims at executing functional workloads in op…