Ultra high-speed electronics for power system dynamic emulation

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The increasing complexity of transformer models in artificial intelligence expands their computational costs, memory usage, and energy consumption. Hardware acceleration tackles the ensuing challenges by designing processors and accelerators tailored for t ...

Much attention has been paid to dynamical simulation and quantum machine learning (QML) independently as applications for quantum advantage, while the possibility of using QML to enhance dynamical simulations has not been thoroughly investigated. Here we d ...

Dehydration is a frequent condition in the elderly and can lead to serious health complications if not compensated timely. Early diagnosis can be problematic, as medical examinations in the hospital would be needed. Fully wearable low-cost multisensing dev ...

This paper proposes a generic and unified model of the power flow (PF) problem for multiterminal hybrid AC/DC networks. The proposed model is an extension of the standard AC-PF. The DC network is treated as an AC one and, in addition to the Slack, PV and P ...

Embedded memories occupy an increasingly dominant part of the area and power budgets of modern systems-on-chips (SoCs). Multi-ported embedded memories, commonly used by media SoCs and graphical processing units, occupy even more area and consume higher pow ...

The global imperative to transition from fossil fuel-based energy sources to renewable alternatives has become increasingly urgent in the pursuit of sustainable and renewable power generation. This paradigm shift necessitates innovative approaches to manag ...

Smarty is a fully-reconfigurable on-chip feed-forward artificial neural network (ANN) with ten integrated time-to-digital converters (TDCs) designed in a 16 nm FinFET CMOS technology node. The integration of TDCs together with an ANN aims to reduce system ...

The goal of this work is to use anisotropic adaptive finite elements for the numerical simulation of aluminium electrolysis. The anisotropic adaptive criteria are based on a posteriori error estimates derived for simplified problems. First, we consider an ...

Machine learning algorithms such as Convolutional Neural Networks (CNNs) are characterized by high robustness towards quantization, supporting small-bitwidth fixed-point arithmetic at inference time with little to no degradation in accuracy. In turn, small ...

Numerical simulations have become one of the key tools used by theorists in all the fields of astrophysics and cosmology. The development of modern tools that target the largest existing computing systems and exploit state-of-the-art numerical methods and ...

The desire and ability to place AI-enabled applications on the edge has grown significantly in recent years. However, the compute-, area-, and power-constrained nature of edge devices are stressed by the needs of the AI-enabled applications, due to a gener ...

Accurate forecasting of photovoltaic (PV) power production is crucial for the integration of more renewable energy sources into the power grid. PV power production is highly intermittent, due to the stochastic cloud behaviour and cloud dynamics. Previous w ...

With the growth in the performance of general-purpose computing no longer following Moore's law and Dennard scaling, the use of hardware-specialized systems is common practice. Field-programmable gate arrays (FPGAs) are adopted in cloud and cyber-physical ...

In the past decades, a significant increase of the transistor density on a chip has led to exponential growth in computational power driven by Moore's law. To overcome the bottleneck of traditional von-Neumann architecture in computational efficiency, effo ...

Ultra high-speed electronics for power system dynamic emulation

Chattez avec Graph Search

Accelerator-driven Data Arrangement to Minimize Transformers Run-time on Multi-core Architectures

Dynamical simulation via quantum machine learning with provable generalization

Design and in vitro Characterization of a Wearable Multisensing System for Hydration Monitoring

General and Unified Model of the Power Flow Problem in Multiterminal AC/DC Networks

Multi-Ported GC-eDRAM Bitcell with Dynamic Port Configuration and Refresh Mechanism

Study of flexible operating conditions in variable-speed hydraulic turbines : advanced models and experimental validation

On-Chip Fully Reconfigurable Artificial Neural Network in 16 nm FinFET for Positron Emission Tomography

Adaptive Finite Elements with Large Aspect Ratio. Application to Aluminium Electrolysis

DBFS: Dynamic Bitwidth-Frequency Scaling for Efficient Software-defined SIMD

Swift : a modern highly parallel gravity and smoothed particle hydrodynamics solver for astrophysical and cosmological applications

Exploring High-Performance and Energy-Efficient Architectures for Edge AI-Enabled Applications

Network time series forecasting in photovoltaics power production

Electrical-Level Fault-Injection Attacks on FPGA-Based Systems

Towards Scalable Electronics: Synthetic 2D Materials for Large-Area 2D Circuit Integration