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Pronounced advance on typhoon track forecast with global convection-permitting model

Science Bulletin 2025年第9期70卷 1424-1428页

作者： Gu, Jun Zhao, Chun Li, Gudongze Feng, Jiawang Xu, Mingyue Du, Qiuyan Xia, Zihan Li, Yubin Chen, Guanghua Hao, Xiaoyu Chen, Junshi An, Hong Deep Space Exploration Laboratory / School of Earth and Space Sciences / CMA-USTC Laboratory of Fengyun Remote Sensing / State Key Laboratory of Fire Science / Institute of Advanced Interdisciplinary Research on High-Performance Computing Systems and Software University of Science and Technology of China Hefei230026 China Laoshan Laboratory Qingdao266237 China CAS Center for Excellence in Comparative Planetology University of Science and Technology of China Hefei230026 China School of Atmospheric Physics Nanjing University of Information Science and Technology Nanjing210044 China Key Laboratory of Cloud-Precipitation Physics and Severe Storms Institute of Atmospheric Physics Chinese Academy of Sciences Beijing100029 China School of Computer Science and Technology University of Science and Technology of China Hefei230026 China

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Numerical simulations of attachment-line boundary layer in hypersonic flow. Part 1. Roughness-induced subcritical transitions

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Journal of Fluid Mechanics 2025年 1009卷

作者： Xi, Youcheng Yan, Bowen Yang, Guangwen Sha, Xinguo Zhu, Dehua Fu, Song School of Aerospace Engineering Tsinghua University Beijing100084 China Institute of High Performance Computing Department of Computer Science and Technology Tsinghua University Beijing100084 China China Academy of Aerospace Aerodynamics Beijing100074 China

The attachment-line boundary layer is critical in hypersonic flows because of its significant impact on heat transfer and aerodynamic performance. In this study, high-fidelity numerical simulations are conducted to analyse the subcritical roughness-induced laminar–turbulent transition at the leading-edge attachment-line boundary layer of a blunt swept body under hypersonic conditions. This simulation represents a significant advancement by successfully reproducing the complete leading-edge contamination process induced by a surface roughness element in a realistic configuration, thereby providing previously unattainable insights. Two roughness elements of different heights are examined. For the lower-height roughness element, additional unsteady perturbations are required to trigger a transition in the wake, suggesting that the flow field around the roughness element acts as a perturbation amplifier for upstream perturbations. Conversely, a higher roughness element can independently induce the transition. A low-frequency absolute instability is detected behind the roughness, leading to the formation of streaks. The secondary instabilities of these streaks are identified as the direct cause of the final transition. © The Author(s), 2025.

关键词： Hypersonic flow

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Neural Operator Modeling of Platelet Geometry and Stress in Shear Flow

arXiv

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arXiv 2025年

作者： Laudato, Marco Manzari, Luca Shukla, Khemraj FLOW Research Center Department of Engineering Mechanics KTH Royal Institute of Technology StockholmSE-10044 Sweden PDC Center for High Performance Computing KTH Royal Institute of Technology StockholmSE-11428 Sweden Division of Applied Mathematics Brown University ProvidenceRI02906 United States

Thrombosis involves processes spanning large-scale fluid flow to sub-cellular events such as platelet activation. Traditional CFD approaches often treat blood as a continuum, which can limit their ability to capture these microscale phenomena. In this paper, we introduce a neural operator-based surrogate model to bridge this gap. Our approach employs DeepONet, trained on high-fidelity particle dynamics simulations performed in LAMMPS under a single shear flow condition. The model predicts both platelet membrane deformation and accumulated stress over time, achieving a mode error of ∼ 0.3% under larger spatial filtering radii. At finer scales, the error increases, suggesting a correlation between the DeepONet architecture’s capacity and the spatial resolution it can accurately learn. These findings highlight the importance of refining the trunk network to capture localized discontinuities in stress data. Potential strategies include using deeper trunk nets or alternative architectures optimized for graph-structured meshes, further improving accuracy for high-frequency features. Overall, the results demonstrate the promise of neural operator-based surrogates for multi-scale platelet modeling. By reducing computational overhead while preserving accuracy, our framework can serve as a critical component in future simulations of thrombosis and other micro-macro fluid-structure problems. © 2025, CC BY.

