32 citations · 107 across the 33 of their papers we have counts for
37 papers
Right Device, Right Place: Variation-Aware Placement and Design Optimization for Robust Photonic Lattice-Filter Demultiplexers
Zahra Ghanaatian, Edwin K. P. Chong, Mahdi Nikdast
We propose a Bayesian co-optimization framework for robust integrated photonic lattice-filter demultiplexers, jointly optimizing device placement and design parameters under fabric…
LightPro: A Linear Photonic Processor with Full Programmability
Amin Shafiee, Zahra Ghanaatian, Benoit Charbonnier +1
In this paper, we propose a novel fully programmable linear photonic processor, which we call LightPro, with improved scalability, performance, and footprint. At the heart of Light…
LuxNAS: A Coherent Photonic Neural Network Powered by Neural Architecture Search
Amin Shafiee, Febin Sunny, Sudeep Pasricha +1
We demonstrate a novel coherent photonic neural network using tunable phase-change-material-based couplers and neural architecture search. Compared to the MZI-based Clements networ…
Enabling Scalable Photonic Tensor Cores with Polarization-Domain Photonic Computing
Amin Shafiee, Linhong Chen, Sudeep Pasricha +2
We present a silicon-photonic tensor core using 2D ferroelectric materials to enable wavelength- and polarization-domain computing. Results, based on experimentally characterized m…
Roadmap on Neuromorphic Photonics
Daniel Brunner, Bhavin J. Shastri, Mohammed A. Al Qadasi +147
This roadmap consolidates recent advances while exploring emerging applications, reflecting the remarkable diversity of hardware platforms, neuromorphic concepts, and implementatio…
OPIMA: Optical Processing-In-Memory for Convolutional Neural Network Acceleration
Febin Sunny, Amin Shafiee, Abhishek Balasubramaniam +2
Recent advances in machine learning (ML) have spotlighted the pressing need for computing architectures that bridge the gap between memory bandwidth and processing power. The adven…
Silicon Photonic 2.5D Interposer Networks for Overcoming Communication Bottlenecks in Scale-out Machine Learning Hardware Accelerators
Febin Sunny, Ebadollah Taheri, Mahdi Nikdast +1
Modern machine learning (ML) applications are becoming increasingly complex and monolithic (single chip) accelerator architectures cannot keep up with their energy efficiency and t…
Accelerating Neural Networks for Large Language Models and Graph Processing with Silicon Photonics
Salma Afifi, Febin Sunny, Mahdi Nikdast +1
In the rapidly evolving landscape of artificial intelligence, large language models (LLMs) and graph processing have emerged as transformative technologies for natural language pro…
COMET: A Cross-Layer Optimized Optical Phase Change Main Memory Architecture
Febin Sunny, Amin Shafiee, Benoit Charbonnier +2
Traditional DRAM-based main memory systems face several challenges with memory refresh overhead, high latency, and low throughput as the industry moves towards smaller DRAM cells.…
RISA: Round-Robin Intra-Rack Friendly Scheduling Algorithm for Disaggregated Datacenters
Rashadul Kabir, Ryan G. Kim, Mahdi Nikdast
Recent trends see a move away from a fixed-resource server-centric datacenter model to a more adaptable "disaggregated" datacenter model. These disaggregated datacenters can then d…
Compact and Low-Loss PCM-based Silicon Photonic MZIs for Photonic Neural Networks
Amin Shafiee, Sanmitra Banerjee, Benoit Charbonnier +2
We present an optimized Mach-Zehnder Interferometer (MZI) with phase change materials for photonic neural networks (PNNs). With 0.2 dB loss, -38 dB crosstalk, and length of 52 micr…
SerIOS: Enhancing Hardware Security in Integrated Optoelectronic Systems
Felipe Gohring de Magalhaes, Mahdi Nikdast, Gabriela Nicolescu
Silicon photonics (SiPh) has different applications, from enabling fast and high-bandwidth communication for high-performance computing systems to realizing energy-efficient optica…
