Research Bits: April 8

Annealing processor Researchers from the Tokyo University of Science designed a scalable, fully-coupled annealing processor with 4096 spins on a single board with 36 CMOS chips, with parallelized capabilities for accelerated solving of combinatorial optimization problems. "We want to achieve advanced information processing directly at the edge, rather than in the cloud, or performing prepro... » read more

Research Bits: Feb. 13

Fast phase-change memory Researchers from Stanford University, TSMC, National Institute of Standards and Technology (NIST), and University of Maryland developed a new phase-change memory for future AI and data-centric systems. It is based on GST467, an alloy of four parts germanium, six parts antimony, and seven parts tellurium, which is sandwiched between several other nanometer-thin material... » read more

A New Phase-Change Memory For Processing Large Amounts Of Data 

A technical paper titled “Novel nanocomposite-superlattices for low energy and high stability nanoscale phase-change memory” was published by researchers at Stanford University, TSMC, NIST, University of Maryland, Theiss Research and Tianjin University. Abstract: "Data-centric applications are pushing the limits of energy-efficiency in today’s computing systems, including those based on... » read more

3D Integration Supports CIM Versatility And Accuracy

Compute-in-memory (CIM) is gaining attention due to its efficiency in limiting the movement of massive volumes of data, but it's not perfect. CIM modules can help reduce the cost of computation for AI workloads, and they can learn from the highly efficient approaches taken by biological brains. When it comes to versatility, scalability, and accuracy, however, significant tradeoffs are requir... » read more

Analog In-Memory Cores With Multi-Memristive Unit-Cells (IBM)

A technical paper titled “Exploiting the State Dependency of Conductance Variations in Memristive Devices for Accurate In-Memory Computing” was published by researchers at IBM Research-Europe, IBM Research-Albany, and IBM Research-Yorktown Heights. Abstract: "Analog in-memory computing (AIMC) using memristive devices is considered a promising Non-von Neumann approach for deep learning (DL... » read more

Research Bits: September 26

2D waveguides Researchers from the University of Chicago found that a sheet of glass crystal just a few atoms thick could trap and carry light efficiently up to a centimeter. In tests, the researchers found they could use extremely tiny prisms, lenses, and switches to guide the path of the light along a chip. “We were utterly surprised by how powerful this super-thin crystal is; not on... » read more

Optimizing Projected PCM for Analog Computing-In-Memory Inferencing (IBM)

A new technical paper titled "Optimization of Projected Phase Change Memory for Analog In-Memory Computing Inference" was published by researchers at IBM Research. "A systematic study of the electrical properties-including resistance values, memory window, resistance drift, read noise, and their impact on the accuracy of large neural networks of various types and with tens of millions of wei... » read more

Neuromorphic Computing: Challenges, Opportunities Including Materials, Algorithms, Devices & Ethics

This new research paper titled "2022 roadmap on neuromorphic computing and engineering" is from numerous researchers at Technical University of Denmark, Instituto de Microelectrónica de Sevilla, CSIC, University of Seville, and many others. Partial Abstract: "The aim of this roadmap is to present a snapshot of the present state of neuromorphic technology and provide an opinion on the chall... » read more

Neurosynaptic Device That Mimics Synaptic and Intrinsic Plasticity Concomitantly In a Single cell

New academic paper titled "Simultaneous emulation of synaptic and intrinsic plasticity using a memristive synapse" from researchers at Korea Advanced Institute of Science and Technology (KAIST). Abstract Neuromorphic computing targets the hardware embodiment of neural network, and device implementation of individual neuron and synapse has attracted considerable attention. The emulation of... » read more

An Energy-Efficient DRAM Cache Architecture for Mobile Platforms With PCM-Based Main Memory

Abstract "A long battery life is a first-class design objective for mobile devices, and main memory accounts for a major portion of total energy consumption. Moreover, the energy consumption from memory is expected to increase further with ever-growing demands for bandwidth and capacity. A hybrid memory system with both DRAM and PCM can be an attractive solution to provide additional capacity ... » read more

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