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2023 International Conference on High Performance Computing in Asia-Pacific Region Workshops, HPC Asia 2023

作者： Kikuchi, Kohei Fujita, Norihisa Kobayashi, Ryohei Boku, Taisuke Master's Program in Computer Science Degree Programs in Systems and Information Engineering Graduate School of Science and Technology University of Tsukuba Tsukuba Japan Center for Computational Sciences University of Tsukuba Tsukuba Japan

ISBN: (纸本)9781450399890

In the high-performance computing domain, Field programmable Gate Array (FPGA) is a novel accelerator that exhibits high flexibility and performance characteristics distinct from other accelerators such as the Graphics Processing Unit (GPU). Recent advanced high-end FPGA is equipped with multiple channels of high speed optical link up to 100Gbps performance for each. This is a crucial feature when we construct PC clusters with FPGAs as accelerators, however it is not easy to utilize from user kernels because this feature is implemented in low level and simple direct communication between neighboring FPGAs. In order to provide the communication feature between FPGAs for accelerated PC clusters, we developed a communication system named CIRCUS which implies a user-friendly API from OpenCL and is equipped with routing function over multi-hop communication on multi-dimensional torus network of FPGAs. However, current CIRCUS only provides a point-to-point communication between source and destination FPGAs. In ordinary parallel processing environment such as MPI, the user program the message passing with various collective communication functions for parallel algorithm, for instance Allreduce, Allgather, etc. In this paper, we implement the collective communication function over CIRCUS for user-friendly programming of ordinary parallel algorithms on FPGAs. As the first target, we implement Allreduce function which is the most essential and important function. The paper describes the CIRCUS system briefly followed by the design, implementation and preliminary performance evaluation on Intel Stratix10 FPGAs. © 2023 ACM.

关键词： Field programmable gate arrays (FPGA)

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Large Pre-Trained Models and Few-Shot FineTuning for Virtual Metrology: A Framework for Uncertainty-Driven Adaptive Process Control in Semiconductor Manufacturing

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IEEE Transactions on Automation science and engineering 2025年 22卷 15351-15370页

作者： Lin, Chin-Yi Tseng, Tzu-Liang Emon, Solayman Hossain Tsai, Tsung-Han University of Texas at EL Paso Department of Industrial Manufacturing and Systems Engineering Texas El PasoTX79968 United States Computational Science Program University of Texas at EL Paso Texas El PasoTX79968 United States National Taipei University of Business Institute of Information and Decision Sciences Taipei10051 Taiwan

High-precision wafer metrology poses significant cost and throughput challenges in modern semiconductor manufacturing, where frequent process changes and recipe variations demand highly adaptive and scalable solutions. In this paper, we present a Generative-FewShot-Active Virtual Metrology (GFA-VM) framework that unifies large-scale generative modeling, few-shot fine-tuning, and uncertainty-driven active sampling into a single, data-centric system. A foundational generative model, built on a hybrid architecture of Transformer networks and Variational Autoencoders (VAEs), learns diverse sensor characteristics in an offline stage without relying on extensive labeled data. During online inference, the model produces both wafer quality predictions and predictive uncertainties;samples exceeding a dynamic uncertainty threshold are selected for physical measurement and few-shot model recalibration. This selective sampling both reduces measurement costs and adapts rapidly to new process conditions (e.g., novel recipes or equipment upgrades), requiring only a handful of freshly labeled wafers. The paper further addresses the long-term stability of the system through a self-updating mechanism that adjusts the uncertainty threshold when distributional shifts occur. Empirical evaluations confirm that our GFA-VM approach achieves state-of-the-art accuracy while significantly reducing metrology overhead compared to conventional virtual metrology methods. Additionally, rigorous theoretical analyses—including proofs of convergence and label cost bounds—demonstrate the reliability of using a generative foundation plus meta-learning technique. By fostering on-demand adaptation within a closedloop framework, GFA-VM offers a comprehensive, scalable strategy for next-generation semiconductor process control. © 2004-2012 IEEE.

