deep neural network (DNN)

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High-Precision Close-to-Analog Programming of PCM Cells as Devices for AiMC Edge-AI

High-Precision Close-to-Analog Programming of PCM Cells as Devices for AiMC Edge-AI 150 150
Author(s): Alessio Antolini, Andrea Lico, Francesco Zavalloni, Lorenzo Greco, Riccardo Zurla, Jacopo Bertolini, Riccardo Vignali, Luca Iannelli, Emanuela Calvetti, Marco Pasotti, Alessandro Cabrini, Eleonora Franchi Scarselli

Abstract:

This article presents a high-precision close-to-analog programming methodology for phase-change memory (PCM) cells, targeting analog in-memory computing (AiMC) architectures for edge-artificial intelligence (AI) applications. By leveraging an iterative accumulation approach during the verify phase, the proposed technique enhances the effective number of bits (ENOBs) achievable in PCM cells. Experimental validation …

Published in: IEEE Journal of Solid-State Circuits
Page(s): 1 – 14
Year of Publication: 2026
Electronic ISSN: 1558-173X
DOI: 10.1109/JSSC.2026.3680266
Publisher: IEEE

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Birch: A Real-Time Multi-Domain Multi-Task Extended Reality Perception Accelerator

Birch: A Real-Time Multi-Domain Multi-Task Extended Reality Perception Accelerator 150 150
Author(s): Kathleen Feng, Kai Bartolone, Kartik Prabhu, Brianna McColm, Xingyu Ni, Siddhant Gupta, Priyanka Raina

Abstract:

Birch is a system-on-chip (SoC) that efficiently and accurately accelerates the multi-task multi-domain extended reality (XR) perception pipeline, with workloads such as visual inertial odometry (VIO), eye gaze tracking, and scene understanding. Birch features vision modules with cascaded line buffers, in-step feature sorting, and double-buffered optical flow to extract and …

Published in: IEEE Solid-State Circuits Letters
Page(s): 121 – 124
Year of Publication: 2026
Electronic ISSN: 2573-9603
DOI: 10.1109/LSSC.2026.3673168
Publisher: IEEE

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A 0.8-μm 32-Mpixel Always-On CMOS Image Sensor With Windmill-Pattern Edge Extraction and On-Chip DNN

A 0.8-μm 32-Mpixel Always-On CMOS Image Sensor With Windmill-Pattern Edge Extraction and On-Chip DNN 150 150
Author(s): Mamoru Sato, Sachio Akebono, Kazuyoshi Yasuoka, Eriko Kato, Masahiro Tsuruta, Chiaki Takano, Kensuke Ota, Kazuki Haraguchi, Masahiro Watanabe, Genki Fujii, Koichiro Yamanaka, Kazunori Yasuda, Satoshi Minami, Katsuhiko Hanzawa, Kohei Matsuda, Akihiko Kato, Yosuke Ueno

Abstract:

This letter presents a CMOS image sensor (CIS) that integrates two operation modes: 1) a high-resolution viewing mode with $0.8~\mu $ m 32 Mpixels and 2) a low-power always-on object recognition mode consuming 2.67 mW at 10 frames/s. The CIS features a unique windmill-pattern analog edge extraction circuit that is resilient to illumination variations. An …

Published in: IEEE Solid-State Circuits Letters
Page(s): 353 – 356
Year of Publication: 2025
Electronic ISSN: 2573-9603
DOI: 10.1109/LSSC.2025.3628314
Publisher: IEEE

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