Search Results - "Analog In-Memory Computing"

Edge Training and Inference with Analog ReRAM Technology for Hand Gesture Recognition

Authors: Clerico, Victoria Dutta, Anirvan Falcone, Donato Francesco et al.

Source: 2025 IEEE International Symposium on Circuits and Systems (ISCAS). :1-5

Subject Terms: Signal Processing (eess.SP), Human-Machine Interaction, Analog In-Memory Computing, FOS: Electrical engineering, electronic engineering, information engineering, SDG 7 - Affordable and Clean Energy, Electrical Engineering and Systems Science - Signal Processing, nalog ReRAM, Edge AI, Hand gesture recognition, SDG 7 – Betaalbare en schone energie

Access URL: http://arxiv.org/abs/2502.18152

Multi-Mode Borderguard Controllers for Efficient On-Chip Communication in Heterogeneous Digital/Analog Neural Processing Units

Authors: Pang, Hong Cappetta, Carmine Massa, Riccardo et al.

Source: 2025 Design, Automation & Test in Europe Conference (DATE)

Subject Terms: Heterogeneous Neural Processing Unit, Data Communication, Analog In-Memory Computing, Edge AI

Access URL: http://hdl.handle.net/20.500.11850/749321

Controlled Acceleration of PCM Cells Time Drift Through On-Chip Current-Induced Annealing for AIMC Multilevel MVM Computation

Authors: Alessio Antolini Francesco Zavalloni Andrea Lico et al.

Contributors: Alessio Antolini Francesco Zavalloni Andrea Lico et al.

Source: IEEE Transactions on Electron Devices. 72:215-221

Subject Terms: Phase change materials, Programming, Annealing, Lattices, Standards, Artificial neural networks, Accuracy, Phase change memory, IP networks, Temperature measurement, Analog in-memory computing (AIMC), deep neural network (DNN), drift compensation, matrix-vector multiplication (MVM), phase-change memory (PCM)

File Description: application/pdf

Access URL: https://ieeexplore.ieee.org/document/10758353
https://hdl.handle.net/11585/997798
https://doi.org/10.1109/TED.2024.3496445

A Bit-Line Biasing Circuit for Analog In-Memory Computing Based on Phase Change Memory

Authors: A. Lico A. Antolini F. Zavalloni et al.

Source: 2024 19th Conference on Ph.D Research in Microelectronics and Electronics (PRIME)

Subject Terms: Analog In-memory Computing (AIMC)), Phase change Memory (PCM), Biasing Circuit

Access URL: https://hdl.handle.net/11585/972711

Drift-Tolerant Implementation of a Neural Network on a PCM-Based Analog In-Memory Computing Unit for Motor Control Applications

Authors: F. Zavalloni A. Antolini M. L. Torres et al.

Source: 2024 19th Conference on Ph.D Research in Microelectronics and Electronics (PRIME)

Subject Terms: Phase-change Memory (PCM), Analog In-memory Computing (AIMC), Proportional-Integral-Derivative (PID), Motor Control, Artificial Intelligence

Access URL: https://hdl.handle.net/11585/972712

A Precision-Optimized Fixed-Point Near-Memory Digital Processing Unit for Analog In-Memory Computing

Authors: Ferro E. Vasilopoulos A. Lammie C. et al.

Source: 2024 IEEE International Symposium

Subject Terms: FOS: Computer and information sciences, Computer Science - Machine Learning, AI, Analog in-memory computing, Deep learning, Fixed-point computing, Near-memory processing, Emerging Technologies (cs.ET), Hardware Architecture (cs.AR), Computer Science - Emerging Technologies, Computer Science - Hardware Architecture, Machine Learning (cs.LG)

Access URL: http://arxiv.org/abs/2402.07549

Disturbance‐Aware On‐Chip Training with Mitigation Schemes for Massively Parallel Computing in Analog Deep Learning Accelerator

Authors: Jaehyeon Kang Jongun Won Narae Han et al.

