Complementary Metal Oxide Semiconductor

Complementary Metal-Oxide-Semiconductor (CMOS) technology is being extensively re-purposed to create energy-efficient hardware for machine learning, particularly focusing on neuromorphic computing architectures like spiking neural networks (SNNs) and reservoir computing. Current research emphasizes developing low-power analog and mixed-signal CMOS circuits for implementing neurons and synapses, often incorporating memristors or other emerging technologies to enhance performance and reduce power consumption. This work is significant because it enables the development of powerful, energy-efficient edge devices for applications ranging from sensor processing and AI acceleration to advanced robotics and telecommunications.

Papers

November 11, 2024

Spiking Transformer Hardware Accelerators in 3D Integration
Boxun Xu, Junyoung Hwang, Pruek Vanna-iampikul, Sung Kyu Lim, Peng Li
Transformer Architecture Neuromorphic Hardware Computation Method Spiking Transformer Complementary Metal Oxide Semiconductor

October 21, 2024

TEXEL: A neuromorphic processor with on-chip learning for beyond-CMOS device integration
Hugh Greatorex, Ole Richter, Michele Mastella, Madison Cotteret, Philipp Klein, Maxime Fabre, Arianna Rubino, Willian Soares Girão, Junren Chen, Martin Ziegler, Laura Bégon-Lours, Giacomo Indiveri, Elisabetta Chicca
Neuromorphic Computing Complementary Metal Oxide Semiconductor Mixed Signal Neuromorphic Better on Chip Data

October 15, 2024

DPD-NeuralEngine: A 22-nm 6.6-TOPS/W/mm$^2$ Recurrent Neural Network Accelerator for Wideband Power Amplifier Digital Pre-Distortion
Ang Li, Haolin Wu, Yizhuo Wu, Qinyu Chen, Leo C. N. de Vreede, Chang Gao
Recurrent Neural Network Gated Recurrent Unit Phantom 2D Accelerator Neural CDEs Complementary Metal Oxide Semiconductor Digital Pre Distortion

October 11, 2024

Energy-efficient SNN Architecture using 3nm FinFET Multiport SRAM-based CIM with Online Learning
Lucas Huijbregts, Liu Hsiao-Hsuan, Paul Detterer, Said Hamdioui, Amirreza Yousefzadeh, Rajendra Bishnoi
Spiking Neural Network Online Learning Energy Efficient Complementary Metal Oxide Semiconductor Current Artificial Intelligence

October 7, 2024

Hardware-Software Co-optimised Fast and Accurate Deep Reconfigurable Spiking Inference Accelerator Architecture Design Methodology
Anagha Nimbekar, Prabodh Katti, Chen Li, Bashir M. Al-Hashimi, Amit Acharyya, Bipin Rajendran
Spiking Neural Network Hardware Accelerator Complementary Metal Oxide Semiconductor SoC FPGA

September 28, 2024

Co-design of a novel CMOS highly parallel, low-power, multi-chip neural network accelerator
W Hokenmaier, R Jurasek, E Bowen, R Granger, D Odom
Co Design Chip Design Neural Network Accelerator Complementary Metal Oxide Semiconductor Dual Network AI Hardware VLSI Design

September 21, 2024

QMOS: Enhancing LLMs for Telecommunication with Question Masked loss and Option Shuffling
Blessed Guda, Gabrial Zencha A., Lawrence Francis, Carlee Joe-Wong
Large Language Model Retrieval Augmented Generation Question Answering Yes No Question Smaller Language Model Continuous Option Telecom Domain Complementary Metal Oxide Semiconductor

September 18, 2024

Hardware-Friendly Implementation of Physical Reservoir Computing with CMOS-based Time-domain Analog Spiking Neurons
Nanako Kimura, Ckristian Duran, Zolboo Byambadorj, Ryosho Nakane, Tetsuya Iizuka
Complementary Metal Oxide Semiconductor Hardware Implementation Physical Reservoir Computing Coupled Oscillator

August 14, 2024

Analog Spiking Neuron in CMOS 28 nm Towards Large-Scale Neuromorphic Processors
Marwan Besrour, Jacob Lavoie, Takwa Omrani, Gabriel Martin-Hardy, Esmaeil Ranjbar Koleibi, Jeremy Menard, Konin Koua, Philippe Marcoux, Mounir Boukadoum, Rejean Fontaine
Spiking Neural Network Neuron Model Complementary Metal Oxide Semiconductor Leaky Integrate and Fire Mixed Signal Neuromorphic Large Scale Neuromorphic

May 30, 2024

Autonomous programmable microscopic electronic lablets optimized with digital control
Thomas Maeke, John McCaskill, Dominic Funke, Pierre Mayr, Abhishek Sharma, Uwe Tangen, Jürgen Oehm
Legal Autonomy Electrode Array Complementary Metal Oxide Semiconductor Control Architecture Self Propelled Particle Power Capacitor

May 22, 2024

Time-Series Forecasting and Sequence Learning Using Memristor-based Reservoir System
Abdullah M. Zyarah, Dhireesha Kudithipudi
Time Series Forecasting Edge Device Memristive Device Echo State Network Complementary Metal Oxide Semiconductor Sequence Learning Memristive Reservoir

