tag: Neuromorphic

Neuromorphic chip integrated with a large-scale integration circuit and amorphous-metal-oxide semiconductor thin-film synapse devices
By Technical Paper Link - 01 Apr, 2022 - Comments: 0

New academic paper from Nara Institute of Science and Technology (NAIST) and Ryukoku University. Abstract "Artificial intelligences are promising in future societies, and neural networks are typical technologies with the advantages such as self-organization, self-learning, parallel distributed computing, and fault tolerance, but their size and power consumption are large. Neuromorphic syste... » read more

Comprehensive Model of Electron Conduction in Oxide-Based Memristive Devices
By Technical Paper Link - 03 Feb, 2022 - Comments: 0

Abstract "Memristive devices are two-terminal devices that can change their resistance state upon application of appropriate voltage stimuli. The resistance can be tuned over a wide resistance range enabling applications such as multibit data storage or analog computing-in-memory concepts. One of the most promising classes of memristive devices is based on the valence change mechanism in oxide... » read more

Weight Adjustable Photonic Synapse by Nonlinear Gain in a Vertical Cavity Semiconductor Optical Amplifier
By Technical Paper Link - 21 Dec, 2021 - Comments: 0

Abstract: "In this paper, we report a high-speed and tunable photonic synaptic element based on a vertical cavity semiconductor optical amplifier (VCSOA) operating with short (150 ps-long) and low-energy (μW peak power) light pulses. By exploiting nonlinear gain properties of VCSOAs when subject to external optical injection, our system permits full weight tunability of sub-ns input light p... » read more

Considerations for Neuromorphic Supercomputing in Semiconducting and Superconducting Optoelectronic Hardware
By Technical Paper Link - 18 Nov, 2021 - Comments: 0

Abstract: "Any large-scale spiking neuromorphic system striving for complexity at the level of the human brain and beyond will need to be co-optimized for communication and computation. Such reasoning leads to the proposal for optoelectronic neuromorphic platforms that leverage the complementary properties of optics and electronics. Starting from the conjecture that future large-scale neurom... » read more

Manufacturing Bits: April 27
By Mark LaPedus - 27 Apr, 2021 - Comments: 0

Next-gen neuromorphic computing The European Union (EU) has launched a new project to develop next-generation devices for neuromorphic computing systems. The project, called MeM-Scales, plans to develop a novel class of algorithms, devices, and circuits that reproduce multi-timescale processing of biological neural systems. The results will be used to build neuromorphic computing systems th... » read more

Power/Performance Bits: Jan. 26
By Jesse Allen - 26 Jan, 2021 - Comments: 0

Neural networks on MCUs Researchers at MIT are working to bring neural networks to Internet of Things devices. The team's MCUNet is a system that designs compact neural networks for deep learning on microcontrollers with limited memory and processing power. MCUNet is made up of two components. One is TinyEngine, an inference engine that directs resource management. TinyEngine is optimized t... » read more

Engineering Within Constraints
By Brian Bailey - 30 Jul, 2020 - Comments: 0

One of the themes of DAC this year was the next phase of machine learning. It is as if CNNs and RNNs officially have migrated from the research community and all that is left now is optimization. The academics need something new. Quite correctly, they have identified power as the biggest problem associated with learning and inferencing today, and a large part of that problem is associated with ... » read more

Spiking Neural Networks Place Data In Time
By Katherine Derbyshire - 16 Jul, 2020 - Comments: 0

Artificial neural networks have found a variety of commercial applications, from facial recognition to recommendation engines. Compute-in-memory accelerators seek to improve the computational efficiency of these networks by helping to overcome the von Neumann bottleneck. But the success of artificial neural networks also highlights their inadequacies. They replicate only a small subset of th... » read more

Going On the Edge
By Mark LaPedus - 27 Jan, 2020 - Comments: 3

Emmanuel Sabonnadière, chief executive of Leti, sat down with Semiconductor Engineering to talk about artificial intelligence (AI), edge computing and chip technologies. What follows are excerpts of that conversation. SE: Where is AI going in the future? Sabonnadière: I am a strong believer that edge AI will change our lives. Today’s microelectronics are organized with 80% of things i... » read more

Manufacturing Bits: March 29
By Mark LaPedus - 29 Mar, 2016 - Comments: 0

Brain-inspired computing Lawrence Livermore National Laboratory (LLNL) has purchased a brain-inspired supercomputing platform for deep learning developed by IBM Research. Based on a neurosynaptic computer chip called IBM TrueNorth, the scalable platform will process the equivalent of 16 million neurons and 4 billion synapses. It will consume the energy equivalent of a tablet computer. ... » read more

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