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HSCS:a hybrid shared cache scheduling scheme for multiprogrammed workloads

Frontiers of Computer Science 2018年第6期12卷 1090-1104页

作者： Jingyu ZHANG Chentao WU Dingyu YANG Yuanyi CHEN Xiaodong MENG Liting XU Minyi GUO Department of Computer Science and Engineering Shanghai Jiao Tong UniversityShanghai 200240China Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation School of Computer and Communication EngineeringChangsha University of Science and TechnologyChangsha 410004China School of Electronics and Information Shanghai Dianji UniversityShanghai 200240China

The traditional dynamic random-access memory (DRAM) storage medium can be integrated on chips via modern emerging 3D-stacking technology to architect a DRAM shared cache in multicore systems. Compared with static random-access memory (SRAM), DRAM is larger but slower. In the existing research, a lot of work has been devoted to improving the workload performance using SRAM and stacked DRAM together in shared cache systems, ranging from SRAM structure improvement to optimizing cache tags and data access. However, little attention has been paid to designing a shared cache scheduling scheme for multiprogrammed workloads with different memory footprints in multicore systems. Motivated by this, we propose a hybrid shared cache scheduling scheme that allows a multicore system to utilize SRAM and 3D-stacked DRAM efficiently, thus achieving better workload performance. This scheduling scheme employs (1) a cache monitor, which is used to collect cache statistics; (2) a cache evaluator, which is used to evaluate the cache information during the process of programs being executed; and (3) a cache switcher, which is used to self-adaptively choose SRAM or DRAM shared cache modules. A cache data migration policy is naturally developed to guarantee that the scheduling scheme works correctly. Extensive experiments are conducted to evaluate the workload performance of our proposed scheme. The experimental results showed that our method can improve the multiprogrammed workload performance by up to 25% compared with state-of-the-art methods (including conventional and DRAM cache systems).

关键词： multicore system shared cache workload performance

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Deep well construction of big data platform based on multi-source heterogeneous data fusion

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International Journal of Internet Manufacturing and Services 2019年第4期6卷 371-388页

作者： Zhang, Yu Wang, Yange Ding, Hongwei Li, Yongzhen Bai, Yanping School of Electrical and Information Engineering Beijing Key Laboratory of Intelligent Processing for Building Big Data Beijing University of Civil Engineering and Architecture No. 1 Zhanlanguan Road Xicheng District Beijing100044 China China University of Mining and Technology No. 16 Qinghua Road Haidian District Beijing100083 China School of Software Beijing University of Technology Beijing100124 China Network Information Center Beijing University of Civil Engineering and Architecture Beijing100044 China College of Management Capital Normal University Beijing100048 China

At present, energy saving and emission reduction had become a problem of great concern for mankind. At the same time, there were some problems in the mining industry, such as waste of resources, low efficiency and easy occurrence of industrial accidents. Therefore, this paper had designed a deep well construction big data platform. The high precision and bear great pressure sensors were added to the system to solve the difficult problem of collecting information in deep wells by ordinary sensors. The multi-source heterogeneous data fusion algorithm was added to the system to solve the problem that the format of the data acquisition was different. In conclusion, the completion of the platform could achieve data monitoring in the process of mines. It not only helps to enhance the safety of mine construction, but also provides data analytical tools for further theoretical research of mine construction. © 2019 Inderscience Enterprises Ltd.

关键词： big data

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Strong convergence of an extragradient algorithm for variational inequality and fixed point problems

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UPB Scientific Bulletin, Series A: Applied Mathematics and Physics 2020年第1期82卷 3-12页

作者： Yao, Yonghong Postolache, Mihai Yao, Jen-Chih School of Mathematical Sciences Tianjin Polytechnic University Tianjin300387 China The Key Laboratory of Intelligent Information and Big Data Processing of NingXia Province North Minzu University Yinchuan750021 China China Medical University Taichung40402 Taiwan Romanian Academy Institute of Mathematical Statistics and Applied Mathematics Bucharest050711 Romania University "Politehnica" of Bucharest Bucharest060042 Romania Center for General Education China Medical University Taichung Taiwan

In this paper, we consider the fixed point and variational inequality problems in Hilbert spaces. We suggest an extragradient algorithm for finding a common element of the set of fixed points of a pseudocontractive operator and the set of solutions of the variational inequality problem. Strong convergence of the proposed algorithm is proved. © 2020, Politechnica University of Bucharest. All rights reserved.

