PISA: A Non-Volatile Processing-in-Sensor Accelerator for Imaging Systems
Document Type
Article
Publication Date
10-1-2023
Abstract
This work proposes a Processing-In-Sensor Accelerator, namely PISA, as a flexible, energy-efficient, and high-performance solution for real-Time and smart image processing in AI devices. PISA intrinsically implements a coarse-grained convolution operation in Binarized-Weight Neural Networks (BWNNs) leveraging a novel compute-pixel with non-volatile weight storage at the sensor side. This remarkably reduces the power consumption of data conversion and transmission to an off-chip processor. The design is completed with a bit-wise near-sensor in-memory computing unit to process the remaining network layers. Once the object is detected, PISA switches to typical sensing mode to capture the image for a fine-grained convolution using only a near-sensor processing unit. Our circuit-To-Application co-simulation results on a BWNN acceleration demonstrate minor accuracy degradation on various image datasets in coarse-grained evaluation compared to baseline BWNN models, while PISA achieves a frame rate of 1000 and efficiency of $\sim$∼ 1.74 TOp/s/W. Lastly, PISA substantially reduces data conversion and transmission energy by $\sim$∼ 84% compared to a baseline.
Identifier
85164697340 (Scopus)
Publication Title
IEEE Transactions on Emerging Topics in Computing
External Full Text Location
https://doi.org/10.1109/TETC.2023.3292251
e-ISSN
21686750
First Page
962
Last Page
972
Issue
4
Volume
11
Recommended Citation
Angizi, Shaahin; Tabrizchi, Sepehr; Pan, David Z.; and Roohi, Arman, "PISA: A Non-Volatile Processing-in-Sensor Accelerator for Imaging Systems" (2023). Faculty Publications. 1418.
https://digitalcommons.njit.edu/fac_pubs/1418