关键词： Semiconductor device measurement Metrology Semiconductor device modeling Semiconductor process modeling Uncertainty Adaptation models Accuracy Data models Predictive models Manufacturing

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Optimal Synergic Deep Learning for COVID-19 Classification Using Chest X-Ray Images

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Computers, Materials & Continua 2023年第6期75卷 5255-5270页

作者： JoséEscorcia-Gutierrez Margarita Gamarra Roosvel Soto-Diaz Safa Alsafari Ayman Yafoz Romany F.Mansour Departament of Computational Science and Electronic Universidad de la CostaCUCBarranquilla080002Colombia Biomedical Engineering Program Universidad Simón BolívarBarranquilla080002Colombia Department of Computer Science and AI Faculty of Computer Science and EngineeringUniversity of JeddahJeddahSaudi Arabia Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia Department of Mathematics Faculty of ScienceNew Valley UniversityEl-Kharga72511Egypt

A chest radiology scan can significantly aid the early diagnosis and management of COVID-19 since the virus attacks the *** X-ray(CXR)gained much interest after the COVID-19 outbreak thanks to its rapid imaging time,widespread availability,low cost,and *** radiological investigations,computer-aided diagnostic tools are implemented to reduce intra-and inter-observer *** lately industrialized Artificial Intelligence(AI)algorithms and radiological techniques to diagnose and classify disease is *** current study develops an automatic identification and classification model for CXR pictures using Gaussian Fil-tering based Optimized Synergic Deep Learning using Remora Optimization Algorithm(GF-OSDL-ROA).This method is inclusive of preprocessing and classification based on *** data is preprocessed using Gaussian filtering(GF)to remove any extraneous noise from the image’s ***,the OSDL model is applied to classify the CXRs under different severity levels based on CXR *** learning rate of OSDL is optimized with the help of ROA for COVID-19 diagnosis showing the novelty of the *** model,applied in this study,was validated using the COVID-19 *** experiments were conducted upon the proposed OSDL model,which achieved a classification accuracy of 99.83%,while the current Convolutional Neural Network achieved less classification accuracy,i.e.,98.14%.

关键词： Artificial intelligence chest X-ray COVID-19 optimized synergic deep learning preprocessing public health

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Automated Deep Learning Empowered Breast Cancer Diagnosis UsingBiomedical Mammogram Images

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Computers, Materials & Continua 2022年第6期71卷 4221-4235页

作者： JoséEscorcia-Gutierrez Romany F.Mansour Kelvin Belen Javier Jiménez-Cabas Meglys Pérez Natasha Madera Kevin Velasquez Electronics and Telecommunications Engineering Program Universidad Autónoma del CaribeBarranquilla08001Colombia Department of Mathematics Faculty of ScienceNew Valley UniversityEl-Kharga72511Egypt Mechatronics Engineering Program Universidad Autónoma del CaribeBarranquilla08001Colombia Department of Computational Science and Electronic Universidad de la CostaCUCBarranquilla08001Colombia

Biomedical image processing is a hot research topic which helps to majorly assist the disease diagnostic *** the same time,breast cancer becomes the deadliest disease among women and can be detected by the use of different imaging *** mammograms can be used for the earlier identification and diagnostic of breast cancer to minimize the death *** the proper identification of breast cancer has mainly relied on the mammography findings and results to increased false *** resolving the issues of false positives of breast cancer diagnosis,this paper presents an automated deep learning based breast cancer diagnosis(ADL-BCD)model using digital *** goal of the ADL-BCD technique is to properly detect the existence of breast lesions using digital *** proposed model involves Gaussian filter based pre-processing and Tsallis entropy based image *** addition,Deep Convolutional Neural Network based Residual Network(ResNet 34)is applied for feature extraction ***,a hyper parameter tuning process using chimp optimization algorithm(COA)is applied to tune the parameters involved in ResNet 34 *** wavelet neural network(WNN)is used for the classification of digital mammograms for the detection of breast *** ADL-BCD method is evaluated using a benchmark dataset and the results are analyzed under several performance *** simulation outcome indicated that the ADL-BCD model outperforms the state of art methods in terms of different measures.

关键词： Breast cancer digital mammograms deep learning wavelet neural network Resnet 34 disease diagnosis

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Using SYCLomatic to Migrate CUDA Code to oneAPI Adapting NVIDIA GPU

Using SYCLomatic to Migrate CUDA Code to oneAPI Adapting NVI...

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IEEE International Conference on Cluster Computing Workshops and Posters (CLUSTER WORKSHOPS)

作者： Wentao Liang Norihisa Fujita Ryohei Kobayashi Taisuke Boku Master's Program in Computer Science Degree Program in Systems and Information Engineering Graduate School of Science and Technology University of Tsukuba Center for Computational Sciences University of Tsukuba

ISBN: (数字)9798350383454

ISBN: (纸本)9798350383461

Nowadays, the use of accelerators in high performance computing has become more common than ever before. The most used accelerators must be the Graphics Processing Unit (GPU). It has emerged as an important component in most of the parallel computing scenarios, surpassing the capabilities of the traditional Central Processing Unit (CPU) in perspective of both performance and energy efficiency.

