Publicaties
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Automotive computing, neuromorphic computing, and beyond Universiteit Gent
Design of Many-Core Big Little mu Brains for Energy-Efficient Embedded Neuromorphic Computing Interuniversitair Micro-Electronica Centrum vzw
As spiking-based deep learning inference applications are increasing in embedded systems, these systems tend to integrate neuromorphic accelerators such as mu Brain to improve energy efficiency. We propose a mu Brain-based scalable many-core neuromorphic hardware design to accelerate the computations of spiking deep convolutional neural networks (SDCNNs). To increase energy efficiency, cores are designed to be heterogeneous in terms of their ...
Spin-orbit torque MRAM for ultrafast cache and neuromorphic computing applications Interuniversitair Micro-Electronica Centrum vzw
Spin-orbit torque (SOT) magnetic random-access memory (MRAM) is a 3-terminal non-volatile memory technology promising high speed up to multi-GHz, high endurance and non-volatility. Here we show how SOT-MRAM stack can be optimized to reach performance towards an embedded last level cache memory replacing SRAM. Moreover, we show how the stack and device geometry can be optimized to increase density and how the stack properties can be optimized to ...
Photonic neuromorphic information processing and reservoir computing Universiteit Gent
Photonic neuromorphic computing is attracting tremendous research interest now, catalyzed in no small part by the rise of deep learning in many applications. In this paper, we will review some of the exciting work that has been going in this area and then focus on one particular technology, namely, photonic reservoir computing.
Behavioral modeling of integrated phase-change photonic devices for neuromorphic computing applications Universiteit Gent
The combination of phase-change materials and integrated photonics has led to the development of new forms of all-optical devices, including photonic memories, arithmetic and logic processors, and synaptic and neuronal mimics. Such devices can be readily fabricated into photonic integrated circuits, so potentially delivering large-scale all-optical arithmetic-logic units and neuromorphic processing chips. To facilitate in the design and ...
Neuromorphic computing with signal-mixing cavities Universiteit Gent
A FeFET with a novel MFMFIS gate stack: towards energy-efficient and ultrafast NVMs for neuromorphic computing KU Leuven
The discovery of ferroelectricity in the fluorite structure based hafnium oxide (HfO2) material sparked major efforts for reviving the ferroelectric field effect transistor (FeFET) memory concept. A Novel metal-ferroelectric-metal-ferroelectric-insulator-semiconductor (MFMFIS) FeFET memory is reported based on dual ferroelectric integration as an MFM and MFIS in a single gate stack using Si-doped Hafnium oxide (HSO) ferroelectric (FE) material. ...