A survey of silicon photonics for energy-efficient manycore computing
S Pasricha, M Nikdast - IEEE Design & Test, 2020 - ieeexplore.ieee.org
A Survey of Silicon Photonics for Energy-Efficient Manycore Computing Page 1 60 2168-2356/20©2020
IEEE Copublished by the IEEE CEDA, IEEE CASS, IEEE SSCS, and TTTC IEEE Design&Test …
IEEE Copublished by the IEEE CEDA, IEEE CASS, IEEE SSCS, and TTTC IEEE Design&Test …
Design space exploration of microring resonators in silicon photonic interconnects: impact of the ring curvature
A detailed analysis of fundamental tradeoffs between ring radius and coupling gap size is
presented to draw realistic borders of the possible design space for microring resonators …
presented to draw realistic borders of the possible design space for microring resonators …
Tron: Transformer neural network acceleration with non-coherent silicon photonics
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 of …
natural language processing (NLP) and computer vision. However, the complex structure of …
LIBRA: Thermal and process variation aware reliability management in photonic networks-on-chip
IG Thakkar, S Pasricha - IEEE Transactions on Multi-Scale …, 2018 - ieeexplore.ieee.org
Silicon nanophotonics technology is being considered for future networks-on-chip (NoCs) as
it can enable high bandwidth density and lower latency with traversal of data at the speed of …
it can enable high bandwidth density and lower latency with traversal of data at the speed of …
A silicon photonic accelerator for convolutional neural networks with heterogeneous quantization
Parameter quantization in convolutional neural networks (CNNs) can help generate efficient
models with lower memory footprint and computational complexity. But, homogeneous …
models with lower memory footprint and computational complexity. But, homogeneous …
Optical Computing for Deep Neural Network Acceleration: Foundations, Recent Developments, and Emerging Directions
S Pasricha - arXiv preprint arXiv:2407.21184, 2024 - arxiv.org
Emerging artificial intelligence applications across the domains of computer vision, natural
language processing, graph processing, and sequence prediction increasingly rely on deep …
language processing, graph processing, and sequence prediction increasingly rely on deep …
ARXON: A Framework for Approximate Communication Over Photonic Networks-on-Chip
The approximate computing paradigm advocates for relaxing accuracy goals in applications
to improve energy-efficiency and performance. Recently, this paradigm has been explored …
to improve energy-efficiency and performance. Recently, this paradigm has been explored …
SOTERIA: exploiting process variations to enhance hardware security with photonic NoC architectures
SVR Chittamuru, IG Thakkar, V Bhat… - Proceedings of the 55th …, 2018 - dl.acm.org
Photonic networks-on-chip (PNoCs) enable high bandwidth on-chip data transfers by using
photonic waveguides capable of dense-wave-length-division-multiplexing (DWDM) for …
photonic waveguides capable of dense-wave-length-division-multiplexing (DWDM) for …
Exploiting process variations to secure photonic NoC architectures from snooping attacks
The compact size and high wavelength-selectivity of microring resonators (MRs) enable
photonic networks-on-chip (PNoCs) to utilize dense-wavelength-division-multiplexing …
photonic networks-on-chip (PNoCs) to utilize dense-wavelength-division-multiplexing …
ICES: an innovative crosstalk-efficient 2× 2 photonic-crystal switch
Crosstalk and insertion loss are the crucial determinants of ring resonated routers. A novel
2× 2 optical switch is proposed through a combination of broadband waveguide crossing …
2× 2 optical switch is proposed through a combination of broadband waveguide crossing …