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检索条件"任意字段=Conference on High Performance Computer Modernization Program"

共 10394 条记录，以下是4341-4350 订阅

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Navigating a Shortest Path with high Probability in Massive Complex Networks 1

引用

conference on Analysis of Experimental Algorithms (SEA2)

作者： Liu, Jun Pan, Yicheng Hu, Qifu Li, Angsheng Chinese Acad Sci Inst Software State Key Lab Comp Sci Beijing Peoples R China Univ Chinese Acad Sci Beijing Peoples R China Beihang Univ State Key Lab Software Dev Environm Beijing Peoples R China

ISBN: (数字)9783030340292

ISBN: (纸本)9783030340292;9783030340285

In this paper, we study the problem of point-to-point shortest path query in massive complex networks. Nowadays a breadth first search in a network containing millions of vertices may cost a few seconds and it can not meet the demands of real-time applications. Some existing landmark-based methods have been proposed to solve this problem in sacrifice of precision. However, their query precision and efficiency is not high enough. We first present a notion of navigator, which is a data structure constructed from the input network. Then navigation algorithm based on the navigator is proposed to solve this problem. It effectively navigates a path only using local information of each vertex by interacting with navigator. We conduct extensive experiments in massive real-world networks containing hundreds of millions of vertices. The results demonstrate the efficiency of our methods. Compared with previous methods, ours can navigate a shortest path with higher probability in less time.

关键词： Navigation Shortest path Massive networks

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Miniaturized and high Precision Monitoring System for Natural Waters Using a Microflow Analyzer 17

Miniaturized and High Precision Monitoring System for Natura...

引用

17th IEEE International conference on IC Design and Technology (ICICDT)

作者： Ren, Lin-Lin Ren, Jun Jin, Fu-Hua Jiang, Tian-Yu Fu, Jun Yang, Yi Ren, Tian-Ling Tsinghua Univ Inst Microelect Beijing 100084 Peoples R China Tsinghua Univ Beijing Natl Lab Informat Sci & Technol Beijing 100084 Peoples R China Tsinghua Univ Dept Elect Engn Beijing 100084 Peoples R China

ISBN: (纸本)9781728118536

In this work, we fabricated a miniaturized water quality monitoring system with microfluidic analysis chip to meet the high density and network requirements of wide area water system monitoring. The framework of the system is a layered tower structure, including human-computer interaction module, micro-control module, microfluidic chip and master control module. The miniaturized water quality monitoring system optimizes the integration of microfluidic technology and absorption photometric detection methods, and the design of the micro control system ensures automatic analysis of water quality. Experiments show that the system has excellent detection performance while achieving miniaturization. The detection limit (LOD) of the miniatured analyzer was 3.4 mu M, and the reaction time was between 100 s and 300 s. The reagent consumption is only 6 mu L per sample.

关键词： Microflow loop analyzers Micro system Water quality monitorin Absorbance photometre

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Online Prediction of Server Crash Based on Running Data

Online Prediction of Server Crash Based on Running Data

引用

IEEE International conference on Software Quality, Reliability and Security Companion (QRS-C)

作者： Zhuoliang Zou Jun Ai School of Reliability and Systems Engineering Beihang University Beijing China

ISBN: (数字)9781728189154

ISBN: (纸本)9781728189161

For web servers, the most typical and common failure is that the client's web page requests surge in a certain period of time, resulting in the server's collapse under extreme pressure. The early warning of server crash time provides the possibility to avoid crash loss. In this paper, we propose an early-warning method for Web service failure. Firstly, we obtain the key nodes on the running path of the server, collect and analyze the running status data of the path under various pressures through program instrumentation, and inform the occurrence of failure in advance through LSTM-SVM (the algorithm combining SVM and LSTM). We apply this method to Nginx, a widely used server, and the accuracy of crash warning is over 95%. Experiments show that the method of acquiring target data has little effect on the performance of server, achieves high degree of automation, and realizes high-precision fault warning. The innovation of this paper is that we realize the fault warning through the change of the parameters in the software.