Analysis of Optical Loss and Crosstalk Noise in MZI-based Coherent Photonic Neural Networks
Amin Shafiee, Sanmitra Banerjee, Krishnendu Chakrabarty +2
With the continuous increase in the size and complexity of machine learning models, the need for specialized hardware to efficiently run such models is rapidly growing. To address…
GHOST: A Graph Neural Network Accelerator using Silicon Photonics
Salma Afifi, Febin Sunny, Amin Shafiee +2
Graph neural networks (GNNs) have emerged as a powerful approach for modelling and learning from graph-structured data. Multiple fields have since benefitted enormously from the ca…
Design Space Exploration for PCM-based Photonic Memory
Amin Shafiee, Benoit Charbonnier, Sudeep Pasricha +1
The integration of silicon photonics (SiPh) and phase change materials (PCMs) has created a unique opportunity to realize adaptable and reconfigurable photonic systems. In particul…
TRON: Transformer Neural Network Acceleration with Non-Coherent Silicon Photonics
Salma Afifi, Febin Sunny, Mahdi Nikdast +1
Transformer neural networks are rapidly being integrated into state-of-the-art solutions for natural language processing (NLP) and computer vision. However, the complex structure o…
Cross-Layer Design for AI Acceleration with Non-Coherent Optical Computing
Febin Sunny, Mahdi Nikdast, Sudeep Pasricha
Emerging AI applications such as ChatGPT, graph convolutional networks, and other deep neural networks require massive computational resources for training and inference. Contempor…
Machine Learning Accelerators in 2.5D Chiplet Platforms with Silicon Photonics
Febin Sunny, Ebadollah Taheri, Mahdi Nikdast +1
Domain-specific machine learning (ML) accelerators such as Google's TPU and Apple's Neural Engine now dominate CPUs and GPUs for energy-efficient ML processing. However, the evolut…
RecLight: A Recurrent Neural Network Accelerator with Integrated Silicon Photonics
Febin Sunny, Mahdi Nikdast, Sudeep Pasricha
Recurrent Neural Networks (RNNs) are used in applications that learn dependencies in data sequences, such as speech recognition, human activity recognition, and anomaly detection.…
ReSiPI: A Reconfigurable Silicon-Photonic 2.5D Chiplet Network with PCMs for Energy-Efficient Interposer Communication
Ebadollah Taheri, Sudeep Pasricha, Mahdi Nikdast
2.5D chiplet systems have been proposed to improve the low manufacturing yield of large-scale chips. However, connecting the chiplets through an electronic interposer imposes a hig…
Characterizing Coherent Integrated Photonic Neural Networks under Imperfections
Sanmitra Banerjee, Mahdi Nikdast, Krishnendu Chakrabarty
Integrated photonic neural networks (IPNNs) are emerging as promising successors to conventional electronic AI accelerators as they offer substantial improvements in computing spee…
A Silicon Photonic Accelerator for Convolutional Neural Networks with Heterogeneous Quantization
Febin Sunny, Mahdi Nikdast, Sudeep Pasricha
Parameter quantization in convolutional neural networks (CNNs) can help generate efficient models with lower memory footprint and computational complexity. But, homogeneous quantiz…
Characterization and Optimization of Integrated Silicon-Photonic Neural Networks under Fabrication-Process Variations
Asif Mirza, Amin Shafiee, Sanmitra Banerjee +3
Silicon-photonic neural networks (SPNNs) have emerged as promising successors to electronic artificial intelligence (AI) accelerators by offering orders of magnitude lower latency…
LoCI: An Analysis of the Impact of Optical Loss and Crosstalk Noise in Integrated Silicon-Photonic Neural Networks
Amin Shafiee, Sanmitra Banerjee, Krishnendu Chakrabarty +2
Compared to electronic accelerators, integrated silicon-photonic neural networks (SP-NNs) promise higher speed and energy efficiency for emerging artificial-intelligence applicatio…