Source: Adv Sci (Weinh)
Advanced Science, Vol 12, Iss 23, Pp n/a-n/a (2025)

Subject Terms: IGZO TFT, Analog in‐memory computing, Disturbance‐aware training, Science, Neuromorphic, Disturbance, Half‐selected, Research Article

Access URL: https://pubmed.ncbi.nlm.nih.gov/40390534
https://doaj.org/article/d1bfbf3b951040bf9f44533150280cfa

A Readout Scheme for PCM-Based Analog In-Memory Computing With Drift Compensation Through Reference Conductance Tracking

Authors: Alessio Antolini Andrea Lico Francesco Zavalloni et al.

Source: IEEE Open Journal of the Solid-State Circuits Society, Vol 4, Pp 69-82 (2024)
IEEE Open Journal of the Solid-State Circuits Society

Subject Terms: 0301 basic medicine, 0303 health sciences, 03 medical and health sciences, Analog In-memory Computing (AIMC), Artificial Intelligence, Drift Compensation, Matrix-vector Multiplication (MVM), Phase-change Memory (PCM), drift compensation, phase-change memory (PCM), Electric apparatus and materials. Electric circuits. Electric networks, artificial intelligence, TK452-454.4, Analog in-memory computing (AIMC), matrix-vector multiplication (MVM)

File Description: application/pdf

Access URL: https://doaj.org/article/410dac993f694d3ba1f6f8a8600151c0
https://ieeexplore.ieee.org/document/10609348
https://hdl.handle.net/11585/976134
https://doi.org/10.1109/ojsscs.2024.3432468

Enhancing Vibration Inspection via Compressed Sensing Based on Embedded Phase Change Memories

Authors: Zonzini, Federica Zavalloni, Francesco Martinelli, Daniele et al.

Source: Lecture Notes in Electrical Engineering ISBN: 9783031715174

Subject Terms: Analog In-memory Computing, Compressed Sensing, Embedded Phase Change Memory, Vibration Inspection

File Description: application/pdf

Evaluating an Analog Main Memory Architecture for All-Analog In-Memory Computing Accelerators

Authors: Monga Dipesh Singh Gaurav Andraud Martin et al.

Contributors: Monga Dipesh Singh Gaurav Andraud Martin et al.

Source: 2024 IEEE 6th International Conference on AI Circuits and Systems (AICAS). :248-252

Subject Terms: Analog in memory Computing, Analog Memory

File Description: application/pdf

Access URL: https://aaltodoc.aalto.fi/handle/123456789/134075

Boosting RRAM-Based Mixed-Signal Accelerators in FD-SOI Technology for ML Applications

Authors: Andrea Boni Francesco Malena Francesco Saccani et al.

Contributors: Andrea Boni Francesco Malena Francesco Saccani et al.

Source: IEEE Journal on Exploratory Solid-State Computational Devices and Circuits, Vol 9, Iss 2, Pp 159-167 (2023)

Subject Terms: Computer engineering. Computer hardware, Convolutional Neural Networks, resistive random access memory (RRAM), 02 engineering and technology, Settore IINF-01/A - Elettronica, RRAM, 7. Clean energy, Analog in-memory computing, TK7885-7895, mixed-signal accelerators, convolutional neural networks, 0202 electrical engineering, electronic engineering, information engineering, Settore IINF-05/A - Sistemi di elaborazione delle informazioni, Analog in-Memory Computing, FD-SOI, Mixed-signal Accelerators

Access URL: https://doaj.org/article/9e67aea22ed44814bf0a3db8e7495b83

Analog or Digital In-Memory Computing? Benchmarking Through Quantitative Modeling

Authors: Sun, Jiacong Houshmand, Pouya Verhelst, Marian

Source: 2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD)

