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A survey on dynamic graph processing on GPUs: concepts, terminologies and systems

Frontiers of Computer Science 2024年第4期18卷 1-23页

作者： Hongru GAO Xiaofei LIAO Zhiyuan SHAO Kexin LI Jiajie CHEN Hai JIN National Engineering Research Center for Big Data Technology and System/Services Computing Technology and System Lab/Cluster and Grid Computing Lab School of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China Zhejiang Lab Hangzhou 311121China

Graphs that are used to model real-world entities with vertices and relationships among entities with edges,have proven to be a powerful tool for describing real-world problems in *** most real-world scenarios,entities and their relationships are subject to constant *** that record such changes are called dynamic *** recent years,the widespread application scenarios of dynamic graphs have stimulated extensive research on dynamic graph processing systems that continuously ingest graph updates and produce up-to-date graph analytics *** the scale of dynamic graphs becomes larger,higher performance requirements are demanded to dynamic graph processing *** the massive parallel processing power and high memory bandwidth,GPUs become mainstream vehicles to accelerate dynamic graph processing ***-based dynamic graph processing systems mainly address two challenges:maintaining the graph data when updates occur(i.e.,graph updating)and producing analytics results in time(i.e.,graph computing).In this paper,we survey GPU-based dynamic graph processing systems and review their methods on addressing both graph updating and graph *** comprehensively discuss existing dynamic graph processing systems on GPUs,we first introduce the terminologies of dynamic graph processing and then develop a taxonomy to describe the methods employed for graph updating and graph *** addition,we discuss the challenges and future research directions of dynamic graph processing on GPUs.

关键词： dynamic graphs graph processing graph algorithms GPUs

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Leakage Location Method of Water Supply Pipe Network Based on Integrated Neural Network

Leakage Location Method of Water Supply Pipe Network Based o...

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2022 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers, IPEC 2022

作者： Wu, Xiaoxuan Zhang, Chen Hefei University School of Artificial Intelligence and Big Data Hefei230601 China Hefei University Anhui Engineering Lab of Big Data Technology Application for Urban Infrastructure Hefei230601 China

ISBN: (纸本)9781665409025

Concerning the problem that selecting the monitoring points and locating the leakage points accurate in the water supply network, a method of locating leakage points based on integrated neural network model is proposed. Based on the similarity of water supply pipe network node pressure, a fuzzy C-means clustering fusion algorithm (FCMCF) was used to select the limited monitoring points, instead of randomly selecting monitoring points;on this basis, according to the distribution structure of water supply pipe network, the hydraulic simulation was carried out by using EPANET pipe network adjustment software, and the water pressure of all nodes before and after leakage was obtained 24hours, the integrated neural network combining the convolutional neural network (CNN) and long and short time memory network (LSTM) was used to locate the leakage points of water supply pipe network. In the experimental part, the application of a model LangXi County Xuan City, an area of underground water supply pipe network leakage problem, through FCMCF selected five monitoring stations, using EPANET software simulate the 396 kinds of fault state, through the integrated neural network model training and testing, finally realizes the accurate positioning of the leak, model accuracy reached 90.25% and loss rate of the model is up to 20.24%. Compared with the empirical mode decomposition (EMD) combined with LSTM structure, the accuracy of the model is significantly improved, while the loss rate is significantly reduced. The experimental results show that the leakage location method of water supply pipe network based on integrated neural network can effectively solve the problem of actual leakage location. © 2022 IEEE.

关键词： Water supply

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Fan sound fault detection algorithm based on the fusion of convolutional neural network and gated recurrent unit network 6

Fan sound fault detection algorithm based on the fusion of c...

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6th International Conference on Advanced Electronic Materials, Computers, and Software engineering, AEMCSE 2023

作者： Qiu, Feng Chen, Shengbing Jin, Dou Lu, Anqi School of Artificial Intelligence and Big Data Hefei University Hefei230601 China Anhui Engineering Lab of Big Data Technology Application for Urban Infrastructure Hefei University Hefei230601 China

