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Jigsaw-Sketch: a fast and accurate algorithm for finding top-k elephant flows in high-speed networks

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science China(Information sciences) 2024年第4期67卷 113-130页

作者： Boyu ZHANG He HUANG Yu-E SUN Yang DU Dan WANG school of computer science and technology Soochow University school of Rail Transportation Soochow University

Finding top-k elephant flows in high-speed networks is one of the most fundamental network measurement tasks. It is more challenging than per-flow size estimation since the IDs and sizes of top-k flows must be tracked simultaneously. Most existing studies only record the IDs of a small number of elephant flows to fit their estimators in the extremely limited high-speed on-chip memory. However, these solutions need too many memory accesses when a packet arrives to track the elephant flows with high accuracy, which limits their practicability. Therefore, this paper proposes Jigsaw-Sketch, a new algorithm to find the top-k elephant flows with much fewer memory accesses while achieving high memory efficiency and accuracy. In this design, we propose a novel two-stage jigsaw storage scheme, which can capture the candidate top-k flows from massive network steams efficiently, and further find the top-k elephant flows with high memory efficiency and only a few memory accesses for each packet. Extensive experimental results based on real network traces show that Jigsaw-Sketch improves the packet processing throughput by at least 86%, while achieving smaller memory footprints and higher accuracy compared to the SOTA.

关键词： sketch top-$k$ network measurement elephant flow high-speed networks

Dynamic Event-Triggered Consensus Control for Input Constrained Multi-Agent Systems With a Designable Minimum Inter-Event Time

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IEEE/CAA Journal of Automatica Sinica 2024年第3期11卷 649-660页

作者： Meilin Li Yue Long Tieshan Li Hongjing Liang C.L.Philip Chen the school of Automation Engineering University of Electronic Science and Technology of ChinaChengdu 611731China IEEE the Yangtze Delta Region Institute University of Electronic Science and Technology of ChinaHuzhou 313000 the Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing 100089China the school of computer science and Engineering South China University of TechnologyGuangzhou 510006

This paper investigates the consensus control of multi-agent systems(MASs) with constrained input using the dynamic event-triggered mechanism(ETM).Consider the MASs with small-scale networks where a centralized dynamic ETM with global information of the MASs is first ***,a distributed dynamic ETM which only uses local information is developed for the MASs with large-scale *** is shown that the semi-global consensus of the MASs can be achieved by the designed bounded control protocol where the Zeno phenomenon is eliminated by a designable minimum inter-event *** addition,it is easier to find a trade-off between the convergence rate and the minimum inter-event time by an adjustable ***,the results are extended to regional consensus of the MASs with the bounded control *** simulations show the effectiveness of the proposed approach.

关键词： Constrained input designable minimum inter-event time directed communication topology dynamic event-triggered mechanism MASs consensus control

Incorporating contextual evidence to improve implicit discourse relation recognition in Chinese

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Frontiers of computer science 2024年第3期18卷 91-104页

作者： Sheng XU Peifeng LI Qiaoming ZHU school of computer science and technology Soochow UniversitySuzhou 215000China

The discourse analysis task,which focuses on understanding the semantics of long text spans,has received increasing attention in recent *** a critical component of discourse analysis,discourse relation recognition aims to identify the rhetorical relations between adjacent discourse units(e.g.,clauses,sentences,and sentence groups),called arguments,in a *** works focused on capturing the semantic interactions between arguments to recognize their discourse relations,ignoring important textual information in the surrounding ***,in many cases,more than capturing semantic interactions from the texts of the two arguments are needed to identify their rhetorical relations,requiring mining more contextual *** this paper,we propose a method to convert the RST-style discourse trees in the training set into dependency-based trees and train a contextual evidence selector on these transformed *** this way,the selector can learn the ability to automatically pick critical textual information from the context(i.e.,as evidence)for arguments to assist in discriminating their *** we encode the arguments concatenated with corresponding evidence to obtain the enhanced argument ***,we combine original and enhanced argument representations to recognize their *** addition,we introduce auxiliary tasks to guide the training of the evidence selector to strengthen its selection *** experimental results on the Chinese CDTB dataset show that our method outperforms several state-of-the-art baselines in both micro and macro F1 scores.