关键词： Computational fluid dynamics

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Efficient and Scalable AIxeleration of Reactive CFD Solvers Coupled with Deep Learning Inference on Heterogeneous Architectures

Efficient and Scalable AIxeleration of Reactive CFD Solvers ...

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Proceedings of the 2025 International Conference on high performance computing in Asia-Pacific Region Workshops

作者： Fabian Orland Ludovico Nista Nick Kocher Joris Vanvinckenroye Heinz Pitsch Christian Terboven High Performance Computing RWTH Aachen University Aachen Germany Institute for Combustion Technology RWTH Aachen University Aachen Germany Chair of AI Methodology RWTH Aachen University Aachen Germany

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All-optical scalable and programmable VCSEL-based Ising annealer with parallel feedback

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Optics Express 2025年第11期33卷 22119-22131页

作者： Dewen Zhang Zifeng Yuan Thanh Xuan Hoang Wujie Fu Ching Eng Png Soon Thor Lim Aaron Danner National University of Singapore Department of Electrical and Computer Engineering 4 Engineering Drive 3 117583 Singapore Institute of High Performance Computing (IHPC) Agency for Science Technology and Research (A★STAR) 1 Fusionopolis Way #16-16 Connexis 138632 Singapore

An Ising machine stands as a compelling solution for large-scale combinatorial optimization problems, leveraging its unconventional computational architecture. We propose an optical parallel feedback system, employing mutual injection locking of vertical-cavity surface-emitting lasers (VCSELs) and programmable spatial light modulators (SLMs), specifically aimed at removing electrical bottlenecks to achieve all-optical computation. Through simulation results, the ability to solve a 16-bit square-lattice MAXCUT optimization problem is analyzed. As a proof-of-concept, we demonstrate an optical injection lock using single-mode master and slave VCSELs. Remarkably, we achieve polarization switching with less than 1% of the master VCSEL’s injection power. Building upon this modest achievement, we outline a roadmap envisioning the integration of advanced nanophotonic devices, particularly metasurface-enabled SLMs and VCSELs. This strategic evolution targets scalability and programmability while upholding an all-optical computing paradigm.

关键词： Diffractive optical elements Fiber lasers Light propagation Optical parametric oscillators Spatial light modulators Vertical cavity surface emitting lasers

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PCDe: A personalized conversational debiasing framework for next POI recommendation with uncertain check-ins

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Neural Networks 2025年 188卷 107443页

作者： Li, Chen Huang, Guoyan Sun, Zhu Zhang, Lu Feng, Shanshan Liu, Guanfeng School of Computer Science and Engineering Yanshan University Qinhuangdao066000 China Pillar of Information Systems Technology and Design Singapore University of Technology and Design 487372 Singapore Chengdu University of Information Technology Chengdu610000 China SUGON Industrial Control and Security Center Chengdu610000 China Center for Frontier AI Research Agency for Science Technology and Research 138632 Singapore Institute of High Performance Computing Agency for Science Technology and Research 138632 Singapore School of Computing Macquarie University Sydney2109 Australia

