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A challenging part of dynamic probabilistic risk assessment for nuclear power plants is the need for large amounts of temporal simulations given various initiating events and branching conditions from which representative feature extraction…

Machine Learning · Computer Science 2021-04-20 Bing Zha , Alessandro Vanni , Yassin Hassan , Tunc Aldemir , Alper Yilmaz

Motivation: Read mapping is a computationally expensive process and a major bottleneck in genomics analyses. The performance of read mapping is mainly limited by the performance of three key computational steps: Index Querying, Seed…

Hardware Architecture · Computer Science 2023-10-02 Julien Eudine , Mohammed Alser , Gagandeep Singh , Can Alkan , Onur Mutlu

We introduce Dynamic Dropout, a novel regularization technique designed to enhance the training efficiency of Transformer models by dynamically adjusting the dropout rate based on training epochs or validation loss improvements. This…

Machine Learning · Computer Science 2024-11-06 Hanrui Yan , Dan Shao

To explore the feasibility of high-precision particle identification using the cluster counting technique for the drift chamber, a dedicated readout electronics system with low noise, high bandwidth, and high sampling rate is required. This…

Instrumentation and Detectors · Physics 2026-03-31 Dongcheng Cai , Qicai Li , Mingyi Dong , Weile Gong , Mengyang Ji , Hongbin Liu , Wenyu Pan , Linghui Wu , Dewei Xu , Yimie Yuan , Hongyu Zhang , Guang Zhao , Yubin Zhao

Fast dynamics and transient events are becoming more and more frequent in power systems, due to the high penetration of renewable energy sources and the consequent lack of inertia. In this scenario, Phasor Measurement Units (PMUs) are…

Systems and Control · Electrical Eng. & Systems 2023-06-01 Guglielmo Frigo , Paolo Attilio Pegoraro , Sergio Toscani

Electronic control systems used for quantum computing have become increasingly complex as multiple qubit technologies employ larger numbers of qubits with higher fidelity targets. Whereas the control systems for different technologies share…

Motivated by the need for adaptive, secure and responsive scheduling in a great range of computing applications, including human-centered and time-critical applications, this paper proposes a scheduling framework that seamlessly adds…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-01-14 Georgios C. Chasparis , Vladimir Janjic , Michael Rossbory

Most commercial embedded devices have been deployed with a single processor architecture. The code size and complexity of applications running on embedded devices are rapidly increasing due to the emergence of application business models…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-01-26 Geunsik Lim , Changwoo Min , YoungIk Eom

IBM TrueNorth chip uses digital spikes to perform neuromorphic computing and achieves ultrahigh execution parallelism and power efficiency. However, in TrueNorth chip, low quantization resolution of the synaptic weights and spikes…

Neural and Evolutionary Computing · Computer Science 2016-07-19 Wei Wen , Chunpeng Wu , Yandan Wang , Kent Nixon , Qing Wu , Mark Barnell , Hai Li , Yiran Chen

Ideal projective quantum measurement makes the system state collapse in one of the observable operator eigenstates $|\phi_\alpha\rangle$, making it a powerful tool for preparing the system in the desired pure state. Nevertheless,…

In cyber-physical systems, as in 5G and beyond, multiple physical processes require timely online monitoring at a remote device. There, the received information is used to estimate current and future process values. When transmitting the…

Information Theory · Computer Science 2020-05-12 Stefan Roth , Ahmed Arafa , H. Vincent Poor , Aydin Sezgin

Imaging flow cytometry systems aim to analyze a huge number of cells or micro-particles based on their physical characteristics. The vast majority of current systems acquire a large amount of images which are used to train deep artificial…

Neural and Evolutionary Computing · Computer Science 2023-03-21 Muhammed Gouda , Steven Abreu , Alessio Lugnan , Peter Bienstman

Achieving faster execution with shorter compilation time can foster further diversity and innovation in neural networks. However, the current paradigm of executing neural networks either relies on hand-optimized libraries, traditional…

Machine Learning · Computer Science 2020-01-27 Byung Hoon Ahn , Prannoy Pilligundla , Amir Yazdanbakhsh , Hadi Esmaeilzadeh

Novel electronic devices can often be operated in a plethora of ways, which makes testing circuits comprised of them difficult. Often, no single tool can simultaneously analyze the operating margins, maximum speed, and failure modes of a…

Instrumentation and Detectors · Physics 2025-09-11 Reed A. Foster , Stephen Kandeh , Owen Medeiros , Alejandro Simon , Matteo Castellani , Karl K. Berggren

Increasing the throughput of the Transformer architecture, a foundational component used in numerous state-of-the-art models for vision and language tasks (e.g., GPT, LLaVa), is an important problem in machine learning. One recent and…

Multi-core processors are becoming more and more popular in embedded and real-time systems. While fixed-priority scheduling with task-splitting in real-time systems are widely applied, current approaches have not taken into consideration…

Operating Systems · Computer Science 2015-12-24 Yao Guo , Junyang Lu

Network switches and routers need to serve packet writes and reads at rates that challenge the most advanced memory technologies. As a result, scaling the switching rates is commonly done by parallelizing the packet I/Os using multiple…

Information Theory · Computer Science 2015-04-27 Rami Cohen , Yuval Cassuto

Optical readout of GEM based devices by means of high granularity and low noise CMOS sensors allows to obtain very interesting tracking performance. Space resolution of the order of tens of $\mu$m were measured on the GEM plane along with…

Recurrent Neural Networks (RNNs) have become the state-of-the-art choice for extracting patterns from temporal sequences. However, current RNN models are ill-suited to process irregularly sampled data triggered by events generated in…

Machine Learning · Computer Science 2016-11-01 Daniel Neil , Michael Pfeiffer , Shih-Chii Liu

Read-optimized columnar databases use differential updates to handle writes by maintaining a separate write-optimized delta partition which is periodically merged with the read-optimized and compressed main partition. This merge process…