tag: RRAM

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

Verification and Reliability Methods For RRAM-Based Computing-in-Memory (Univ. of Bremen et al)
By Technical Paper Link - 05 Dec, 2025 - Comments: 0

A new technical paper titled "Special Session Paper: Formal Verification Techniques and Reliability Methods for RRAM-based Computing-in-Memory" was published by researchers at University of Bremen, DFKI GmbH, University of Florida and TU Munich. Abstract "Computing-in-memory (CIM) has gained immense traction owing to the benefits it provides in power, performance, and area. CIM can be don... » read more

Digital Memristor-Based PIM From A Device And Reliability View (Northwestern, Technion)
By Technical Paper Link - 25 Nov, 2025 - Comments: 0

A new technical paper titled "A Comparative Study of Digital Memristor-Based Processing-In-Memory from a Device and Reliability Perspective" was published by researchers at Northwestern University and  Technion – Israel Institute of Technology. Abstract "As data-intensive applications increasingly strain conventional computing systems, processing-in-memory (PIM) has emerged as a promis... » read more

Emerging Synaptic Memory Technologies For Neuromorphic CIM Platforms (Tampere Univ.)
By Technical Paper Link - 21 Nov, 2025 - Comments: 0

A new technical paper titled "Toward Capacitive In-Memory-Computing: A Device to Systems Level Perspective on the Future of Artificial Intelligence Hardware" was published by researchers at Tampere University. Abstract: "The quest for energy-efficient, scalable neuromorphic computing has elevated compute-in-memory (CIM) architectures to the forefront of hardware innovation. While memristive... » 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

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

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