Moving Intelligence Closer to the Sensor Edge (IBM Research)


A researcher from IBM Research - Europe published “Emerging Trends in Intelligent Sensing”. Abstract “The rapid proliferation of artificial intelligence, connected devices, and high speed mobile networks is driving unprecedented computational demands that challenge traditional sensor architectures. This article explores the shift toward edge computing, where computation is perfor... » read more

Nanoscale MoS₂-based Memristors Integrated into CMOS Microchips


A new technical paper, "Integration of Low-Voltage Nanoscale MoS2 Memristors on CMOS Microchips" was published by RWTH Aachen and Forschungszentrum Jülich GmbH. Abstract "2D materials (2DMs) are gaining increased attention for applications such as advanced electronics and neuromorphic computing due to their excellent electrical properties. Among these 2DMs, molybdenum disulfide (MoS2) ha... » read more

Comprehensive Performance Bound and Bottleneck Analysis Of Neuromorphic Accelerators (Harvard, Politecnico di Torino, Intel et al.)


A new technical paper titled "Modeling and Optimizing Performance Bottlenecks for Neuromorphic Accelerators" was published by researchers at Harvard University, Politecnico di Torino, Intel, LMU Munich, Accenture Labs, BootLoop AI, TU Delft and Wordly. Abstract "Neuromorphic accelerators offer promising platforms for machine learning (ML) inference by leveraging event-driven, spatially-expa... » read more

Research Bits: Oct. 13


Mimicking neural plasticity Researchers from Korea Advanced Institute of Science and Technology (KAIST) developed a frequency switching neuristor device that mimics the intrinsic plasticity of neurons. The device can autonomously adjust the frequency of its signals, similar to the way the brain becomes less startled by repeated stimuli or becomes increasingly sensitive through training. The... » read more

Research Bits: Sept. 23


Opto-electrical excitation of MTJs Researchers at the University of Greifswald, International Iberian Nanotechnology Laboratory, Max Planck Institute for the Science of Light, and Aarhus University advanced the use of magnetic tunnel junctions (MTJs) for neuromorphic computing. The team developed a hybrid opto-electrical excitation scheme that combines electrical currents with short laser p... » read more

Research Bits: July 29


Sort-in-memory Researchers from Peking University and the Chinese Institute for Brain Research developed a sort-in-memory hardware system based on memristors that is tailored for complex, nonlinear sorting tasks. The comparator-free processing-in-memory architecture is built on a one-transistor–one-resistor (1T1R) memristor array, using a Digit Read mechanism that replaces traditional com... » read more

Emerging NVM: Review Of Emerging Memory Materials And Device Architectures


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

Main Applications And Corresponding Requirements For IMC With RRAM Devices


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

Research Bits: Apr. 1


Neuro-synaptic RAM Researchers from the National University of Singapore (NUS) and King Abdullah University of Science and Technology (KAUST) found that a standard silicon transistor can function like a biological neuron and synapse when arranged and operated in a specific way. The team was able to replicate both neural firing and synaptic weight changes by adjusting the resistance of the b... » read more

Research Bits: Jan. 20


Self-correcting memristor array Researchers at Korea Advanced Institute of Science and Technology (KAIST), Seoul National University, Sungkyunkwan University, Electronics and Telecommunications Research Institute (ETRI), and Yonsei University developed a memristor-based neuromorphic chip that can learn and correct errors, enabling it to adapt to immediate environmental changes. The system c... » read more

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