April 26, 2024

Embedded FPGA Developments in 130nm and 28nm CMOS for Machine Learning in Particle Detector Readout
Julia Gonski, Aseem Gupta, Haoyi Jia, Hyunjoon Kim, Lorenzo Rota, Larry Ruckman, Angelo Dragone, Ryan Herbst
Machine Learning Field Programmable Gate Array Multi FPGA Complementary Metal Oxide Semiconductor FPGA Implementation Particle Detector Readout Head

March 5, 2024

Mem-elements based Neuromorphic Hardware for Neural Network Application
Ankur Singh
Neuromorphic Hardware CNN Accelerator Complementary Metal Oxide Semiconductor Neural Network Application

August 18, 2023

Constrained Bayesian Optimization Using a Lagrange Multiplier Applied to Power Transistor Design
Ping-Ju Chuang, Ali Saadat, Sara Ghazvini, Hal Edwards, William G. Vandenberghe
Bayesian Optimization Objective Function Complementary Metal Oxide Semiconductor Lagrange Multiplier

July 12, 2023

Neuromorphic analog circuits for robust on-chip always-on learning in spiking neural networks
Arianna Rubino, Matteo Cartiglia, Melika Payvand, Giacomo Indiveri
Neural Network Chip Design Complementary Metal Oxide Semiconductor Chip Learning Mixed Signal Neuromorphic

April 12, 2023

CMOS + stochastic nanomagnets: heterogeneous computers for probabilistic inference and learning
Nihal Sanjay Singh, Keito Kobayashi, Qixuan Cao, Kemal Selcuk, Tianrui Hu, Shaila Niazi, Navid Anjum Aadit, Shun Kanai, Hideo Ohno, Shunsuke Fukami, Kerem Y. Camsari
Heterogeneous Computing Bayesian Computation Complementary Metal Oxide Semiconductor Magnetic Tunnel Junction

February 13, 2023

A full-stack view of probabilistic computing with p-bits: devices, architectures and algorithms
Shuvro Chowdhury, Andrea Grimaldi, Navid Anjum Aadit, Shaila Niazi, Masoud Mohseni, Shun Kanai, Hideo Ohno, Shunsuke Fukami, Luke Theogarajan, Giovanni Finocchio, Supriyo Datta, Kerem Y. Camsari
Practical Algorithm Smart Device P Bit Energy Efficient Inference Bayesian Computation Complementary Metal Oxide Semiconductor

August 25, 2022

CMOS-based area-and-power-efficient neuron and synapse circuits for time-domain analog spiking neural networks
Xiangyu Chen, Zolboo Byambadorj, Takeaki Yajima, Hisashi Inoue, Isao H. Inoue, Tetsuya Iizuka
Neural Network Energy Efficient Analog Circuit Complementary Metal Oxide Semiconductor Neural Structure Virtual Analog

August 2, 2022

Analog Gated Recurrent Neural Network for Detecting Chewing Events
Kofi Odame, Maria Nyamukuru, Mohsen Shahghasemi, Shengjie Bi, David Kotz
Neural Network Recurrent Neural Network Analog Neural Network Complementary Metal Oxide Semiconductor Virtual Analog

May 13, 2022

Toward A Formalized Approach for Spike Sorting Algorithms and Hardware Evaluation
Tim Zhang, Corey Lammie, Mostafa Rahimi Azghadi, Amirali Amirsoleimani, Majid Ahmadi, Roman Genov
Spike Train Neural Recording Resistive Random Access Memory Complementary Metal Oxide Semiconductor Hardware Debugging Spike Sorting

Complementary Metal Oxide Semiconductor

Papers

Spiking Transformer Hardware Accelerators in 3D Integration

TEXEL: A neuromorphic processor with on-chip learning for beyond-CMOS device integration

DPD-NeuralEngine: A 22-nm 6.6-TOPS/W/mm$^2$ Recurrent Neural Network Accelerator for Wideband Power Amplifier Digital Pre-Distortion

Energy-efficient SNN Architecture using 3nm FinFET Multiport SRAM-based CIM with Online Learning

Hardware-Software Co-optimised Fast and Accurate Deep Reconfigurable Spiking Inference Accelerator Architecture Design Methodology

Co-design of a novel CMOS highly parallel, low-power, multi-chip neural network accelerator

QMOS: Enhancing LLMs for Telecommunication with Question Masked loss and Option Shuffling

Hardware-Friendly Implementation of Physical Reservoir Computing with CMOS-based Time-domain Analog Spiking Neurons

Analog Spiking Neuron in CMOS 28 nm Towards Large-Scale Neuromorphic Processors

Autonomous programmable microscopic electronic lablets optimized with digital control

Time-Series Forecasting and Sequence Learning Using Memristor-based Reservoir System

Embedded FPGA Developments in 130nm and 28nm CMOS for Machine Learning in Particle Detector Readout

Mem-elements based Neuromorphic Hardware for Neural Network Application

Constrained Bayesian Optimization Using a Lagrange Multiplier Applied to Power Transistor Design

Neuromorphic analog circuits for robust on-chip always-on learning in spiking neural networks

CMOS + stochastic nanomagnets: heterogeneous computers for probabilistic inference and learning

A full-stack view of probabilistic computing with p-bits: devices, architectures and algorithms

CMOS-based area-and-power-efficient neuron and synapse circuits for time-domain analog spiking neural networks

Analog Gated Recurrent Neural Network for Detecting Chewing Events

Toward A Formalized Approach for Spike Sorting Algorithms and Hardware Evaluation