activity
20202025
most citedAn Electro-Photonic System for Accelerating Deep Neural Networks

65 citations · 90 across the 7 of their papers we have counts for

collaborators

7 papers

cs.LG2025

Systolic Array-based Accelerator for Structured State-Space Models

Shiva Raja, Cansu Demirkiran, Aakash Sarkar +2

Sequence modeling is crucial for AI to understand temporal data and detect complex time-dependent patterns. While recurrent neural networks (RNNs), convolutional neural networks (C…

cs.ET2023

Towards Efficient Hyperdimensional Computing Using Photonics

Farbin Fayza, Cansu Demirkiran, Hanning Chen +8

Over the past few years, silicon photonics-based computing has emerged as a promising alternative to CMOS-based computing for Deep Neural Networks (DNN). Unfortunately, the non-lin…

cs.AR2023★ 14 cited

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…

cs.ET2023★ 11 cited

A Blueprint for Precise and Fault-Tolerant Analog Neural Networks

Cansu Demirkiran, Lakshmi Nair, Darius Bunandar +1

Analog computing has reemerged as a promising avenue for accelerating deep neural networks (DNNs) due to its potential to overcome the energy efficiency and scalability challenges…

cs.AR2023

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…

cs.AR2021★ 65 cited

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…

cs.AR2020

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…