tag: ReRAM

Optimizing In-Memory AI Accelerators Across Multiple Workloads (KAUST, Compumacy)
By Technical Paper Link - 06 Mar, 2026 - Comments: 0

Researchers from KAUST and Compumacy for Artificial Intelligence Solutions have released “Joint Hardware-Workload Co-Optimization for In-Memory Computing Accelerators”. Abstract “Software-hardware co-design is essential for optimizing in-memory computing (IMC) hardware accelerators for neural networks. However, most existing optimization frameworks target a single workload, lea... » read more

ReRAM-based Neo-Hebbian Synapses For Training Neuromorphic HW (IIT Madras, UCSB)
By Technical Paper Link - 23 Feb, 2026 - Comments: 0

A new technical paper, "NeoHebbian synapses to accelerate online training of neuromorphic hardware," was published by researchers at IIT Madras and UC Santa Barbara. Abstract "Neuromorphic systems that employ advanced synaptic learning rules, such as the three-factor learning rule, require synaptic devices of increased complexity. Herein, a novel neoHebbian artificial synapse utilizing ReRA... » read more

Why In-Memory Computation Is So Important For Edge AI
By Katherine Derbyshire - 23 Oct, 2025 - Comments: 1

In popular media, “AI” usually means large language models running in expensive, power-hungry data centers. For many applications, though, smaller models running on local hardware are a much better fit. Autonomous vehicles need to respond in real-time, without data transmission delays. Medical and industrial applications often depend on sensitive data that cannot be shared with third par... » read more

KAN Acceleration: Algorithm Hardware Co-Design Approach (Georgia Tech, National Tsing Hua Univ., TSMC)
By Technical Paper Link - 16 Sep, 2025 - Comments: 0

A new technical paper titled "Hardware Acceleration of Kolmogorov-Arnold Network (KAN) in Large-Scale Systems" was published by researchers at Georgia Institute of Technology, National Tsing Hua University and TSMC. Abstract "Recent developments have introduced Kolmogorov-Arnold Networks (KAN), an innovative architectural paradigm capable of replicating conventional deep neural network (DNN... » read more

RRAM: Transforming Memory Solutions For AI-driven IoT Devices And Embedded Systems
By Infineon - 07 Aug, 2025 - Comments: 0

Artificial Intelligence (AI) and Machine Learning (ML) applications are driving increased demand for high-performance, low-power memory solutions across consumer, medical, and industrial markets. These applications require efficient, Non-Volatile Memory (NVM) to process, store, and retain large volumes of data, as well as support frequent Firmware Over-The-Air (FOTA) updates. In the consumer... » read more

Emerging NVM: Review Of Emerging Memory Materials And Device Architectures
By Technical Paper Link - 08 Jul, 2025 - Comments: 0

A new technical paper titled "Emerging Nonvolatile Memory Technologies in the Future of Microelectronics" was published by researchers at Texas A&M University, University of Massachusetts and USC. Abstract "Memory technologies are central to modern computing systems, performing essential functions that range from primary data storage to advanced tasks, such as in-memory computing for ... » read more

All-In-One Analog AI Accelerator With CMO/HfOx ReRAM Integrated Into The BEOL (IBM Research-Europe)
By Technical Paper Link - 18 Jun, 2025 - Comments: 0

A new technical paper titled "All-in-One Analog AI Hardware: On-Chip Training and Inference with Conductive-Metal-Oxide/HfOx ReRAM Devices" was published by researchers at IBM Research-Europe. Abstract "Analog in-memory computing is an emerging paradigm designed to efficiently accelerate deep neural network workloads. Recent advancements have focused on either inference or training accelera... » read more

Main Applications And Corresponding Requirements For IMC With RRAM Devices
By Technical Paper Link - 06 May, 2025 - Comments: 0

A new technical paper titled "Resistive Switching Random-Access Memory (RRAM): Applications and Requirements for Memory and Computing" was published by researchers at Politecnico di Milano, IUNET and Hewlett-Packard Labs. Abstract "In the information age, novel hardware solutions are urgently needed to efficiently store and process increasing amounts of data. In this scenario, memory device... » read more

ReRAM-Based, In-Memory Implementation Of Stochastic Computing
By Technical Paper Link - 14 Apr, 2025 - Comments: 0

A new technical paper titled "All-in-Memory Stochastic Computing using ReRAM" was published by researchers at TU Dresden, Center for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI), Case Western Reserve University, University of Louisiana at Lafayette and Barkhausen Institut. Abstract "As the demand for efficient, low-power computing in embedded and edge devices grows, tradit... » read more

HW Implementation Of An ONN Coupled By A ReRAM Crossbar Array (IBM, TU Eindhoven)
By Technical Paper Link - 25 Mar, 2025 - Comments: 0

A new technical paper titled "Hardware Implementation of Ring Oscillator Networks Coupled by BEOL Integrated ReRAM for Associative Memory Tasks" was published by researchers at IBM Research Europe and Eindhoven University of Technology. Abstract "We demonstrate the first hardware implementation of an oscillatory neural network (ONN) utilizing resistive memory (ReRAM) for coupling elements. ... » read more

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