Suchergebnisse - "In-memory computing"

Energy-Efficient Solid-State Oxide-Ion Electrochemical Synaptic Transistor for Neuromorphic Computing

Autoren: Langner, Philipp Lucas

Thesis Advisors: Chiabrera , Francesco Maria, Tarancón Rubio, Albert

Quelle: TDX (Tesis Doctorals en Xarxa)

Schlagwörter: ECRAM, Computació en memòria, In-memory computing, Computación en memoria, Transistor sinàptic d'ió-òxid, Oxide-ion synaptic transistor, Transistor sináptico de iones, Ciències Experimentals

Dateibeschreibung: application/pdf

Zugangs-URL: http://hdl.handle.net/10803/695623

Predictive Performance Modeling for SAP Systems and HANA Database: Leveraging Job History, Usage Patterns and Database Metrics for Proactive Optimization

Autoren: Kolluri, Srinivas

Quelle: International Journal of Science and Research Archive. 16:001-007

Schlagwörter: Machine Learning, Performance Optimization, Cloud Integration, Predictive Analytics, In-Memory Computing

Calibration-Free Edge-Computing IMC Macro With Direct Current-to-Digital Conversion

Autoren: Andrea Fasolino Rosalba Liguori Luigi Di Benedetto et al.

Quelle: IEEE Transactions on Circuits and Systems II: Express Briefs. 72:1018-1022

Schlagwörter: calibration-free, current source, edge computing, in-memory computing, multiply-accumulate, thermal stability, ultra-low power

Zugangs-URL: https://hdl.handle.net/11386/4914456
https://doi.org/10.1109/TCSII.2025.3581384

An Area-Efficient and Low-Latency Analog Content-Addressable Memory Design Using gm/ID Methodology with Memristors

Autoren: Nguyen, P. T. P. Phan, K. A. Tran, L.

Quelle: Radioengineering, Vol 34, Iss 1, Pp 155-165 (2025)

Schlagwörter: In-memory computing, in-memory computing, gm/id design methodology, analog CAM, analog cam, content-addressable memory, Electrical engineering. Electronics. Nuclear engineering, memristor, gm/ID design methodology, TK1-9971

Dateibeschreibung: text; application/pdf

Zugangs-URL: https://doaj.org/article/83d0700d2df940c89f31ce935313e191
https://hdl.handle.net/11012/250869

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

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

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

Schlagwörter: 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

Zugangs-URL: http://arxiv.org/abs/2502.18152

Edge-Embedded System-on-Chip Architecture for Unified Transformer-Based AI in Cross-Domain Energy Systems

Autoren: ZAIDI, ADNAN HAIDER

Quelle: International Journal for Research in Applied Science and Engineering Technology. 13:2450-2456

Schlagwörter: System-on-Chip, Transformer, Deep Learning, Smart Grid, UAV, Spacecraft, In-Memory Computing, Graph Neural Networks, Cross-Domain AI, Edge AI

In-Memory Implementation of an Approximate Adder With Reduced Latency and Error

Autoren: Vijaya Lakshmi Vikramkumar Pudi John Reuben

Quelle: IEEE Transactions on Circuits and Systems I: Regular Papers. 72:2128-2138

Schlagwörter: In-memory computing, approximate computing, 1T–1R array, resistive random access memory, speculative adder, error-tolerant, DDC Classification::6 Technik, Medizin, angewandte Wissenschaften::62 Ingenieurwissenschaften::620 Ingenieurwissenschaften und zugeordnete Bereiche

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

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

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

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

Zugangs-URL: http://hdl.handle.net/20.500.11850/749321

Recent advances in ferroelectric materials, devices, and in-memory computing applications

Autoren: Hwiho Hwang Sangwook Youn Hyungjin Kim

Quelle: Nano Convergence, Vol 12, Iss 1, Pp 1-31 (2025)

Schlagwörter: Ferroelectric thin films, Non-volatile memory devices, In-memory computing, Neuromorphic computing, Hardware security, Technology, Chemical technology, TP1-1185, Biotechnology, TP248.13-248.65, Science, Physics, QC1-999

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/2196-5404

Zugangs-URL: https://doaj.org/article/5413daaeac9647c69c932378e530adf0

TensorCIM: Digital Computing-in-Memory Tensor Processor With Multichip-Module-Based Architecture for Beyond-NN Acceleration

Autoren: Yiqi Wang Zihan Wu Weiwei Wu et al.

Quelle: IEEE Journal of Solid-State Circuits. 60:734-747

Schlagwörter: In-memory computing, Floating-point, Artificial neural networks, Multichip-module (MCM), Graph neural network (NN), Tensors, Random access memory, Vectors, Recommendation system, Common Information Model (computing), Computing-in-memory (CIM), Computer architecture, Sparsity

Tools and techniques for real-time data processing: A review

Autoren: Rani, Sangeeta

Quelle: International Journal of Science and Research Archive. 14:1872-1881

Schlagwörter: Stream processing, Complex event processing, In-memory computing, Real-time data processing, Micro-batching, Windowing

Investigating Self-Heating Effects in Ferroelectric FinFETs for Reliable In-Memory Computing

Autoren: Swati Deshwal Shubham Kumar Swetaki Chatterjee et al.

