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检索条件"机构=State Key Lab. of Computer Science Inst. of Software"

共 394 条记录，以下是131-140 订阅

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Unleashing the performance potential of CPU-GPU platforms for the 3D atmospheric Euler solver

Unleashing the performance potential of CPU-GPU platforms fo...

引用

International Conference on Application Specific Systems (ASAP), Architectures and Processors

作者： Haohuan Fu Jingheng Xu Lin Gan Chao Yang Wei Xue Wenlai Zhao Wen Shi Xinliang Wang Guangwen Yang National Supercomputing Center in Wuxi Ministry of Education Key Lab. for Earth System Modeling Center for Earth System Science Tsinghua University Department of Computer Science & Technology Tsinghua University Institute of Software and State Key Laboratory of Computer Science Chinese Academy of Sciences Tsinghua University Beijing Beijing CN

ISBN: (纸本)9781509015047

As a traditional application on various supercomputers, atmospheric modeling has long been suffering from the low performance efficiency. In this paper, we pick the 3D Euler equation solver (the most essential dynamic component for a non-hydrostatic atmospheric model) as the target application, and explore the maximum performance efficiency that can be achieved on CPU-GPU hybrid architectures. Besides presenting the suitable hybrid domain decomposition methodology and taking proper usage of tuning techniques for both the CPU and GPU parts, we further propose a novel GPU tuning technique, namely the customizable data caching mechanism with thread warp rescheduling scheme, which is specifically designed for the Euler solver. Combining all the optimizing approaches together, remarkable performance boost has been achieved on mainst.eam GPU architectures including Tesla Fermi C2050, K20×, K40 and K80. Especially, on the latest Tesla K80, we demonstrate a 31.64× speedup over the performance of 12-core E5-2697 CPU. In addition, based on a hybrid CPU-GPU node with two 12-core E5-2697 CPUs and two Tesla K80 GPUs, a sustained double-precision performance of 1.04 Tflops (16% of the peak) is achieved, which is remarkably higher than the efficiency of similar optimizing tasks based on heterogeneous platforms (strictly less than 10%, as demonstrated in the related work). In addition, a nearly linear weak scaling efficiency is achieved which demonstrate the effectiveness of our domain decomposition method.

关键词： Atmospheric modeling Graphics processing units Mathematical model Computational modeling computer architecture Tuning Three-dimensional displays

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Modeling and evaluating IaaS cloud using performance evaluation process algebra

Modeling and evaluating IaaS cloud using performance evaluat...

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Asia-Pacific Conference on Communications

作者： Jie Ding Leijie Sha Xiao Chen State Key Lab. for Novel Software Technology Nanjing University Nanjing China School of Information Engineering Yangzhou University Yangzhou China School of Computer Science and Telecommunication Engineering Jiangsu University Zheniian China

ISBN: (纸本)9781509006779

Infrastructure as a Service (IaaS) is a service mode of cloud, which provides Virtual Machines (VMs) to customers. With the increasingly fierce competition in market, cloud providers pay more attention to Quality of service (Qos). As the practical measurement costs a large amount of resource, deriving performance metrics from analytical model is a good choice. Recently, Stochastic Petri Net (SPN) has been used to construct analytical models, but they lack the ability to exhibit hierarchies of IaaS cloud. Compare to SPN, Performance Evaluation Process Algebra (PEPA) has the feature of compositionality, which imports the hierarchial strategy into the semantics. So, PEPA models of IaaS cloud are closed to actual architecture and can be more easily accepted by engineers. This paper provides a PEPA model of IaaS cloud and gives some numerical results.

关键词： Mathematical model Cloud computing Analytical models Switches Numerical models Performance evaluation

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Handling motion blur in multi-frame super-resolution

Handling motion blur in multi-frame super-resolution

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IEEE Conference on computer Vision and Pattern Recognition, CVPR 2015

作者： Ma, Ziyang Liao, Renjie Tao, Xin Xu, Li Jia, Jiaya Wu, Enhua University of Chinese Academy of Sciences State Key Lab. of Computer Science Inst. of Software CAS China Chinese University of Hong Kong Hong Kong Hong Kong FST University of Macau China

ISBN: (纸本)9781467369640

Ubiquitous motion blur easily fails multi-frame super-resolution (MFSR). Our method proposed in this paper tackles this issue by optimally searching least blurred pixels in MFSR. An EM framework is proposed to guide residual blur estimation and high-resolution image reconstruction. To suppress noise, we employ a family of sparse penalties as natural image priors, along with an effective solver. Theoretical analysis is performed on how and when our method works. The relationship between estimation errors of motion blur and the quality of input images is discussed. Our method produces sharp and higher-resolution results given input of challenging low-resolution noisy and blurred sequences. © 2015 IEEE.