ISBN: (纸本)9781510668249

Fans are the important equipment in the manufacturing industry, which are easy to cause faults because of the complex working conditions and high speed. Various fault detection algorithms based on electrical, vibration and video have been proposed, but these algorithms are difficult to meet the detection requirements of enterprises. In this paper, a novel fan fault detection algorithm is presented based on sound signal detection technology. According to the different characteristics of the fan sound signal in the time and frequency domains, we combined the convolutional neural networks (CNN, which is sensitive to spatial information) and the gated recurrent unit (GRU, which is sensitive to timing information), and proposed a fan sound fault detection algorithm. Firstly, according to the variation characteristics of the acoustic signal in different states, the spectrogram of sound signal containing spatial and temporal characteristics is extracted, and the histogram equalization is used to enhance the spectrogram. On this basis, CNN and GRU are combined to train the Log-Fbank spectrogram respectively, so that it can better model the different characteristics of time domain and frequency domain information, so as to obtain a fan state model with high confidence and realize the sound fault detection of the fan. Experiments on MIMII dataset show that the algorithm has high fault recognition accuracy and fast convergence speed, which has good application value. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Fault detection

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ViGT: proposal-free video grounding with a learnable token in the transformer

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Science China(Information Sciences) 2023年第10期66卷 196-212页

作者： Kun LI Dan GUO Meng WANG School of Computer Science and Information Engineering Hefei University of Technology Key Laboratory of Knowledge Engineering with Big Data Ministry of Education Intelligent Interconnected Systems Laboratory of Anhui Province Institute of Artificial Intelligence Hefei Comprehensive National Science Center

The video grounding(VG) task aims to locate the queried action or event in an untrimmed video based on rich linguistic descriptions. Existing proposal-free methods are trapped in the complex interaction between video and query, overemphasizing cross-modal feature fusion and feature correlation for VG. In this paper, we propose a novel boundary regression paradigm that performs regression token learning in a transformer. Particularly, we present a simple but effective proposal-free framework, namely video grounding transformer(ViGT), which predicts the temporal boundary using a learnable regression token rather than multi-modal or cross-modal features. In ViGT, the benefits of a learnable token are manifested as follows.(1) The token is unrelated to the video or the query and avoids data bias toward the original video and query.(2) The token simultaneously performs global context aggregation from video and query ***, we employed a sharing feature encoder to project both video and query into a joint feature space before performing cross-modal co-attention(i.e., video-to-query attention and query-to-video attention) to highlight discriminative features in each modality. Furthermore, we concatenated a learnable regression token [REG] with the video and query features as the input of a vision-language transformer. Finally, we utilized the token [REG] to predict the target moment and visual features to constrain the foreground and background probabilities at each timestamp. The proposed ViGT performed well on three public datasets:ANet-Captions, TACoS, and YouCookⅡ. Extensive ablation studies and qualitative analysis further validated the interpretability of ViGT.

关键词： video grounding temporal sentence grounding boundary regression token learning proposal-free

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Long time-series modelling and analysis of lake expansion on the Qinghai Tibet Plateau using multi-source datasets

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Remote Sensing Letters 2025年第8期16卷 806-819页

作者： Zhang, Han-Su Mo, Yaoguang Zhong, Kaiwen Yao, Jiaqi Li, Zhichao Xu, Nan School of Artificial Intelligence and Information Technology Nanjing University of Chinese Medicine Nanjing China Chinese Academy of Science Guangzhou Institute of Geochemistry Guangzhou China College of Earth and Planetary Sciences University of Chinese Academy of Science Beijing China Guangdong Academy of Science Guangzhou Institute of Geography Guangdong Engineering Laboratory for Geographic Spatio-temporal Big Data Key Lab of Guangdong for Utilization of Remote Sensing & Geography Information System Guangzhou China Academy of Ecological Civilization Development for JING-JIN-JI Tianjin Normal University Tianjin China Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China College of Geography and Remote Sensing Hohai University Nanjing China Key Laboratory for Geo-Environmental Monitoring of Great Bay Area Ministry of Natural Resources & Guangdong Key Laboratory of Urban Informatics Shenzhen University Shenzhen China School of Architecture & Urban Planning Shenzhen University Shenzhen China

Lakes are a valuable natural resource that are sensitive to climate change. In recent years, global warming is ongoing, resulting in increased glacier melting and enhanced precipitation, leading to unprecedented lake expansion in the Qinghai-Tibet Plateau. This study aims to conduct modelling and monitoring of annual changes in lake areas, water levels, and storages for 108 representative expanding lakes on the Qinghai-Tibet plateau from 1999 to 2021. By leveraging Global Surface Water (GSW) data and Digital Elevation Model (DEM) derived from Shuttle Radar Topography Mission (SRTM), we estimated long-term annual lake areas and water levels for each lake. Our results have been validated by accurate Landsat-derived lake areas and satellite altimetry-derived water levels, demonstrating a high level of accuracy in our results. By modelling lake areas and water levels, we further estimated lake storage changes over the 1999–2021 period for these 108 typical lakes across the Qinghai-Tibet Plateau. This study provides detailed insights into the lake areas, water levels, and storages of 108 lakes in the Qinghai-Tibet Plateau, serving as a valuable reference for guiding regional sustainable development initiatives and policy-making efforts. © 2025 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Lakes