关键词： discourse parsing discourse relation recognition contextual evidence selection

Identifying influential spreaders in complex networks based on density entropy and community structure

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Chinese Physics B 2024年第5期33卷 765-774页

作者：苏湛陈磊艾均郑雨语别娜 school of Optical-Electrical and computer Engineering University of Shanghai for Science and Technology

In recent years,exploring the relationship between community structure and node centrality in complex networks has gained significant attention from researchers,given its fundamental theoretical significance and practical *** address the impact of network communities on target nodes and effectively identify highly influential nodes with strong propagation capabilities,this paper proposes a novel influential spreaders identification algorithm based on density entropy and community structure(DECS).The proposed method initially integrates a community detection algorithm to obtain the community partition results of the *** then comprehensively considers the internal and external density entropies and degree centrality of the target node to evaluate its *** validation is conducted on eight networks of varying sizes through susceptible–infected–recovered(SIR)propagation experiments and network static attack *** experimental results demonstrate that the proposed method outperforms five other node centrality methods under the same comparative conditions,particularly in terms of information spreading capability,thereby enhancing the accurate identification of critical nodes in networks.

关键词： corrigendum electron impact ionization cross sections carbon monoxide

APF-GAN:Exploring asymmetric pre-training and fine-tuning strategy for conditional generative adversarial network

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Computational Visual Media 2024年第1期10卷 187-192页

作者： Yuxuan Li Lingfeng Yang Xiang Li College of computer science Nankai UniversityTianjinChina school of computer science and Engineering Nanjing University of Science and TechnologyNanjingChina

The use of generative adversarial network(GAN)-based models for the conditional generation of image semantic segmentation has shown promising results in recent ***,there are still some limitations,including limited diversity of image style,distortion of detailed texture,unbalanced color tone,and lengthy training *** address these issues,we propose an asymmetric pre-training and fine-tuning(APF)-GAN model.

关键词： tuning network asymmetric

Towards Effective Author Name Disambiguation by Hybrid Attention

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Journal of computer science & technology 2024年第4期39卷 929-950页

作者： Qian Zhou Wei Chen Peng-Peng Zhao An Liu Jia-Jie Xu Jian-Feng Qu Lei Zhao school of computer science and technology Soochow UniversitySuzhou 215006China

Author name disambiguation(AND)is a central task in academic search,which has received more attention recently accompanied by the increase of authors and academic *** tackle the AND problem,existing studies have proposed various approaches based on different types of information,such as raw document features(e.g.,co-authors,titles,and keywords),the fusion feature(e.g.,a hybrid publication embedding based on multiple raw document features),the local structural information(e.g.,a publication's neighborhood information on a graph),and the global structural information(e.g.,interactive information between a node and others on a graph).However,there has been no work taking all the above-mentioned information into account and taking full advantage of the contributions of each raw document feature for the AND problem so *** fill the gap,we propose a novel framework named EAND(Towards Effective Author Name Disambiguation by Hybrid Attention).Specifically,we design a novel feature extraction model,which consists of three hybrid attention mechanism layers,to extract key information from the global structural information and the local structural information that are generated from six similarity graphs constructed based on different similarity coefficients,raw document features,and the fusion *** hybrid attention mechanism layer contains three key modules:a local structural perception,a global structural perception,and a feature ***,the mean absolute error function in the joint loss function is used to introduce the structural information loss of the vector *** results on two real-world datasets demonstrate that EAND achieves superior performance,outperforming state-of-the-art methods by at least+2.74%in terms of the micro-F1 score and+3.31%in terms of the macro-F1 score.

关键词： author name disambiguation multiple-feature information hybrid attention pruning strategy structural information loss of vector space

Total ionizing dose effect modeling method for CMOS digital-integrated circuit

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Nuclear science and Techniques 2024年第2期35卷 32-46页

作者： Bo Liang Jin-Hui Liu Xiao-Peng Zhang Gang Liu Wen-Dan Tan Xin-Dan Zhang school of computer science and technology Xidian UniversityXi’an 710071China