Quelle: IEEE Journal of the Electron Devices Society, Vol 13, Pp 838-844 (2025)

Schlagwörter: Ferroelectric FinFET, Hyperdimensional Computing, Electrical engineering. Electronics. Nuclear engineering, Self-Heating Effect, Variations, In-Memory Computing, TK1-9971

Zugangs-URL: https://doaj.org/article/3e1ea960db4d4ae398839fd060018442

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

Autoren: Alessio Antolini Francesco Zavalloni Andrea Lico et al.

Weitere Verfasser: Alessio Antolini Francesco Zavalloni Andrea Lico et al.

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

Schlagwörter: 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)

Dateibeschreibung: application/pdf

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

Analysis of Low Area Digital Up/Down Clipping Counter for Digital In-Memory Computing

Autoren: Siyeol Lee Geonwoo Lee Seongmin Ahn et al.

Quelle: IEEE Access, Vol 13, Pp 32808-32818 (2025)

Schlagwörter: full adder, in-memory computing, deep learning, Electrical engineering. Electronics. Nuclear engineering, Area efficient, D flip-flop, digital up/down counter, TK1-9971

Zugangs-URL: https://doaj.org/article/77f88fc163b04b82a7d50ab44d5dc6c6

ArXrCiM: Architectural Exploration of Application-Specific Resonant SRAM Compute-in-Memory

Autoren: Dhandeep Challagundla Ignatius Bezzam Riadul Islam

Quelle: IEEE Transactions on Very Large Scale Integration (VLSI) Systems. 33:179-192

Schlagwörter: Optimization, In-memory computing, Compute-in-memory (CiM), UMBC Cybersecurity Institute, memory bottleneck, Logic, resonant energy-recycling, static random-access memory (SRAM), Random access memory, Energy efficiency, Discharges (electric), Inductors, Recycling, Computer architecture, logic synthesis, Microprocessors

Comprehensive Review on the Exploitation of Advanced Memory Optimization Strategies to Improve Performance for Convolutional and Spiking Neural Networks in Medical Imaging Using Hardware Accelerators

Autoren: N. Srikanth Prasad S. Sundar

Quelle: IEEE Access, Vol 13, Pp 62449-62461 (2025)

Schlagwörter: Memory optimization, in-memory computing, medical imaging, Electrical engineering. Electronics. Nuclear engineering, neural networks, hardware accelerators, FPGA, TK1-9971

Zugangs-URL: https://doaj.org/article/04b259fca2ab455584a73bdfb496e826

Physics-Based SPICE-Compatible Compact Model of FLASH Memory With Poly-Si Channel for Computing-in-Memory Applications

Autoren: Jung Rae Cho Donghyun Ryu Donguk Kim et al.

Quelle: IEEE Journal of the Electron Devices Society, Vol 13, Pp 1-7 (2025)

Schlagwörter: in-memory computing, SPICE modeling, Electrical engineering. Electronics. Nuclear engineering, FLASH, TK1-9971

Zugangs-URL: https://doaj.org/article/84b9e31d29264ed8bef631101160da46

Development of In-Memory Computing Device Using Positive Feedback Field Effect Transistor Based on NAND Flash Array

Autoren: Hangwook Jeong Minseon Park Min-Woo Kwon

Quelle: IEEE Access, Vol 13, Pp 45449-45457 (2025)

Schlagwörter: in-memory computing, Feedback field effect transistor, NAND flash, hot carrier injection, Electrical engineering. Electronics. Nuclear engineering, Boolean logical operation, TK1-9971

Zugangs-URL: https://doaj.org/article/53200e6d55e64956a9c4b5ad1ce276b5

Cryogenic Hyperdimensional In-Memory Computing Using Ferroelectric TCAM

Autoren: Shivendra Singh Parihar Shubham Kumar Swetaki Chatterjee et al.

Quelle: IEEE Journal on Exploratory Solid-State Computational Devices and Circuits, Vol 11, Pp 34-41 (2025)

Schlagwörter: TK7885-7895, cryogenic complementary metal oxide semiconductor (CMOS), Computer engineering. Computer hardware, 5-nm fin field-effect transistor (FinFET), in-memory computing (IMC), compact modeling, ferroelectric fin field-effect transistor (FeFinFET), hyperdimensional computing (HDC)

Zugangs-URL: https://doaj.org/article/15af6cc579ac455fb31a87f7fab9e3b2

A Non-Linear Partial Differential Equation Solver Based on Analog Memristor Crossbar Arrays

Autoren: Jiabao Ye Bing Chen Nuo Xu et al.

Quelle: IEEE Journal of the Electron Devices Society, Vol 13, Pp 477-484 (2025)

Schlagwörter: In-memory computing, non-linear partial differential equation (PDE), Electrical engineering. Electronics. Nuclear engineering, crossbar, memristor, TK1-9971

Zugangs-URL: https://doaj.org/article/d7141aaca7934ef0aaefc182d4a50948