相关论文: The SNS Run Permit System

This paper presents a spiking neural network (SNN) accelerator made using fully open-source EDA tools, process design kit (PDK), and memory macros synthesized using OpenRAM. The chip is taped out in the 130 nm SkyWater process and…

Neuromorphic, or spiking, processors are increasingly being considered for use in harsh, radiation-prone environments such as space and avionics, where energy efficiency and graceful degradation are essential. In this study, we propose and…

Science Data Systems (SDS) handle science data from acquisition through processing to distribution. They are deployed in the Cloud today, and the efficiency of Cloud instance utilization is critical to success. Conventional SDS are unable…

Spiking Neural Network (SNN) is the third generation of Neural Network (NN) mimicking the natural behavior of the brain. By processing based on binary input/output, SNNs offer lower complexity, higher density and lower power consumption.…

We propose an innovative design for an optical Echo State Network (ESN), an advanced type of reservoir computer known for its universal computational capabilities. Our design enables an optical implementation of arbitrary ESNs, featuring…

Reconfigurable intelligent surface (RIS)-assisted transmission and space shift keying (SSK) appear as promising candidates for future energy-efficient wireless systems. In this paper, two RIS-based SSK schemes are proposed to efficiently…

Spiking Neural Networks (SNNs) have shown capabilities of achieving high accuracy under unsupervised settings and low operational power/energy due to their bio-plausible computations. Previous studies identified that DRAM-based off-chip…

We present a scheme of surface-sensitive nuclear magnetic resonance in optically pumped semiconductors, where an NMR signal from a part of the surface of a bulk compound semiconductor is detected apart from the bulk signal. It utilizes…

Spiking Neural Networks (SNNs) hold promise for energy-efficient, biologically inspired computing. We identify substantial informatio loss during spike transmission, linked to temporal dependencies in traditional Leaky Integrate-and-Fire…

We discuss a high-performance and high-throughput hardware accelerator for probabilistic Spiking Neural Networks (SNNs) based on Generalized Linear Model (GLM) neurons, that uses binary STT-RAM devices as synapses and digital CMOS logic for…

The human brain comprises about a hundred billion neurons connected through quadrillion synapses. Spiking Neural Networks (SNNs) take inspiration from the brain to model complex cognitive and learning tasks. Neuromorphic engineering…

The COHERENT experiment measures neutrino-induced recoils from coherent elastic neutrino-nucleus scattering (CEvNS) with multiple nuclear targets at the Spallation Neutron Source (SNS) at the Oak Ridge National Laboratory (ORNL), USA.…

Energy efficiency and low latency are crucial requirements for designing wearable AI-empowered human activity recognition systems, due to the hard constraints of battery operations and closed-loop feedback. While neural network models have…

The design, construction and testing of neutrino detector prototypes at CERN are ongoing activities. This document reports on the design of solid state baby MIND and TASD detector prototypes and outlines requirements for a test beam at CERN…

To maximize the performance and energy efficiency of Spiking Neural Network (SNN) processing on resource-constrained embedded systems, specialized hardware accelerators/chips are employed. However, these SNN chips may suffer from permanent…

This paper considers an intelligent reflecting surface (IRS) assisted multi-input multi-output (MIMO) power splitting (PS) based simultaneous wireless information and power transfer (SWIPT) system with multiple PS receivers (PSRs). The…

Cyber Physical Systems (CPS) are the conjoining of an entities' physical and computational elements. The development of a typical CPS system follows a sequence from conceptual modeling, testing in simulated (virtual) worlds, testing in…

The event streams generated by dynamic vision sensors (DVS) are sparse and non-uniform in the spatial domain, while still dense and redundant in the temporal domain. Although spiking neural network (SNN), the event-driven neuromorphic…

Surface-enhanced Raman spectroscopy (SERS) is a sensitive vibrational spectroscopy technique that can enable fast and non-destructive detection of trace molecules. SERS substrates are critical for the advancement of the SERS application. By…

Injected beam energy and energy spread are critical parameters affecting the performance of our rapid cycling synchrotron (RCS). A real-time energy monitoring system is being installed to examine the H- beam out of the Intense Pulsed…