关键词： Variational techniques

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Web Intelligence (WI) 3.0: in search of a better-connected world to create a future intelligent society

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Artificial Intelligence Review 2025年第9期58卷

作者： Kuai, Hongzhi Huang, Jimmy X. Tao, Xiaohui Pasi, Gabriella Yao, Yiyu Liu, Jiming Zhong, Ning School of Computer Science and Technology/School of Artificial Intelligence Chongqing University of Posts and Telecommunications Chongqing China Key Laboratory of Big Data Intelligent Computing Chongqing University of Posts and Telecommunications Chongqing China School of Information Technology York University North YorkON Canada School of Mathematics Physics and Computing University of Southern Queensland ToowoombaQLD Australia Department of Informatics Systems and Communication University of Milano-Bicocca Milano Italy Department of Computer Science University of Regina Regina Canada Department of Computer Science Hong Kong Baptist University Kowloon Tong Hong Kong Faculty of Engineering Maebashi Institute of Technology Gunma Maebashi Japan

Over the past two decades, Web Intelligence (WI) has emerged as a key field driving the evolution of AI in the connected world, addressing the demands of a future intelligent society. This paper provides a comprehensive review of WI’s contributions since its inception in 2000, spanning three distinct phases: Wisdom World Wide Web (WI 1.0, 2000–2009), Wisdom Web of Things (WI 2.0, 2010–2017), and Wisdom Web of Everything (WI 3.0, since 2018). For each phase, we examine key advancements, challenges, and future directions from the perspectives of both intelligent machines and human experts, highlighting significant societal impacts. To advance WI research, we propose a large language model-based learning framework for topic analysis and trend prediction. Moving beyond single-perspective approaches, we emphasize the Connected Intelligence Ecosystem defined by the HIGH5 scheme comprising one goal, two twins, three fundamentals, four functions, and five services that are realized through WI 3.0. This vision serves as a bridge from localized models to a global reference framework for addressing sustainability challenges in future societies. To illustrate the real-world implications of WI 3.0, we present case studies focusing on brain-inspired research, particularly in the intersection of brain intelligence, brain health, and brainternet-fostering interdisciplinary collaboration across diverse research communities. © The Author(s) 2025.

关键词： intelligent computing

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FW-GAN: Flow-Navigated Warping GAN for Video Virtual Try-On

FW-GAN: Flow-Navigated Warping GAN for Video Virtual Try-On

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International Conference on Computer Vision (ICCV)

作者： Haoye Dong Xiaodan Liang Xiaohui Shen Bowen Wu Bing-Cheng Chen Jian Yin School of Data and Computer Science Sun Yat-sen University Guangdong Key Laboratory of Big Data Analysis and Processing Guangzhou P.R.China School of Intelligent Systems Engineering Sun Yat-sen University ByteDance AI Lab