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In-situ synthesized SiC/TiC/SiTiOC hybrid nanofiber mats for broad-range temperature microwave absorption

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Science China Technological Sciences 2025年第06期 183-196页

作者： Yashan HUO Yuetong QIAN Minshan ZHAO Lei ZHANG Yujia TAN Zhihui HE Peng MIAO Fuchun ZHANG Wei CUI Renchao CHE School of Physics and Electronic Information Yan'an University Shaanxi Key Laboratory of Intelligent Processing for Big Energy Data Laboratory of Advanced Materials Shanghai Key Lab of Molecular Catalysis and Innovative Materials Academy for Engineering &Technology Advanced Coatings Research Center of Ministry of Education of China Fudan University School of Materials and Chemical Engineering Xi'an Technological University School of Materials Science & Engineering Tongji University College of Physics Donghua University

Efficient, temperature-insensitive electromagnetic attenuation materials are critical for high microwave absorption at high temperatures. This study presents SiC/TiC/SiTiOC hybrid nanofiber mats constructed using an in-situ synthesis method;these mats incorporate SiC/TiC as the microwave loss unit and SiTiOC as the antioxidant unit, offering an innovative approach to high-temperature microwave absorption. The introduction of high-conductivity TiC not only optimizes the dielectric constant and impedance matching of the material but also enhances its thermal cycling stability. This design ensures steady electromagnetic attenuation, enabling the hybrid nanofiber mats to maintain robust absorption performance in the X-band, even at high temperatures. At 873 K, the material demonstrates an effective absorption bandwidth of 3.6 GHz and a minimum reflection loss of-45.55 dB. Compared to single-system absorbers, such as SiC/C nanofiber materials, with a single system, the multicomponent SiC/TiC/SiTiOC hybrid nanofiber mats deliver reliable absorption performance in the temperature range of 293–873 K. This study confirms that highly conductive titanium-based ceramic materials used for dielectric property regulation effectively address the challenges of poor temperature stability and limited reusability in high-temperature carbon-ceramic absorbing materials, providing valuable insights and guidance for designing efficient microwave absorbers that can operate across a wide temperature range.

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ARCHER:a ReRAM-based accelerator for compressed recommendation systems

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Frontiers of Computer Science 2024年第5期18卷 147-160页

作者： Xinyang SHEN Xiaofei LIAO Long ZHENG Yu HUANG Dan CHEN Hai JIN National Engineering Research Center for Big Data Technology and System Services Computing Technology and System LabClusters and Grid Computing LabSchool of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China

Modern recommendation systems are widely used in modern data *** random and sparse embedding lookup operations are the main performance bottleneck for processing recommendation systems on traditional platforms as they induce abundant data movements between computing units and ***-based processing-in-memory(PIM)can resolve this problem by processing embedding vectors where they are ***,the embedding table can easily exceed the capacity limit of a monolithic ReRAM-based PIM chip,which induces off-chip accesses that may offset the PIM ***,we deploy the decomposed model on-chip and leverage the high computing efficiency of ReRAM to compensate for the decompression performance *** this paper,we propose ARCHER,a ReRAM-based PIM architecture that implements fully yon-chip recommendations under resource ***,we make a full analysis of the computation pattern and access pattern on the decomposed *** on the computation pattern,we unify the operations of each layer of the decomposed model in multiply-and-accumulate *** on the access observation,we propose a hierarchical mapping schema and a specialized hardware design to maximize resource *** the unified computation and mapping strategy,we can coordinatethe inter-processing elements *** evaluation shows that ARCHER outperforms the state-of-the-art GPU-based DLRM system,the state-of-the-art near-memory processing recommendation system RecNMP,and the ReRAM-based recommendation accelerator REREC by 15.79×,2.21×,and 1.21× in terms of performance and 56.06×,6.45×,and 1.71× in terms of energy savings,respectively.

关键词： recommendation system ReRAM processing-in-memory embedding layer

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Maximizing the effect of information adoption: A general framework

Maximizing the effect of information adoption: A general fra...