Subject Terms: Signal Processing (eess.SP), FOS: Computer and information sciences, Technology, DESIGN SPACE EXPLORATION, Science & Technology, digital in-memory computing, Image and Video Processing (eess.IV), Engineering, Electrical & Electronic, Electrical Engineering and Systems Science - Image and Video Processing, 7. Clean energy, Engineering, Manufacturing, quantitative modeling, Engineering, Computer Science, Theory & Methods, analog in-memory computing, Computer Science, Machine learning, Hardware Architecture (cs.AR), FOS: Electrical engineering, electronic engineering, information engineering, Electrical Engineering and Systems Science - Signal Processing, Computer Science - Hardware Architecture

Access URL: http://arxiv.org/abs/2405.14978
https://lirias.kuleuven.be/handle/20.500.12942/735240
https://doi.org/10.1109/iccad57390.2023.10323763

Device Specifications for Neural Network Training with Analog Resistive Cross‐Point Arrays Using Tiki‐Taka Algorithms

Authors: Jinho Byun Seungkun Kim Doyoon Kim et al.

Source: Advanced Intelligent Systems, Vol 7, Iss 5, Pp n/a-n/a (2025)

Subject Terms: analog in‐memory computing, deep learning accelerator, device specification, neural network, Tiki‐Taka algorithm, Computer engineering. Computer hardware, TK7885-7895, Control engineering systems. Automatic machinery (General), TJ212-225

File Description: electronic resource

Relation: https://doaj.org/toc/2640-4567

Access URL: https://doaj.org/article/fdfd171e25ef4d67ab9685b4d4e2b1eb

The Role of Phase-Change Memory in Edge Computing and Analog In-Memory Computing: An Overview of Recent Research Contributions and Future Challenges

Authors: Alessio Antolini Francesco Zavalloni Andrea Lico et al.

Contributors: Alessio Antolini Francesco Zavalloni Andrea Lico et al.

Subject Terms: phase-change memory (PCM), analog in-memory computing (AIMC), edge computing, neural network, artificial intelligence, structural health monitoring (SHM), human body monitoring

File Description: ELETTRONICO

Relation: info:eu-repo/semantics/altIdentifier/wos/WOS:001516356200001; volume:12; firstpage:1; lastpage:18; numberofpages:18; journal:SENSORS; https://hdl.handle.net/11585/1017419

Availability: https://hdl.handle.net/11585/1017419
https://doi.org/10.3390/s25123618
https://www.mdpi.com/1424-8220/25/12/3618

A 64-core mixed-signal in-memory compute chip based on phase-change memory for deep neural network inference

Authors: Manuel Le Gallo Riduan Khaddam-Aljameh Milos Stanisavljevic et al.

Source: Nature Electronics. 6:680-693

Subject Terms: 0301 basic medicine, FOS: Computer and information sciences, 0303 health sciences, 03 medical and health sciences, Emerging Technologies (cs.ET), 0103 physical sciences, 0202 electrical engineering, electronic engineering, information engineering, Computer Science - Emerging Technologies, Analog in memory computing, Phase Change Memory, LSTM network, CNN, DNN, 02 engineering and technology, 01 natural sciences, 7. Clean energy

File Description: application/pdf

Access URL: http://arxiv.org/abs/2212.02872

An embedded PCM Peripheral Unit adding Analog MAC In-Memory Computing Feature addressing Non-linearity and Time Drift Compensation

Authors: Alessio Antolini Andrea Lico Eleonora Franchi Scarselli et al.

Source: ESSCIRC 2022: IEEE 48th European Solid-State Circuits Conference
ESSCIRC 2022-IEEE 48th European Solid State Circuits Conference (ESSCIRC)

Subject Terms: Analog in-memory computing (AIMC), drift compensation, multiply and accumulate operation (MAC), Phase-change memory (PCM), 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

File Description: application/pdf

Combined HW/SW Drift and Variability Mitigation for PCM-Based Analog In-Memory Computing for Neural Network Applications

Authors: Alessio Antolini Carmine Paolino Francesco Zavalloni et al.