ISBN: (数字)9781728148038

ISBN: (纸本)9781728148045

Beyond current image-based virtual try-on systems that have attracted increasing attention, we move a step forward to developing a video virtual try-on system that precisely transfers clothes onto the person and generates visually realistic videos conditioned on arbitrary poses. Besides the challenges in image-based virtual try-on (e.g., clothes fidelity, image synthesis), video virtual try-on further requires spatiotemporal consistency. Directly adopting existing image-based approaches often fails to generate coherent video with natural and realistic textures. In this work, we propose Flow-navigated Warping Generative Adversarial Network (FW-GAN), a novel framework that learns to synthesize the video of virtual try-on based on a person image, the desired clothes image, and a series of target poses. FW-GAN aims to synthesize the coherent and natural video while manipulating the pose and clothes. It consists of: (i) a flow-guided fusion module that warps the past frames to assist synthesis, which is also adopted in the discriminator to help enhance the coherence and quality of the synthesized video; (ii) a warping net that is designed to warp clothes image for the refinement of clothes textures; (iii) a parsing constraint loss that alleviates the problem caused by the misalignment of segmentation maps from images with different poses and various clothes. Experiments on our newly collected dataset show that FW-GAN can synthesize high-quality video of virtual try-on and significantly outperforms other methods both qualitatively and quantitatively.

关键词： Integrated circuits Generators Gallium nitride Three-dimensional displays Image generation Computational modeling Visualization

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A new runoff calculation model based on multi-source radar remote sensing technology 6

A new runoff calculation model based on multi-source radar r...

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6th Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2019

作者： Zhao, Jianhui Wang, Ning Wu, Lin Min, Lin College of Computer and Information Engineering Henan University Kaifeng475004 China College of Environment and Planning Henan University Kaifeng475004 China Network Information Center Office Henan University Kaifeng475004 China Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng475004 China Henan Engineering Research Center of Intelligent Technology and Application Kaifeng475004 China

ISBN: (纸本)9781728129129

River runoff changing will directly affect the safety of the surrounding areas. In theory, river runoff can be calculated from water depth, river width and flow velocity. But in the actual monitoring, the observation of water depth, river width and flow velocity is complex. Radar remote sensing can observe target all-time and all-weather, and has the ability to penetrate clouds, rain and fog. The common Radar remote sensing runoff calculation model is depth-runoff relationship model, which is constructed by fitting water depth and in-situ runoff. The river depth is derived from Radar Altimetry (RA) data. But this model has only one input parameter, the accuracy of this model inverted runoff is not high. In view of the above problems, this paper proposed the Multi-source Radar Remote Sensing Runoff Calculation Model (MRRS-RCM). Firstly, river width and relative water depth were derived from Synthetic Aperture Radar (SAR) images and RA data. Secondly, based on the Manning's equation, the flow velocity were described from river width and relative water depth. Thirdly, river width relative water depth, and in-situ runoff were fitted to construct MRRS-RCM. Experiments show the accuracy of MRRS-RCM estimated runoff is better than depth-runoff relationship model, the RRMSE values of MRRS-RCM reach 13%. © 2019 IEEE.

关键词： Synthetic aperture radar

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Investigation of the Salinity Distribution of the Soil along West Main Canal in Ningxia, China

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IOP Conference Series: Earth and Environmental Science 2021年第1期697卷

作者： Juntao Wu Hefang Jing Weihong Wang Xiaoxiao Guo Xinxia Guo Research Institute of Numerical Computation and Engineering Applications North Minzu University Yinchuan China School of Mathematics and Information Science North Minzu University Yinchuan China The Key Laboratory of Intelligent Information and Big Data Processing of Ningxia Province North Minzu University Yinchuan China

As one of the main irrigation canals in Ningxia, West Main Canal plays a very important role in the irrigation of the land nearby the canal, such as farms, meadows, and tree farms. Because of the long-term use of the Yellow River water for irrigation, the soil salinization in this area become more serious. In this paper, the problem of soil salinization along the West Main Canal in Ningxia is taken as the research object. 82 sample points in the studied area are chosen and a total number of 164 soil samples are measured for the eight main salt ions and pH value. Correlation analysis and principal component analysis are employed to study the distribution of the soil salinity ions and pH value. In addition, two dimensional interpolation is applied to obtain the spatial distribution of the total saltiness. It can be found that Cl−, SO42−, Ca2+, Na+ and HCO3− are the main salt ions and the main soluble salts are NaCl, KCl, CaSO4, Na2SO4 and CaCl2 in the soil of the studied area. The spatial distribution of the total soil salt is mainly in the patterns of north high and south low, far high and near low, up high and down low.

