activity
20142024
most citedBrain-like associative learning using a nanoscale non-volatile phase change synaptic device array

210 citations · 382 across the 9 of their papers we have counts for

collaborators

9 papers

cs.LG2024★ 1 cited

ScaleFold: Reducing AlphaFold Initial Training Time to 10 Hours

Feiwen Zhu, Arkadiusz Nowaczynski, Rundong Li +6

AlphaFold2 has been hailed as a breakthrough in protein folding. It can rapidly predict protein structures with lab-grade accuracy. However, its implementation does not include the…

cs.AR2021★ 11 cited

Edge AI without Compromise: Efficient, Versatile and Accurate Neurocomputing in Resistive Random-Access Memory

Weier Wan, Rajkumar Kubendran, Clemens Schaefer +11

Realizing today's cloud-level artificial intelligence functionalities directly on devices distributed at the edge of the internet calls for edge hardware capable of processing mult…

cs.IT2017★ 1 cited

Opportunities for Analog Coding in Emerging Memory Systems

Jesse H. Engel, S. Burc Eryilmaz, SangBum Kim +5

The exponential growth in data generation and large-scale data analysis creates an unprecedented need for inexpensive, low-latency, and high-density information storage. This need…

cs.NE2016★ 33 cited

Training a Probabilistic Graphical Model with Resistive Switching Electronic Synapses

S. Burc Eryilmaz, Emre Neftci, Siddharth Joshi +6

Current large scale implementations of deep learning and data mining require thousands of processors, massive amounts of off-chip memory, and consume gigajoules of energy. Emerging…

cs.NE2015★ 75 cited

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…

cs.NE2014★ 210 cited

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…

physics.optics2014★ 9 cited

Plasmonic Nanoslit Array Enhanced Metal-Semiconductor-Metal Optical Detectors

Sukru Burc Eryilmaz, Onur Tidin, Ali K. Okyay

Metallic nanoslit arrays integrated on germanium metal-semiconductor-metal photodetectors show many folds of absorption enhancement for transverse-magnetic polarization in the tele…

q-fin.ST2014★ 1 cited

Supervised classification-based stock prediction and portfolio optimization

Sercan Arik, Sukru Burc Eryilmaz, Adam Goldberg

As the number of publicly traded companies as well as the amount of their financial data grows rapidly, it is highly desired to have tracking, analysis, and eventually stock select…

cs.NE2014★ 41 cited

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…