65 citations · 90 across the 7 of their papers we have counts for
4 papers · 1 filter
Mirage: An RNS-Based Photonic Accelerator for DNN Training
Cansu Demirkiran, Guowei Yang, Darius Bunandar +1
Photonic computing is a compelling avenue for performing highly efficient matrix multiplication, a crucial operation in Deep Neural Networks (DNNs). While this method has shown gre…
Leveraging Residue Number System for Designing High-Precision Analog Deep Neural Network Accelerators
Cansu Demirkiran, Rashmi Agrawal, Vijay Janapa Reddi +2
Achieving high accuracy, while maintaining good energy efficiency, in analog DNN accelerators is challenging as high-precision data converters are expensive. In this paper, we over…
An Electro-Photonic System for Accelerating Deep Neural Networks
Cansu Demirkiran, Furkan Eris, Gongyu Wang +7
The number of parameters in deep neural networks (DNNs) is scaling at about 5 the rate of Moore's Law. To sustain this growth, photonic computing is a promising avenue, as…
Custom Tailored Suite of Random Forests for Prefetcher Adaptation
Furkan Eris, Sadullah Canakci, Cansu Demirkiran +1
To close the gap between memory and processors, and in turn improve performance, there has been an abundance of work in the area of data/instruction prefetcher designs. Prefetchers…