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Experimental Study on Flow Characteristics in a Compound Open Channel with Flexible Vegetation

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IOP Conference Series: Earth and Environmental Science 2021年第1期697卷

作者： Xiaoxiao Guo Hefang Jing Weihong Wang Juntao Wu Qiaoling Zhang Research Institute of Numerical Computation and Engineering Applications North Minzu University Yinchuan China School of Mathematics and Information Science North Minzu University Yinchuan China The Key Laboratory of Intelligent Information and Big Data Processing of Ningxia Province North Minzu University Yinchuan China

In order to study the effect of flexible vegetation for the flow in open channels with flood plains, a series of experiments were carried out in a laboratory flume with a two-stage floodplain. Four cases, i.e., dense parallel arrangement, normal parallel arrangement, sparse parallel arrangement and no vegetation condition, were designed with fixed water depth and discharge. By using three dimensional (3D) laser Doppler velocimeter (LDV) and other instruments, under the condition of the four cases,3D flow velocities, water level and turbulence intensity were measured, The experimental results show that, compared with the non-vegetation situation, the arrangement of grasses on the floodplain will increase the water surface gradient, hydraulic gradient and turbulence intensity to a certain extent.

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Impact of DG on short circuit current detected by protection

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IOP Conference Series: Earth and Environmental Science 2021年第1期675卷

作者： Jing Gong School of Electrical and Information Engineering Beijing University of Civil Engineering and Architecture Beijing 100044 China Beijing Key Laboratory of Intelligent Processing for Building Big Data Beijing 100044 China National Virtual Simulation Experimental Center for Smart City Education Beijing100044 China

DG (distributed generation) access causes the change of current detected by the protection, and then affects the sensitivity of the original protection. In order to solve the problem, the influences of DG capacity, DG access location and short-circuit location on short circuit current are analysed in this paper. When the DG capacity and grid-connected position remain unchanged, the unit current method is used to solve the short-circuit current by solving the transfer impedance. The relationship between the change of short circuit position and the impact degree of DG is discussed in detail, and the calculation formula of extreme point is derived. When the DG capacity and short circuit location remain unchanged, the impact of DG grid-connected position on the upstream and downstream current is analysed. The characteristic curve of the impact of DG position change on protection current detection is given, and the impact of DG grid-connected position on protection sensitivity is explained clearly. The conclusion provides an important reference for the selection of DG grid-connected position and the calculation of relay protection in distribution network with DG.

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Deep representation learning for road detection using siamese network

arXiv

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arXiv 2019年

作者： Liu, Huafeng Han, Xiaofeng Li, Xiangrui Yao, Yazhou Huang, Pu Tang, Zhenming School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing210094 China Jiangsu Key Laboratory of Big Data Security & Intelligent Processing Nanjing University of Posts and Telecommunications Nanjing210023 China

Robust road detection is a key challenge in safe autonomous driving. Recently, with the rapid development of 3D sensors, more and more researchers are trying to fuse information across different sensors to improve the performance of road detection. Although many successful works have been achieved in this field, methods for data fusion under deep learning framework is still an open problem. In this paper, we propose a Siamese deep neural network based on FCN-8s to detect road region. Our method uses data collected from a monocular color camera and a Velodyne-64 LiDAR sensor. We project the LiDAR point clouds onto the image plane to generate LiDAR images and feed them into one of the branches of the network. The RGB images are fed into another branch of our proposed network. The feature maps that these two branches extract in multiple scales are fused before each pooling layer, via padding additional fusion layers. Extensive experimental results on public dataset KITTI ROAD demonstrate the effectiveness of our proposed approach. Copyright © 2019, The Authors. All rights reserved.

关键词： Roads and streets

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