Contributors: Alessio Antolini Carmine Paolino Francesco Zavalloni et al.

Source: IEEE Journal on Emerging and Selected Topics in Circuits and Systems, vol. 13, no. 1, pp. 395-407, March 2023

Subject Terms: Analog In-memory Computing (AIMC), Phase-Change Memory (PCM), Deep Neural Network (DNN), Noise-Aware Training, Drift Compensation, 0103 physical sciences, 0202 electrical engineering, electronic engineering, information engineering, PhaseChange Memory (PCM), NoiseAware Training, 02 engineering and technology, 01 natural sciences

File Description: application/pdf

Access URL: https://hdl.handle.net/11583/2976687
https://doi.org/10.1109/JETCAS.2023.3241750
https://ieeexplore.ieee.org/document/10035378
https://hdl.handle.net/11585/913711
https://doi.org/10.1109/JETCAS.2023.3241750
https://ieeexplore.ieee.org/document/10035378

AIMC Modeling and Parameter Tuning for Layer-Wise Optimal Operating Point in DNN Inference

Authors: Dadras, Iman Sarda, Giuseppe M. Laubeuf, Nathan et al.

Source: IEEE Access, Vol 11, Pp 87189-87199 (2023)

Subject Terms: Technology, convolutional neural network (CNN), Science & Technology, Computer Science, Information Systems, Engineering, Electrical & Electronic, modeling, 46 Information and computing sciences, Analog in-memory computing (AIMC), 09 Engineering, TK1-9971, deep neural network (DNN), Engineering, artificial intelligence hardware acceleration, 10 Technology, Computer Science, Telecommunications, characterization, quantization, 08 Information and Computing Sciences, Electrical engineering. Electronics. Nuclear engineering, application-specific integrated circuit (ASIC), CNN, 40 Engineering

Access URL: https://doaj.org/article/de141c8430ce4cdfb8161d62c76e1beb

Prospects of analog in-memory computing using ferroelectric tunnel junctions

Authors: Mattias Borg Christos Papadopoulos Alec Guerin et al.

Source: Neuromorphic Computing and Engineering, Vol 5, Iss 2, p 024006 (2025)

Subject Terms: memristor, analog in-memory computing (AIMC), ferroelectric tunnel junction (FTJ), neuromorphic computing, BERT, Yolo, Electronic computers. Computer science, QA75.5-76.95

File Description: electronic resource

Relation: https://doaj.org/toc/2634-4386

Access URL: https://doaj.org/article/fe2ab37fa6e349ec94efc9a21ea92d80

A Binary Pattern Matching Task Performed in an ePCM-Based Analog In-Memory Computing Unit

Authors: Zavalloni, Francesco Antolini, Alessio Lico, Andrea et al.

Contributors: Zavalloni, Francesco Antolini, Alessio Lico, Andrea et al.

Subject Terms: Analog In-memory Computing (AIMC), Phase-change Memory (PCM), Binary Pattern Matching

File Description: ELETTRONICO

Relation: info:eu-repo/semantics/altIdentifier/isbn/978-3-031-48710-1; info:eu-repo/semantics/altIdentifier/isbn/978-3-031-48711-8; info:eu-repo/semantics/altIdentifier/wos/WOS:001455978800001; ispartofbook:Proceedings of SIE 2023; 54th Annual Meeting of the Italian Electronics Society; volume:1113; firstpage:3; lastpage:11; numberofpages:9; serie:LECTURE NOTES IN ELECTRICAL ENGINEERING; alleditors:C. Ciofi, E. Limiti; https://hdl.handle.net/11585/949930

Availability: https://hdl.handle.net/11585/949930
https://doi.org/10.1007/978-3-031-48711-8_1
https://link.springer.com/book/10.1007/978-3-031-48711-8