PINSim: A Processing In- and Near-Sensor Simulator to Model Intelligent Vision Sensors

This letter introduces PINSim, a user-friendly and flexible framework for simulating emerging smart vision sensors in the early design stages. PINSim enables the realization of integrated sensing and processing near and in the sensor, effectively addressing challenges such as data movement and power-hungry analog-to-digital converters. The framework offers a flexible interface and a wide range of design options for customizing the efficiency and accuracy of processing-near/in-sensor-based accelerators using a hierarchical structure. Its organization spans from the device level upward to the algorithm level. PINSim realizes instruction-accurate evaluation of circuit-level performance metrics. PINSim achieves over <inline-formula><tex-math notation="LaTeX">$25,000\times$</tex-math></inline-formula> speed-up compared to SPICE simulation with less than a 4.1% error rate on average. Furthermore, it supports both multilayer perceptron (MLP) and convolutional neural network (CNN) models, with limitations determined by IoT budget constraints. By facilitating the exploration and optimization of various design parameters, PiNSim empowers researchers and engineers to develop energy-efficient and high-performance smart vision sensors for a wide range of applications.

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Publication Details

Journal
IEEE Computer Architecture Letters
Published
2024-12-25
DOI
https://doi.org/10.1109/lca.2024.3522777
Citations
3
Primary Topic
Sensor Technology and Measurement Systems
Type
article
Field-Weighted Citation Impact
1.05
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article

PINSim: A Processing In- and Near-Sensor Simulator to Model Intelligent Vision Sensors

David Z. Pan, Sepehr Tabrizchi, Shaahin Angizi, Arman Roohi et al.
3 citations
IEEE Computer Architecture Letters
Sensor Technology and Measurement Systems
1.05
article

PINSim: A Processing In- and Near-Sensor Simulator to Model Intelligent Vision Sensors

David Z. Pan, Sepehr Tabrizchi, Shaahin Angizi, Arman Roohi, Mehrdad Morsali
article en
3 citations

Abstract

This letter introduces PINSim, a user-friendly and flexible framework for simulating emerging smart vision sensors in the early design stages. PINSim enables the realization of integrated sensing and processing near and in the sensor, effectively addressing challenges such as data movement and power-hungry analog-to-digital converters. The framework offers a flexible interface and a wide range of design options for customizing the efficiency and accuracy of processing-near/in-sensor-based accelerators using a hierarchical structure. Its organization spans from the device level upward to the algorithm level. PINSim realizes instruction-accurate evaluation of circuit-level performance metrics. PINSim achieves over <inline-formula><tex-math notation="LaTeX">$25,000\times$</tex-math></inline-formula> speed-up compared to SPICE simulation with less than a 4.1% error rate on average. Furthermore, it supports both multilayer perceptron (MLP) and convolutional neural network (CNN) models, with limitations determined by IoT budget constraints. By facilitating the exploration and optimization of various design parameters, PiNSim empowers researchers and engineers to develop energy-efficient and high-performance smart vision sensors for a wide range of applications.

IEEE Computer Architecture LettersVol. 24(1)
New Jersey Institute of Technology (US), University of Illinois Chicago (US), The University of Texas at Austin (US)
Openalex Percentile: Top 20%
Sensor Technology and Measurement Systems
1.05
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