mlsanityData to 7 Oct 2026

Cross-Layer Design for AI Acceleration with Non-Coherent Optical Computing

arXiv 2303.12910 ↗First posted 22 Mar 2023cs.LG cs.AR cs.ETcited by 3

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Abstract (arXiv)

Emerging AI applications such as ChatGPT, graph convolutional networks, and other deep neural networks require massive computational resources for training and inference. Contemporary computing platforms such as CPUs, GPUs, and TPUs are struggling to keep up with the demands of these AI applications. Non-coherent optical computing represents a promising approach for light-speed acceleration of AI workloads. In this paper, we show how cross-layer design can overcome challenges in non-coherent optical computing platforms. We describe approaches for optical device engineering, tuning circuit enhancements, and architectural innovations to adapt optical computing to a variety of AI workloads. We also discuss techniques for hardware/software co-design that can intelligently map and adapt AI software to improve its performance on non-coherent optical computing platforms.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 13 of its 31 references that are in the map. First posted on arXiv 22 Mar 2023.

Builds on

13 of 31 references.

References · 13

  1. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  2. 2017NullHop: A Flexible Convolutional Neural Network Accelerator Based on Sparse Representations of Feature Mapscited by 39
  3. 2021CrossLight: A Cross-Layer Optimized Silicon Photonic Neural Network Acceleratorcited by 29
  4. 2021A Survey on Silicon Photonics for Deep Learningcited by 23
  5. 2022AI and ML Accelerator Survey and Trendscited by 23
  6. 2019Digital Electronics and Analog Photonics for Convolutional Neural Networks (DEAP-CNNs)cited by 22
  7. 2021ROBIN: A Robust Optical Binary Neural Network Acceleratorcited by 15
  8. 2020INDRA: Intrusion Detection using Recurrent Autoencoders in Automotive Embedded Systemscited by 12
  9. 2022RecLight: A Recurrent Neural Network Accelerator with Integrated Silicon Photonicscited by 12
  10. 2021SONIC: A Sparse Neural Network Inference Accelerator with Silicon Photonics for Energy-Efficient Deep Learningcited by 10
  11. 2022A Silicon Photonic Accelerator for Convolutional Neural Networks with Heterogeneous Quantizationcited by 9
  12. 2022LoCI: An Analysis of the Impact of Optical Loss and Crosstalk Noise in Integrated Silicon-Photonic Neural Networkscited by 4
1 more
  1. 2022Robust Perception Architecture Design for Automotive Cyber-Physical Systemscited by 4

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Cited by year

Citing papers per year: 2023: 1; 2024: 2.

3 papers.

  1. 2023GHOST: A Graph Neural Network Accelerator using Silicon Photonicscited by 7
  2. 2024SafeLight: Enhancing Security in Optical Convolutional Neural Network Acceleratorscited by 4
  3. 2024Accelerating Neural Networks for Large Language Models and Graph Processing with Silicon Photonicscited by 1