MEMprop: Gradient-based Learning To Train Fully Memristive SNNs


New technical paper titled "Gradient-based Neuromorphic Learning on Dynamical RRAM Arrays" from IEEE researchers. Abstract "We present MEMprop, the adoption of gradient-based learning to train fully memristive spiking neural networks (MSNNs). Our approach harnesses intrinsic device dynamics to trigger naturally arising voltage spikes. These spikes emitted by memristive dynamics are anal... » read more

HBM-based scalable multi-FPGA emulator for Quantum Fourier Transform (QFT)


New technical paper titled "A Scalable Emulator for Quantum Fourier Transform Using Multiple-FPGAs With High-Bandwidth-Memory" from researchers at Tohoku University in Japan. Abstract: "Quantum computing is regarded as the future of computing that hopefully provides exponentially large processing power compared to the conventional digital computing. However, current quantum computers do not... » read more

End to End System Design for DRAM-based TRNG


Research paper titled "DR-STRaNGe: End-to-End System Design for DRAM-based True Random Number Generators" is presented from researchers at TOBB University of Economics and Technology and ETH Zurich. Abstract "Random number generation is an important task in a wide variety of critical applications including cryptographic algorithms, scientific simulations, and industrial testing tools. True ... » read more

End-to-End System for Object Localization By Coupling pMUTs to a Neuromorphic RRAM-based Computational Map


New research paper titled "Neuromorphic object localization using resistive memories and ultrasonic transducers" from researchers at CEA, LETI, Université Grenoble Alpes and others. Abstract "Real-world sensory-processing applications require compact, low-latency, and low-power computing systems. Enabled by their in-memory event-driven computing abilities, hybrid memristive-Complementary... » read more

ETH Zurich: PIM (Processing In Memory) Architecture, UPMEM & PrIM Benchmarks


New paper technical titled "Benchmarking a New Paradigm: An Experimental Analysis of a Real Processing-in-Memory Architecture" led by researchers at ETH Zurich. Researchers provide a comprehensive analysis of the first publicly-available real-world PIM architecture, UPMEM, and introduce PrIM (Processing-In-Memory benchmarks), a benchmark suite of 16 workloads from different application domai... » read more

Simulation Framework to Evaluate the Feasibility of Large-scale DNNs based on CIM Architecture & Analog NVM


Technical paper titled "Accuracy and Resiliency of Analog Compute-in-Memory Inference Engines" from researchers at UCLA. Abstract "Recently, analog compute-in-memory (CIM) architectures based on emerging analog non-volatile memory (NVM) technologies have been explored for deep neural networks (DNNs) to improve scalability, speed, and energy efficiency. Such architectures, however, leverage ... » read more

Effect of Different Frequency Scaling Levels on Memory in Regard to Total Power Consumption in Mobile MPSoC


New technical paper titled "CPU-GPU-Memory DVFS for Power-Efficient MPSoC in Mobile Cyber Physical Systems" from researchers at University of Essex, Nosh Technologies, and University of Southampton. Abstract "Most modern mobile cyber-physical systems such as smartphones come equipped with multi-processor systems-on-chip (MPSoCs) with variant computing capacity both to cater to performance r... » read more

Scalable Approach to Fabricate Memristor Arrays at Wafer-scale


New technical paper titled "Wafer-scale solution-processed 2D material analog resistive memory array for memory-based computing" from researchers at National University of Singapore and Institute of High Performance Computing, Singapore. Abstract "Realization of high-density and reliable resistive random access memories based on two-dimensional semiconductors is crucial toward their develop... » read more

Novel Spintronic Neuro-mimetic Device Emulating the LIF Neuron Dynamics w/High Energy Efficiency & Compact Footprints


New technical paper titled "Noise resilient leaky integrate-and-fire neurons based on multi-domain spintronic devices" from researchers at Purdue University. Abstract "The capability of emulating neural functionalities efficiently in hardware is crucial for building neuromorphic computing systems. While various types of neuro-mimetic devices have been investigated, it remains challenging to... » read more

Differentiable Analog Nonvolatile CAM (dCAM) Using Memristors


Technical paper titled "Differentiable Content Addressable Memory with Memristors" from researchers at Hewlett Packard Labs and University of Hong Kong. Abstract "Memristors, Flash, and related nonvolatile analog device technologies offer in-memory computing structures operating in the analog domain, such as accelerating linear matrix operations in array structures. These take advantage of ... » read more

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