关键词： Codes Conferences High performance computing Graphics processing units Cluster computing Parallel processing Energy efficiency Central Processing Unit

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LATTICE-VALUED BOTTLENECK DUALITY

arXiv

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arXiv 2024年

作者： Ghrist, Robert Gould, Julian Lopez, Miguel Department of Mathematics Department of Electrical & Systems Engineering and Program in Applied Mathematics & Computational Science University of Pennsylvania United States

This note reformulates certain classical combinatorial duality theorems in the context of order lattices. For source-target networks, we generalize bottleneck path-cut and flow-cut duality results to edges with capacities in a distributive lattice. For posets, we generalize a bottleneck version of Dilworth’s theorem, again weighted in a distributive lattice. These results are applicable to a wide array of non-numerical network flow problems, as shown. All results, proofs, and applications were created in collaboration with AI language models. An appendix documents their role and *** Codes 06D05, 90C35, 06A07 © 2024, CC BY.

关键词： Combinatorial optimization

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A Multi-phase Deep Learning Approach for Predicting HCC Response to TACE using Complete Computed Tomography

A Multi-phase Deep Learning Approach for Predicting HCC Resp...

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2023 IEEE EMBS Special Topic Conference on Data science and engineering in Healthcare, Medicine and Biology, IEEECONF 2023

作者： Chang, Shun Cheng Liu, Chien Fu Misztal, Marta Hsieh, Yi Hsien Lin, Che Taiwan School of Electronic Engineering and Computer Science Queen Mary University of London United Kingdom Department of Electrical Engineering Ntu Taiwan Center for Computational and Systems Biology Center for Biotechnology Ntu Taiwan Smart Medicine and Health Informatics Program Ntu Taiwan

ISBN: (纸本)9798350383386

In this research study, we compare the predictive performance of two advanced deep learning-based models in order to provide a solution to TACE (Transarterial Chemoembolization) response prediction in HCC (Hepatocellular Carcinoma) patients. Using entire abdominal CT scans enabled a broader perspective available for the model, eliminating the need for segmentation during the preprocessing. Making use of both single-phase and multi-phase CT imaging, we have used DenseNet121 and have obtained an accuracy of 80% for the multi-phase *** Relevance: The ability to predict the effectiveness of TACE treatment prior to its administration makes it possible to provide a better decision-making aid for physicians and patients. © 2023 IEEE.

关键词： Computerized tomography

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Evidence of electronic structural change at the metal-insulator transition in the perovskite NaOsO3

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Physical Review B 2023年第19期108卷 195115-195115页

作者： J.-S. Zhou X.-Y. Li M. D. Johannes Materials Science and Engineering Program Mechanical Engineering University of Texas at Austin Austin Texas 78712 USA Center for Computational Materials Science Naval Research Laboratory Washington D.C. 20375 USA

NaOsO3 exhibits an unusual metal-insulator transition (MIT) that has been touted as Slater type, though there are observations that do not entirely conform to this typing. Consistent with a Slater transition, the cell volume and crystal symmetry show no change on cooling through the transition, but both a and b axes in this Pbnm orthorhombic perovskite show a clear kink, and the splitting between them enlarges slightly. Since atomic positions, determined by fitting the intensity of state-of-the-art neutron diffraction data, exhibit no anomalies within the measurement uncertainty, the origin of the a−b splitting and the kink in the data have not yet been elucidated. Understanding the origin of these subtle structural changes across the transition temperature may provide understanding about the electronic behavior. In this paper, we connect local structural changes to changes in the lattice parameters through (1) well-established structural modeling and (2) density functional theory (DFT) calculations. This approach successfully reveals a subtle but significant change of the O-Os-O bond angle on cooling through TMIT. A Madelung energy calculation suggests that this bond angle change signals electron localization in the t2g orbital complex, and this is verified by DFT, which shows an electronic transition from itinerant to localized electronic behavior along with the bond angle shift. In this detailed structural study, we add an important though heretofore overlooked element in the microscopic picture of the MIT in NaOsO3.

