mlsanityData to 14 Oct 2026

BoolNet: Minimizing The Energy Consumption of Binary Neural Networks

arXiv 2106.06991 ↗First posted 13 Jun 2021cs.LG cs.AIcited by 6

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Abstract (arXiv)

Recent works on Binary Neural Networks (BNNs) have made promising progress in narrowing the accuracy gap of BNNs to their 32-bit counterparts. However, the accuracy gains are often based on specialized model designs using additional 32-bit components. Furthermore, almost all previous BNNs use 32-bit for feature maps and the shortcuts enclosing the corresponding binary convolution blocks, which helps to effectively maintain the accuracy, but is not friendly to hardware accelerators with limited memory, energy, and computing resources. Thus, we raise the following question: How can accuracy and energy consumption be balanced in a BNN network design? We extensively study this fundamental problem in this work and propose a novel BNN architecture without most commonly used 32-bit components: textitBoolNet. Experimental results on ImageNet demonstrate that BoolNet can achieve 4.6x energy reduction coupled with 1.2% higher accuracy than the commonly used BNN architecture Bi-RealNet. Code and trained models are available at: https://github.com/hpi-xnor/BoolNet.

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 37 of its 46 references that are in the map. First posted on arXiv 13 Jun 2021.

Builds on

37 of 46 references.

References · 37

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25 more
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Built on by

Cited by year

Citing papers per year: 2022: 4; 2023: 0; 2024: 1; 2025: 1.

6 papers.

  1. 2022A Comprehensive Survey on Model Quantization for Deep Neural Networks in Image Classificationcited by 65
  2. 2022F8Net: Fixed-Point 8-bit Only Multiplication for Network Quantizationcited by 28
  3. 2022Join the High Accuracy Club on ImageNet with A Binary Neural Network Ticketcited by 14
  4. 2025Neural Network Quantization for Microcontrollers: A Comprehensive Survey of Methods, Platforms, and Applicationscited by 7
  5. 2024Evaluating the Energy Consumption of Machine Learning: Systematic Literature Review and Experimentscited by 3
  6. 2022How to train accurate BNNs for embedded systems?cited by 1

Similar, not cited

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  1. 2024CycleBNN: Cyclic Precision Training in Binary Neural Networks
  2. 2023Optimizing data-flow in Binary Neural Networks
  3. 2021A comprehensive review of Binary Neural Network
  4. 2021Bit Error Tolerance Metrics for Binarized Neural Networks
  5. 2025BD-Net: Has Depth-Wise Convolution Ever Been Applied in Binary Neural Networks?
  6. 2022Energy awareness in low precision neural networks
  7. 2026PiC-BNN: A 128-kbit 65 nm Processing-in-CAM-Based End-to-End Binary Neural Network Accelerator
  8. 2024ZOBNN: Zero-Overhead Dependable Design of Binary Neural Networks with Deliberately Quantized Parameters