210 citations · 326 across the 7 of their papers we have counts for
8 papers
Multi-bit Ferroelectric-NAND for High-throughput Massive Database Search
Prasanna Venkatesan, Tanvir H. Pantha, Po-Kai Hsu +28
The growing demand for large-scale database search in data-intensive applications, ranging from proteomics to autonomous systems, has exposed fundamental limitations in von Neumann…
Protonic Nickelate Device Networks for Spatiotemporal Neuromorphic Computing
Yue Zhou, Shaan Shah, Tamal Dey +10
Computation in biological neural circuits arises from the interplay of nonlinear temporal responses and spatially distributed dynamic network interactions. Replicating this richnes…
FeNOMS: Enhancing Open Modification Spectral Library Search with In-Storage Processing on Ferroelectric NAND (FeNAND) Flash
Sumukh Pinge, Ashkan Moradifirouzabadi, Keming Fan +29
The rapid expansion of mass spectrometry (MS) data, now exceeding hundreds of terabytes, poses significant challenges for efficient, large-scale library search - a critical compone…
Multi-level, Forming Free, Bulk Switching Trilayer RRAM for Neuromorphic Computing at the Edge
Jaeseoung Park, Ashwani Kumar, Yucheng Zhou +9
Resistive memory-based reconfigurable systems constructed by CMOS-RRAM integration hold great promise for low energy and high throughput neuromorphic computing. However, most RRAM…
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…
Device and System Level Design Considerations for Analog-Non-Volatile-Memory Based Neuromorphic Architectures
Sukru Burc Eryilmaz, Duygu Kuzum, Shimeng Yu +1
This paper gives an overview of recent progress in the brain inspired computing field with a focus on implementation using emerging memories as electronic synapses. Design consider…
Brain-like associative learning using a nanoscale non-volatile phase change synaptic device array
Sukru Burc Eryilmaz, Duygu Kuzum, Rakesh Jeyasingh +4
Recent advances in neuroscience together with nanoscale electronic device technology have resulted in huge interests in realizing brain-like computing hardwares using emerging nano…
Experimental Demonstration of Array-level Learning with Phase Change Synaptic Devices
S. Burc Eryilmaz, Duygu Kuzum, Rakesh G. D. Jeyasingh +4
The computational performance of the biological brain has long attracted significant interest and has led to inspirations in operating principles, algorithms, and architectures for…