5 papers
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…
Photonics for Sustainable Computing
Farbin Fayza, Satyavolu Papa Rao, Darius Bunandar +2
Photonic integrated circuits are finding use in a variety of applications including optical transceivers, LIDAR, bio-sensing, photonic quantum computing, and Machine Learning (ML).…
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…
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…
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…