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2018 SIAM International Conference on data Mining, SDM 2018

作者： Jin, Tianyuan Xu, Tong Zhong, Hui Chen, Enhong Wang, Zhefeng Liu, Qi Anhui Province Key Lab of Big Data Analysis and Application University of Science and Technology of China China

With the development of social networking services, social influence analyses, as well as the influence maximization tasks, have attracted wide attention in both academia and industry. Traditional studies mainly focus on simulating process of influence spread. However, two basic functions of social spread, i.e., information propagation and information adoption have not been clearly distinguished. Usually, as information adoption could be even more significant for information publishers in application scenarios, more comprehensive analysis for effect of adoption is urgently required. To that end, in this paper, we propose a novel framework to generally describe social spread, in which information adoption process is separately formulated as random events. Along this line, when we apply this framework to the information adoption maximization task, with proving that the adoption maximization problem is NP-hard and submodular, we further design a polling-based algorithm to achieve an effective approximation. Extensive experiments on four real-world data sets demonstrate the effectiveness and efficiency of proposed algorithms, which validates that our approach could better summarize the complete social spread process, and further support the necessity of distinguishing information adoption from information propagation. © 2018 by SIAM.

关键词： data mining

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Judgment of blast furnace iron-tapping status based on data differential processing and dynamic window analysis algorithm

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Progress in Natural Science:Materials International 2023年第4期33卷 450-457页

作者： Youcheng Zong Zixian Wang Xiang Liu Yi Nian Jianian Pan Chaojie Zhang Yingxue Wang Jianhua Chu Liqiang Zhang The Intelligent Metallurgy Research Institute School of Metallurgical Engineering Anhui University of Technology Department of Technical Quality Manufacturing Management Division(Technical Center) Anhui Changjiang Steel Co. Ltd. National Engineering Research Center for Public Safety Risk Perception and Control by Big Data(RPP) China Academic of Electronics and Information Technology

Ironmaking plants hold a core position in steel production. Efficient level detection and iron-tapping status judgment can accurately measure the liquid level and predict the amount of molten iron in the ladle, thereby ensuring production safety and improving production efficiency. At present, the judgment of the start and end statuses of blast furnace iron-tapping mainly relies on manual visual inspection. However, due to the high-temperature environment on-site and interference from iron powder, gunning mud, and other dust, operators find it challenging to make accurate judgments. To address these issues, this study proposes a robust and accurate method for judging the iron-tapping status of blast furnaces. This study collected four million on-site liquid level data, underwent interpolation, noise reduction, normalization, and other preprocessing steps, and then used differential processing to calculate the iron-tapping rate. Combined with dynamic window feature analysis, it effectively captured the change characteristics of the liquid level in the ladle under different iron-tapping *** simulated on-site experiments, the method achieved a 96.6 % accuracy rate for iron-tapping status *** real-time iron-tapping status judgment method based on differential processing of liquid level data and dynamic window feature analysis proposed in this study demonstrates high precision and robustness in the complex environment of ironmaking plants. This technology not only improves the production efficiency of the iron and steel link but also frees on-site operators from the harsh working environment, eliminating human errors in judgments and omissions, further promoting the intelligent process of ironmaking plants.

关键词： Blast furnace iron-tapping Molten iron level Radar level gauge Iron-tapping status judgment data differential processing Sliding window

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The chinese postman problem based on molecular beacon strand displacement 14

The chinese postman problem based on molecular beacon strand...

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14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, ICNC-FSKD 2018

作者： Yang, Jing Huang, Kaifeng Yin, Zhixiang Cui, Jianzhong School of Mathematics and Big Data Anhui University of Science and Technology Anhui China School of Mechanical and Electrical Engineering Huainan Normal University Anhui China

ISBN: (纸本)9781538680971

With the help of the special structure of the molecular beacon, a solution model of the Chinese postman problem is established by using the DNA strand displacement reaction principle. First, the problem is mapped into an undirected weighting graph. Then the vertex and arc of the graph are coded according to the coding principle. Secondly, structure probe, and make use of stand displacement to find solutions to satisfy the problem. Finally, the optimum solution was extracted by gel electrophoresis. The model has high sensitivity, specificity, and the lower error rate. The solution reaction can be carried out at normal temperature. The model calculation shows that the complexity of the problem can be reduced by using the molecular beacon strand displacement reaction to solve the Chinese postman problem. © 2018 IEEE.

关键词： DNA

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