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- W4383899462 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 <inline-formula xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink><tex-math notation=LaTeX>$sim$</tex-math></inline-formula> 1.74 TOp/s/W. Lastly, PISA substantially reduces data conversion and transmission energy by <inline-formula xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink><tex-math notation=LaTeX>$sim$</tex-math></inline-formula> 84% compared to a baseline." @default.
- W4383899462 created "2023-07-12" @default.
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- W4383899462 date "2023-01-01" @default.
- W4383899462 modified "2023-10-16" @default.
- W4383899462 title "PISA: A Non-Volatile Processing-In-Sensor Accelerator for Imaging Systems" @default.
- W4383899462 doi "https://doi.org/10.1109/tetc.2023.3292251" @default.
- W4383899462 hasPublicationYear "2023" @default.
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