关键词： Density of states Jahn-Teller effect Spin-orbit coupling Mott insulators Strongly correlated systems

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An Iterative Thresholding Method for the Minimum Compliance Problem

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Communications in computational Physics 2023年第4期33卷 1189-1216页

作者： Luyu Cen Wei Hu Dong Wang Xiaoping Wang Department of Mathematics Hong Kong University of Science and TechnologyClear Water BayKowloonHong KongChina The Program in Applied and Computational Mathematics Princeton UniversityPrincetonNew JerseyUSA School of Science and Engineering The Chinese University of Hong KongShenzhenGuangdong 518172China Shenzhen International Center for Industrial and Applied Mathematics Shenzhen Research Institute of Big DataGuangdong 518172China

In this paper,we propose a simple energy decaying iterative thresholding algorithm to solve the two-phase minimum compliance *** material domain is implicitly represented by its characteristic function,and the problem is formulated into a minimization problem by the principle of minimum complementary *** prove that the energy is decreasing in each *** effective continuation schemes are proposed to avoid trapping into the local *** results on 2D isotropic linear material demonstrate the effectiveness of the proposed methods.

关键词： Minimum compliance convolution thresholding linear elasticity

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Concentrated ternary ether electrolyte allows for stable cycling of a lithium metal battery with commercial mass loading high-nickel NMC and thin anodes

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Carbon Energy 2023年第3期5卷 2-18页

作者： Jun Yang Xing Li Ke Qu Yixian Wang Kangqi Shen Changhuan Jiang Bo Yu Pan Luo Zhuangzhi Li Mingyang Chen Bingshu Guo Mingshan Wang Junchen Chen Zhiyuan Ma Yun Huang Zhenzhong Yang Pengcheng Liu Rong Huang Xiaodi Ren David Mitlin School of New Energy and Materials Southwest Petroleum UniversityChengduChina Energy Storage Research Institute Southwest Petroleum UniversityChengduChina Shenzhen Key Laboratory of Nanobiomechanics Shenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhenChina China Key Laboratory of Polar Materials and Devices(MOE) Department of ElectronicsEast China Normal UniversityShanghaiChina Materials Science Program and Texas Materials Institute The University of Texas at AustinAustinTexasUSA Beijing Computational Science Research Center BeijingChina School of Materials Science and Engineering Center for Green Innovation University of Science and Technology BeijingBeijingChina Department of Materials Science and Engineering Hefei National Research Center for Physical Sciences at the MicroscaleUniversity of Science and Technology of ChinaHefeiAnhuiChina

A new concentrated ternary salt ether-based electrolyte enables stable cycling of lithium metal battery(LMB)cells with high-mass-loading(13.8 mg cm^(−2),2.5 mAh cm^(−2))NMC622(LiNi_(0.6)Co_(0.2)Mn_(0.2)O_(2))cathodes and 50μm Li ***“CETHER-3,”this electrolyte is based on LiTFSI,LiDFOB,and LiBF4 with 5 vol%fluorinated ethylene carbonate in 1,***-cial carbonate and state-of-the-art binary salt ether electrolytes were also tested as *** CETHER-3,the electrochemical performance of the full-cell battery is among the most favorably reported in terms of high-voltage cycling *** example,LiNi_(x)Mn_(y)Co_(1-x-y)O_(2)(NMC)-Li metal cells retain 80%capacity at 430 cycles with a 4.4 V cut-off and 83%capacity at 100 cycles with a 4.5 V cut-off(charge at C/5,discharge at C/2).According to simulation by density functional theory and molecular dynamics,this favorable performance is an outcome of enhanced coordination between Li^(+)and the solvent/salt *** advanced microscopy(high-resolution transmission electron microscopy,scanning electron microscopy)and surface science(X-ray photoelectron spectroscopy,time-of-fight secondary ion mass spectroscopy,Fourier-transform infrared spectroscopy,Raman spectroscopy),it is demonstrated that a thinner and more stable cathode electrolyte interphase(CEI)and solid electrolyte interphase(SEI)are *** CEI is rich in lithium sulfide(Li_(2)SO_(3)),while the SEI is rich in Li_(3)N and *** cycling,the CEI/SEI suppresses both the deleterious transformation of the cathode R-3m layered near-surface structure into disordered rock salt and the growth of lithium metal dendrites.

关键词： concentrated electrolyte density functional theory ether electrolyte high‐nickel cathode high‐voltage battery molecular dynamics

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