关键词： Support vector machines Technological innovation Automation Instruments computer crashes Software reliability Servers

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Efficient Gene Assembly and Identification for Many Genome Samples 1

引用

3rd International conference on Cognitive Computing (ICCC) Held as Part of the Services conference Federation (SCF)

作者： Xu, Ruifeng Guo, Ning Saravanan, Konda Mani Wei, Yanjie Chinese Acad Sci Shenzhen Inst Adv Technol Ctr High Performance Comp Joint Engn Res Ctr Hlth Big Data Intelligent Anal Shenzhen 518055 Guangdong Peoples R China Univ Chinese Acad Sci 19A Yuquan Rd Beijing 100049 Peoples R China

ISBN: (数字)9783030234072

ISBN: (纸本)9783030234072;9783030234065

The development of the next generation sequencing technology (NGS) has advanced the genomics research in many application domains. Metagenomics is one such powerful approach to study large community of microbial species. For the unknown species in the metagenomic samples, gene assembly and identification without a reference genome is a very challenging problem. To overcome this issue, distributed gene assembly software handling multiple metagenome samples can be used. In this paper, based on our previously developed highly scalable gene assembly software SWAP, we present a work flow called WFswap to assemble large genomic data based on many samples and to identify more genes. Our results suggested that WFswap is able to identify 94.2% of the bench-mark genes when tested on the 19 metagenomic samples that contain Bifidobacterium animalis subsp. lactis CNCM I-2494. Our proposed work-flow WFswap showed better performance than WFsoap, a similar workflow that used SOAPdenovo2 for gene assembly.

关键词： Metagenomics Gene assembly Gene prediction NGS

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Message from the program Chairs

Message from the Program Chairs

引用

IEEE Symposium on high-performance computer Architecture

Presents the introductory welcome message from the conference proceedings. May include the conference officers' congratulations to all involved with the conference event and publication of the proceedings record.

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Investigating the Utility of Perturbation and Observation, Incremental Conductance and Grey-Wolf MPPT Techniques for ON-Grid PV System Under Fluctuated Environmental Conditions

Investigating the Utility of Perturbation and Observation, I...

引用

National Proceedings Power and Energy conference (PECon)

作者： Mohamed A. Khafagy Merna M. Eshak Peter Makeen Sameh O. Abdellatif Hani A. Ghali MSc. Student in Renewable Energy Program Faculty of Engineering The British University of Egypt (BUE) Cairo Egypt Faculty of Engineering and FAbLab in the Center for Emerging Learning Technology(CELT) The British University in Egypt (BUE) Cairo Egypt Faculty of Engineering and Wind Tunnel Lab at the Center for Emerging Learning Technology(CELT) The British University in Egypt (BUE) Cairo Egypt Faculty of Engineering and the Center for Emerging Learning Technology(CELT) The British University in Egypt (BUE) Cairo Egypt

ISBN: (数字)9781728170688

ISBN: (纸本)9781728170695

This paper investigates the performance of the ON-Grid solar PV system using three different Maximum Power Point Tracking (MPPT) techniques (Perturbation and Observation (P&O), Incremental Conductance (I.C.) and Grey-Wolf technique). The performance of the MPPT techniques has been scrutinized while the change in the external environment such as partial shading conditions and the variation of the temperature has been applied. The purpose of this research is regulating the output voltage and output power with a very high-speed response. A comparison between the proposed MPPT techniques has been discussed and it is concluded that the Grey-Wolf MPPT technique ensures a reduction in the time response by 96% and 71.4% corresponding to the I.C. and P&O techniques respectively. All the simulations have been implemented through the MATLAB/Simulink computer program.

关键词： Sun Power generation Maximum power point trackers Voltage control Electrical engineering conferences Perturbation methods

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A Push/Pull-Based System Scheduling Framework for Large-Scale Cluster

A Push/Pull-Based System Scheduling Framework for Large-Scal...