关键词： Optical resolving power

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ADAPTIVE MULTI-TASK LEARNING FOR FINE-GRAINED CATEGORIZATION

ADAPTIVE MULTI-TASK LEARNING FOR FINE-GRAINED CATEGORIZATION

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IEEE International Conference on Image Processing

作者： Gang Sun Yanyun Chen Xuehui Liu Enhua Wu State Key Lab. of Computer Science Inst. of Software Chinese Academy of Sciences

ISBN: (纸本)9781479983407

Multi-task learning has been proposed to improve the generalization performance by learning multiple tasks jointly. One challenge for this learning paradigm is to effectively seek the shared information across multiple tasks. In this paper, we propose a novel multi-task learning method to adaptively share information. Unlike many existing multi-task learning methods which impose strong assumptions on task relatedness, our method captures the relationships among tasks and identifies the disparities of each task simultaneously, thus can flexibly exploit the shared information. Moreover, we apply it to fine-grained categorization problem, which usually suffers from the difficulties of insufficient training data and high inter-class similarity. The experimental results on two widely used datasets show the superiority of our method compared with some state-of-the-art methods.

关键词： Multi-task learning Fine-grained Image categorization Low-rank Learning methods Religious Missions Learning microparticles PARALLEL PROCESSING (computerS) WWOX gene

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A simple probabilistic extension of modal Mu-calculus 24

A simple probabilistic extension of modal Mu-calculus

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24th International Joint Conference on Artificial Intelligence, IJCAI 2015

作者： Liu, Wanwei Song, Lei Wang, Ji Zhang, Lijun School of Computer Science National University of Defense Technology Changsha China University of Technology Sydney Australia State Key Lab. of HPC National University of Defense Technology Changsha China State Key Lab. of Computer Science Institute of Software CAS Beijing China

ISBN: (纸本)9781577357384

Probabilistic systems are an important theme in AI domain. As the specification language, PCTL is the most frequently used logic for reasoning about probabilistic properties. In this paper, we present a natural and succinct probabilistic extension of μ-calculus, another prominent logic in the concurrency theory. We study the relationship with PCTL. Surprisingly, the expressiveness is highly orthogonal with PCTL. The proposed logic captures some useful properties which cannot be expressed in PCTL. We investigate the model checking and satisfiability problem, and show that the model checking problem is in UP ∩co-UP, and the satisfiability checking can be decided via reducing into solving parity games. This is in contrast to PCTL as well, whose satisfiability checking is still an open problem.

关键词： Specification languages

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Personalized location recommendation by aggregating multiple recommenders in diversity

Personalized location recommendation by aggregating multiple...

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Workshop on Location-Aware Recommendations, LocalRec 2015 - co-located with the 9th ACM Conference on Recommender Systems, RecSys 2015

作者： Lu, Ziyu Wang, Hao Mamoulis, Nikos Tu, Wenting Cheung, David W. Dept. of Computer Science Univ. of Hong Kong Hong Kong State Key Lab. for Novel Software Technology Nanjing University China

Location recommendation is an important feature of social network applications and location-based services. Most existing studies focus on developing one single method or model for all users. By analyzing real location-based social networks, in this paper we reveal that the decisions of users on place visits depend on multiple factors, and different users may be affected differently by these factors. We design a location recommendation framework that combines results from various recommenders that consider various factors. Our framework estimates, for each individual user, the underlying influence of each factor to her. Based on the estimation, we aggregate suggestions from different recommenders to derive personalized recommendations. Experiments on Foursquare and Gowalla show that our proposed method outperforms the state-of the-art methods on location recommendation.

关键词： Location

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Research on adaptation criteria generation based on large data mining

Research on adaptation criteria generation based on large da...

