3k citations · 3.1k across the 8 of their papers we have counts for
8 papers
Device Modeling Bias in ReRAM-based Neural Network Simulations
Osama Yousuf, Imtiaz Hossen, Matthew W. Daniels +3
Data-driven modeling approaches such as jump tables are promising techniques to model populations of resistive random-access memory (ReRAM) or other emerging memory devices for har…
Memory-efficient training with streaming dimensionality reduction
Siyuan Huang, Brian D. Hoskins, Matthew W. Daniels +2
The movement of large quantities of data during the training of a Deep Neural Network presents immense challenges for machine learning workloads. To minimize this overhead, especia…
Roadmap on Material-Function Mapping for Photonic-Electronic Hybrid Neural Networks
Mario Miscuglio, Gina C. Adam, Duygu Kuzum +1
Driven by machine-learning tasks neural networks have demonstrated useful capabilities as nonlinear hypothesis classifiers. The underlying technologies performing the dot product m…
Streaming Batch Eigenupdates for Hardware Neuromorphic Networks
Brian D. Hoskins, Matthew W. Daniels, Siyuan Huang +5
Neuromorphic networks based on nanodevices, such as metal oxide memristors, phase change memories, and flash memory cells, have generated considerable interest for their increased…
Stateful characterization of resistive switching TiO2 with electron beam induced currents
Brian D. Hoskins, Gina C. Adam, Evgheni Strelcov +4
Metal oxide resistive switches are increasingly important as possible artificial synapses in next generation neuromorphic networks. Nevertheless, there is still no codified set of…
Highly-Secure Physically Unclonable Cryptographic Primitives Using Nonlinear Conductance and Analog State Tuning in Memristive Crossbar Arrays
Hussein Nili, Gina C. Adam, Mirko Prezioso +4
The rapidly expanding hardware-intrinsic security primitives are aimed at addressing significant security challenges of a massively interconnected world in the age of information t…
Three-Dimensional Stateful Material Implication Logic
Gina C. Adam, Brian D. Hoskins, Mirko Prezioso +1
Monolithic three-dimensional integration of memory and logic circuits could dramatically improve performance and energy efficiency of computing systems. Some conventional and emerg…
Training and Operation of an Integrated Neuromorphic Network Based on Metal-Oxide Memristors
Mirko Prezioso, Farnood Merrikh-Bayat, Brian Hoskins +3
Despite all the progress of semiconductor integrated circuit technology, the extreme complexity of the human cerebral cortex makes the hardware implementation of neuromorphic netwo…