In the next point-of-interest (POI) recommendation, users may visit individual POIs within larger gathering places, such as shopping malls (termed as collective POIs), leading to uncertain check-ins. Our data analysis unveils that (1) the presence of such uncertain check-ins raises a new type of bias, termed as scale bias, that is, the recommender tends to recommend collective POIs over individual POIs, which further exacerbates the commonly-observed popularity bias, that is, the recommender tends to recommend popular POIs rather than unpopular ones;and (2) the existence of the above two types of biases significantly affects the fairness of next POI recommendation with uncertain check-ins. Therefore, we propose a Personalized Conversational Debiasing framework (PCDe) by exploiting the advantages of conversational techniques to capture personalized dynamic user preferences, thereby mitigating both scale and popularity biases at a personalized level. Specifically, the inquiry component designs an improved question-and-answer manner based on personalized information entropy, thus mitigating the scale bias. The rewarding component then introduces a novel debiasing reward mechanism based on the Jensen–Shannon divergence to make the recommendations better aligned with users’ historical preferences on popularity, thereby addressing the popularity bias. Extensive experiments demonstrate the superiority of our proposed PCDe over state-of-the-arts (SOTAs) regarding mitigating scale and popularity biases while enhancing recommendation accuracy thanks to its personalized debiasing mechanism. © 2025

关键词： Conversational recommendation Next POI recommendation Popularity bias Scale bias Uncertain check-ins

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A Decade of Action Quality Assessment: Largest Systematic Survey of Trends, Challenges, and Future Directions

arXiv

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arXiv 2025年

作者： Yin, Hao Parmar, Paritosh Xu, Daoliang Zhang, Yang Zheng, Tianyou Fu, Weiwei Division of Life Sciences and Medicine University of Science and Technology of China Anhui Hefei China Suzhou Institute of Biomedical Engineering and Technology Chinese Academy of Science Jiangsu Suzhou China Institute of High Performance Computing Agency for Science Technology and Research Singapore

Action Quality Assessment (AQA)—the ability to quantify the quality of human motion, actions, or skill levels and provide feedback—has far-reaching implications in areas such as low-cost physiotherapy, sports training, and workforce development. As such, it has become a critical field in computer vision & video understanding over the past decade. Significant progress has been made in AQA methodologies, datasets, & applications, yet a pressing need remains for a comprehensive synthesis of this rapidly evolving field. In this paper, we present a thorough survey of the AQA landscape, systematically reviewing over 200 research papers using the preferred reporting items for systematic reviews & meta-analyses (PRISMA) framework. We begin by covering foundational concepts & definitions, then move to general frameworks & performance metrics, & finally discuss the latest advances in methodologies & datasets. This survey provides a detailed analysis of research trends, performance comparisons, challenges, & future directions. Through this work, we aim to offer a valuable resource for both newcomers & experienced researchers, promoting further exploration & progress in AQA. Data are available at https://***/Survey_of_AQA/. Copyright © 2025, The Authors. All rights reserved.

关键词： Personnel training

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An Analysis of User-space Idle State Instructions on x86 Processors 25

An Analysis of User-space Idle State Instructions on x86 Pro...

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Proceedings of the 16th ACM/SPEC International Conference on performance Engineering

作者： Malte-Christian Kuns Hannes Tröpgen Robert Schöne Institute for Computer Engineering Faculty of Computer Science TU Dresden Dresden Germany Information Services and High Performance Computing (ZIH) Center for Interdisciplinary Digital Sciences (CIDS) TU Dresden Dresden Germany

ISBN: (纸本)9798400710735

Power consumption has become a limiting factor in all areas of computing. Hence, making the most of the available power budget is paramount. To use the available budget most efficiently, techniques like dynamic voltage and frequency scaling and idle states can be used. This work analyzes the instructions UMWAIT, TPAUSE, and MWAITX on three different systems. We analyze their instruction latencies, power consumptions, and dependencies on core frequencies. To do so, we introduce benchmarks to gather performance and power parameters, which can be used for future software optimizations. Key findings include: The expected sleep duration passed to UMWAIT and TPAUSE can influence the depth of the user idle state. The actual sleep duration of TPAUSE increases stepwise with an increasing expected sleep duration. Requesting a deeper idle state leads to an additional sleep duration, which increases with a lower core frequency. The core frequency influences the instruction latency of TPAUSE, where a low frequency can lead to an irregular performance pattern. The latency of TPAUSE, UMWAIT, and MWAITX is most often higher than requested on the evaluated systems. Core power consumption can be reduced by ~20% ~70% compared to the usage of PAUSE. The latency for waking a core in user idle reflects the underlying hardware architecture with tens (desktop architecture with shallow idle states) to hundreds (server architecture with deep idle states) of nanoseconds at nominal frequencies.