Simulating the total ionizing dose(TID)of an electrical system using transistor-level models can be difficult and expensive,particularly for digital-integrated circuits(ICs).In this study,a method for modeling TID effects in complementary metaloxide semiconductor(CMOS)digital ICs based on the input/output buffer information specification(IBIS)was *** digital IC was first divided into three parts based on its internal structure:the input buffer,output buffer,and functional *** of these three parts was separately *** the IBIS model,the transistor V-I characteristic curves of the buffers were processed,and the physical parameters were extracted and modeled using *** the functional area,logic functions were modeled in VHDL according to the data sheet.A golden digital IC model was developed by combining the input buffer,output buffer,and functional area ***,the golden ratio was reconstructed based on TID experimental data,enabling the assessment of TID effects on the threshold voltage,carrier mobility,and time series of the digital *** experiments were conducted using a CMOS non-inverting multiplexer,NC7SZ157,and the results were compared with the simulation results,which showed that the relative errors were less than 2%at each dose *** confirms the practicality and accuracy of the proposed modeling *** TID effect model for digital ICs developed using this modeling technique includes both the logical function of the IC and changes in electrical properties and functional degradation impacted by TID,which has potential applications in the design of radiation-hardening tolerance in digital ICs.

关键词： CMOS digital-integrated circuit Total ionizing dose IBIS model Behavior-physical hybrid model Physical parameters

TSCompiler: efficient compilation framework for dynamic-shape models

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science China(Information sciences) 2024年第10期67卷 67-84页

作者： Xiang LUO Chen ZHANG Chenbo GENG Yanzhi YI Jiahui HU Renwei ZHANG Zhen ZHANG Gianpietro CONSOLARO Fan YANG Tun LU Ning GU Li SHANG school of computer science Fudan University school of electronic Information and Electrical Engineering Shanghai Jiao Tong University school of computer science and technology Harbin Institute of Technology Huawei Technologies Co. Ltd. Huawei Paris Research Center school of Microelectronics Fudan University

Today's deep learning models face an increasing demand to handle dynamic shape tensors and computation whose shape information remains unknown at compile time and varies in a nearly infinite range at runtime. This shape dynamism brings tremendous challenges for existing compilation pipelines designed for static models which optimize tensor programs relying on exact shape values. This paper presents TSCompiler, an end-to-end compilation framework for dynamic shape models. TSCompiler first proposes a symbolic shape propagation algorithm to recover symbolic shape information at compile time to enable subsequent optimizations. TSCompiler then partitions the shape-annotated computation graph into multiple subgraphs and fine-tunes the backbone operators from the subgraph within a hardware-aligned search space to find a collection of high-performance schedules. TSCompiler can propagate the explored backbone schedule to other fusion groups within the same subgraph to generate a set of parameterized tensor programs for fused cases based on dependence analysis. At runtime, TSCompiler utilizes an occupancy-targeted cost model to select from pre-compiled tensor programs for varied tensor shapes. Extensive evaluations show that TSCompiler can achieve state-of-the-art speedups for dynamic shape models. For example, we can improve kernel efficiency by up to 3.97× on NVIDIA RTX3090, and 10.30× on NVIDIA A100 and achieve up to five orders of magnitude speedups on end-to-end latency.

关键词： machine learning tensor compilers dynamic shape operator fusion code generation auto-tuning

Dynamical behaviors in discrete memristor-coupled small-world neuronal networks

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Chinese Physics B 2024年第4期33卷 729-734页

作者：鲁婕妤谢小华卢亚平吴亚联李春来马铭磷 school of Automation and electronic Information Xiangtan UniversityXiangtan 411105China school of computer science school of Cyberspace science Xiangtan UniversityXiangtan 411105China

The brain is a complex network system in which a large number of neurons are widely connected to each other and transmit signals to each *** memory characteristic of memristors makes them suitable for simulating neuronal synapses with *** this paper,a memristor is used to simulate a synapse,a discrete small-world neuronal network is constructed based on Rulkov neurons and its dynamical behavior is *** explore the influence of system parameters on the dynamical behaviors of the discrete small-world network,and the system shows a variety of firing patterns such as spiking firing and triangular burst firing when the neuronal parameterαis *** results of a numerical simulation based on Matlab show that the network topology can affect the synchronous firing behavior of the neuronal network,and the higher the reconnection probability and number of the nearest neurons,the more significant the synchronization state of the *** addition,by increasing the coupling strength of memristor synapses,synchronization performance is *** results of this paper can boost research into complex neuronal networks coupled with memristor synapses and further promote the development of neuroscience.

关键词： small-world networks Rulkov neurons memristor synchronization