mlsanityData to 7 Oct 2026

A Silicon Photonic Accelerator for Convolutional Neural Networks with Heterogeneous Quantization

arXiv 2205.11244 ↗First posted 17 May 2022cs.AR cs.LGcited by 9

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Abstract (arXiv)

Parameter quantization in convolutional neural networks (CNNs) can help generate efficient models with lower memory footprint and computational complexity. But, homogeneous quantization can result in significant degradation of CNN model accuracy. In contrast, heterogeneous quantization represents a promising approach to realize compact, quantized models with higher inference accuracies. In this paper, we propose HQNNA, a CNN accelerator based on non-coherent silicon photonics that can accelerate both homogeneously quantized and heterogeneously quantized CNN models. Our analyses show that HQNNA achieves up to 73.8x better energy-per-bit and 159.5x better throughput-energy efficiency than state-of-the-art photonic CNN accelerators.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 8 of its 25 references that are in the map. First posted on arXiv 17 May 2022.

Builds on

8 of 25 references.

References · 8

  1. 2017To prune, or not to prune: exploring the efficacy of pruning for model compressioncited by 596
  2. 2018Mixed Precision Quantization of ConvNets via Differentiable Neural Architecture Searchcited by 122
  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. 2021ROBIN: A Robust Optical Binary Neural Network Acceleratorcited by 15
  6. 2020BitPruning: Learning Bitlengths for Aggressive and Accurate Quantizationcited by 14
  7. 2021ARXON: A Framework for Approximate Communication over Photonic Networks-on-Chipcited by 2
  8. 2020LORAX: Loss-Aware Approximations for Energy-Efficient Silicon Photonic Networks-on-Chipcited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 1; 2023: 2; 2024: 5; 2025: 0; 2026: 1.

9 papers.

  1. 2022RecLight: A Recurrent Neural Network Accelerator with Integrated Silicon Photonicscited by 12
  2. 2023Machine Learning Accelerators in 2.5D Chiplet Platforms with Silicon Photonicscited by 5
  3. 2024SafeLight: Enhancing Security in Optical Convolutional Neural Network Acceleratorscited by 4
  4. 2023Cross-Layer Design for AI Acceleration with Non-Coherent Optical Computingcited by 3
  5. 2024Accelerating Neural Networks for Large Language Models and Graph Processing with Silicon Photonicscited by 1
  6. 2024OPIMA: Optical Processing-In-Memory for Convolutional Neural Network Accelerationcited by 1
  7. 2024A Comparative Analysis of Microrings Based Incoherent Photonic GEMM Acceleratorscited by 0
  8. 2024Optical Computing for Deep Neural Network Acceleration: Foundations, Recent Developments, and Emerging Directionscited by 0
  9. 2026Accelerating Diffusion Models for Generative AI Applications with Silicon Photonicscited by 0