关键词： energy efficiency

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Federated Single Sign-On and Zero Trust Co-design for AI and HPC Digital Research Infrastructures 24

Federated Single Sign-On and Zero Trust Co-design for AI and...

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Proceedings of the SC '24 Workshops of the International Conference on high performance computing, Network, Storage, and Analysis

作者： Sadaf R. Alam Christopher Woods Matt Williams Dave Moore Isaac Prior Ethan Williams Anna Price James Womack Simon McIntosh-Smith Fan Yang-Turner Matt Pryor Ilja Livenson Bristol Centre for Supercomputing University of Bristol Bristol United Kingdom StackHPC Beacon Tower Bristol United Kingdom Institute of Computer Science High Performance Computing Center University of Tartu Tartu Estonia

ISBN: (纸本)9798350355543

Scientific workflows have become highly heterogenous, leveraging distributed facilities such as high performance computing (HPC), Artificial Intelligence (AI), Machine Learning (ML), scientific instruments (data-driven pipelines) and edge computing. As a result, Identity and Access Management (IAM) and Cybersecurity challenges across the diverse hardware and software stacks are growing. Nevertheless, scientific productivity relies on lowering access barriers via seamless, single sign-on (SSO) and federated login while ensuring access controls and compliance. We present an implementation of a federated IAM solution, which is coupled with multiple layers of security controls, multi-factor authentication, cloud-native protocols, and time-limited role-based access controls (RBAC) that has been co-designed and deployed for the Isambard-AI and HPC supercomputing Digital Research Infrastructures (DRIs) in the UK. Isambard DRIs as a national research resource are expected to comply with regulatory frameworks. Implementation details for monitoring, alerting and controls are outlined in the paper alongside selected user stories for demonstrating IAM workflows for different roles.

关键词： AI

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Robust Integration of Fast Flavor Conversions in Classical Neutrino Transport

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Physical Review Letters 2025年第5期134卷 051003-051003页

作者： Zewei Xiong Meng-Ru Wu Manu George Chun-Yu Lin GSI Helmholtzzentrum für Schwerionenforschung Planckstraße 1 64291 Darmstadt Germany Institute of Physics Academia Sinica Taipei 115201 Taiwan Institute of Astronomy and Astrophysics Academia Sinica Taipei 106319 Taiwan Physics Division National Center for Theoretical Sciences Taipei 106319 Taiwan National Center for High-performance Computing Hsinchu 30076 Taiwan

The quantum kinetic evolution of neutrinos in dense environments, such as the core-collapse supernovae or the neutron star mergers, can result in fast flavor conversion (FFC), presenting a significant challenge to achieving robust astrophysical modeling of these systems. Recent works that directly simulate the quantum kinetic transport of neutrinos in localized domains have suggested that the asymptotic outcome of FFCs can be modeled by simple analytical prescriptions when coarse grained over a size much larger than the FFC length scale. In this Letter, by leveraging such a scale separation, we incorporate the analytical prescriptions into global simulations that solve the classical neutrino transport equation including collisions and advection under spherical symmetry. We demonstrate that taking this approach allows to obtain results that quantitatively agree with those directly from the corresponding global quantum kinetic simulations and precisely capture the collisional feedback effect for cases where the FFC happens inside the neutrinosphere. Notably, the effective scheme does not require resolving the FFC time and length scales, hence only adds negligible computational overhead to classical transport. Our work highlights that efficient and robust integration of FFCs in classical neutrino transport used in astrophysical simulation can be feasible.

关键词： Supernovae

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