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IEEE Chinese Guidance, Navigation and Control Conference (CGNCC)

作者： Hong-Quan Yun Li Xu Hao Dou De-Lie Ming National Key Laboratory of Science and Technology on Aerospace Intelligence Control Beijing Aerospace Automatic Control Institute China Nat. Key Lab. of Sci. & Technol. on Aerosp. Intell. Control Beijing Aerosp. Autom. Control Inst. China State Key Lab. for Multi-spectral Inf. Process. Technol. Huazhong University of Science and Technology Wuhan Hubei CN

ISBN: (纸本)9781467383196

This paper performs research on adaptation analysis based on large amount of multi-source remote sensing data. In view of different demands from different task background, the research is firstly focused on how to analyze the data in computer language. To achieve this, the feature parameters of target areas are extracted from different target area geographic data. In combination of ORACLE database engine, data mining technology is used to carry out the target area adaptation assessment, and extract corresponding adaptation criteria. We test the trained adaptation criteria on multi-source geographic information data of different target areas. Experimental results show that the resulting criterion has certain coincidence rate and robustness.

关键词： Image edge detection Decision trees Stability criteria Pattern matching Guidelines Real-time systems

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Adaptive level set for fluid surface tracking 15

Adaptive level set for fluid surface tracking

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21st ACM Symposium on Virtual Reality software and Technology, VRST 2015

作者： Li, Xiaosheng Sun, Hanqiu Liu, Xuehui Wu, Enhua State Key Lab. of Computer Science Institute of Software Chinese Academy of Sciences China Department of Computer Science and Engineering Chinese University of Hong Kong Hong Kong Faculty of Science and Technology University of Macau China University of Chinese Academy of Sciences China

ISBN: (纸本)9781450339902

We introduce an adaptive hybrid level set surface tracking for fluid simulation in this paper. To improve the accuracy of the convectional level set method, we propose a method that combines the higher accuracy interpolation and octree grid to improve the accuracy while still maintain good efficiency. Adaptive gradient-augmented level set is adopted for higher accuracy interpolation and two strategies are proposed to guide the building of the octree structure. We demonstrate our method with several level set tests, and couple it to several existing fluid simulators. The results show that our method facilitates significant improvements in accuracy and efficiency, and is effective for free surface fluid simulation in capturing fluid details. © 2015 ACM.

关键词： Interpolation

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Social sensing enhanced time estimation for bus service

Social sensing enhanced time estimation for bus service

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作者： Liu, Jin Li, Juan Cui, Xiaohui Niu, Xiaoguang Sun, Xiaoping Zhou, Jing State Key Lab. of Software Engineering Computer School Wuhan University Wuhan China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology Guilin China International School of Software Wuhan University Wuhan China Computer School Wuhan University Wuhan China Key Lab of Intelligent Information Processing Institute of Computing Technology CAS Beijing China School of Computer Science Communication University of China China

The precise prediction of bus routes or the arrival time of buses for a traveler can enhance the quality of bus service. However, many social factors influence people's preferences for taking buses. These social factors may include heavy traffic cost, traffic congestion, poor air quality and so forth. Existing prediction techniques rarely consider social sensing when predicting the bus arrival time. Accordingly, this paper proposes a social sensing enhanced service for predicting bus routes, which integrates sensing ability and social networks to understand and measure the influence between social events and vehicle velocity. We focus on the analysis of two different attributions: PT service quality attributions PEAs and road condition attributions PRCAs. Both of them synthesize the social sensing in their evaluation of bus routes. PEA represents individual preferences and PRCA represents physical factors that significantly influence vehicle velocity. Bus relevant social events were further categorized into PEA events or PRCA events. PEAs of buses were scored according to the tendency of bus conditions reflected in social events. Furthermore, an artificial neural network prediction model is established to estimate the bus travel time. © 2015 John Wiley & Sons, Ltd.

关键词： Buses

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Battery capacity anomaly detection and data fusion

Battery capacity anomaly detection and data fusion

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2015 Annual Conference of the Prognostics and Health Management Society, PHM 2015

作者： Weddington, John Yan, Wuzhao Dou, Wanchun Zhang, Bin Department of Electrical Engineering University of South Carolina ColumbiaSC United States Department of Computer Science and Technology State Key Lab. for Novel Software Technology Nanjing University NanjingJiangsu210093 China

ISBN: (纸本)9781936263202

Anomaly detection is a critical enabling technique of PHM, especially in safety critical applications. In order for the PHM system to begin prediction of remaining useful life of a given system or component, the fault must be detected. This paper presents an integrated anomaly detection system for state-of-health of lithium-ion batteries. Two algorithms for state estimation and anomaly detection are used: the extended Kalman filter and the particle filter. A Dempster-Shafer Theory-based fusion approach is implemented to reduce the uncertainty of detection. The results on battery data show that the fusion improves the detection results significantly. © 2015, Prognostics and Health Management Society. All rights reserved.

关键词： Kalman filters

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