引用

International conference on Big Data and Information Analytics (BigDIA)

作者： Bo Wang Zhiguang Chen Nong Xiao College of Computer National University of Defense Technology Changsha China School of Data and Computer Science Sun Yat-Sen University Guangzhou China

ISBN: (数字)9781665422321

ISBN: (纸本)9781665446662

The integration of high-performance computing jobs and big data processing jobs has developed into a significant trend in the industry. Since distributed big data clusters are slightly inferior to supercomputers in terms of performance, more and more big data jobs are operated on supercomputers, such as Tianhe-2. These two types of jobs have different characteristics and resource requirements, which makes it difficult for the job scheduler currently used in supercomputers to make a perfect connection between jobs and resources. To this end, this paper proposes a resource scheduling framework based on the combination of Push and Pull. According to the node resource usage and job resource request amount, two different scheduling strategies, Push or Pull, can be implemented for the job. Among them, Push means that the management node dispatches a task to the work node, and Pull means that the work node applies to the management node a task to execute. According to the experiments, compared to the Push-based scheduling mode, our Push/Pull-based scheduling mode has about 3 times the job throughput without affecting the scalability and increases the resource utilization 20.4%.

关键词： Job shop scheduling Processor scheduling Scalability Big Data Throughput Supercomputers Task analysis

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Towards high Energy Efficiency Contact Plan Design in Collaborative Data Offloading in Space Information Network 10th

Towards High Energy Efficiency Contact Plan Design in Collab...

引用

10th European-Alliance-for-Innovation (EAI) International conference on Wireless and Satellite Systems (WiSATS)

作者： Liu, Xianfeng Yang, Lei Fan, Chengguang Wu, Shuai Guo, Jianming Chen, Quan Natl Univ Def Technol Coll Aerosp Sci & Engn Changsha 410073 Peoples R China

ISBN: (纸本)9783030191535;9783030191528

Space information network (SIN) consisting of communication satellites plays an important role in information acquisition and transmission. An increasing volume of data produced by different space missions is forwarded by satellites to ground stations (GSs), which leads to satellites that are responsible for forwarding being overload and data cannot be timely downloaded to GS. Moreover the dynamic and complex SIN operating environment deteriorates the performance of data downloading. Thus, for improving data downloading, it is a key to realize data load balance. That means extra data is offloaded to other satellites having extra downloading capacity with an effective scheduling method. To this end, we modeled collaborative data offloading problem as multi-objective mixed integer nonlinear programming (MOMINLP) problems based on developing time-evolving graph (TEG) and contact plan. Due to its computational complexity, we proposed a heuristic approach with phasing based on contact plan, i.e., phased offloading algorithm (POA) operating on a slot-by-slot basis, to jointly schedule data offloading among the satellites and data downloading from satellites to the GS. Simulation results demonstrate that, in many cases, the proposed algorithms can guarantee relatively high data down-loading throughput and low energy consumption produced by data offloading.

关键词： Space information networks Data offloading Contact plan design Optimization

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HyperTune: Dynamic Hyperparameter Tuning for Efficient Distribution of DNN Training Over Heterogeneous Systems

HyperTune: Dynamic Hyperparameter Tuning for Efficient Distr...

引用

IEEE International conference on computer-Aided Design

作者： Ali HeydariGorji Siavash Rezaei Mahdi Torabzadehkashi Hossein Bobarshad Vladimir Alves Pai H. Chou University of California Irvine Irvine California USA NGD Systems Inc. Irvine California USA NGD Systems Inc. Irvine CA USA University of California Irvine Irvine CA USA

ISBN: (数字)9781665423243

Distributed training is a novel approach to accelerating training of Deep Neural Networks (DNN), but common training libraries fall short of addressing the distributed nature of heterogeneous processors or interruption by other workloads on the shared processing nodes. This paper describes distributed training of DNN on computational storage devices (CSD), which are NAND flash-based, high-capacity data storage with internal processing engines. A CSD-based distributed architecture incorporates the advantages of federated learning in terms of performance scalability, resiliency, and data privacy by eliminating the unnecessary data movement between the storage device and the host processor. The paper also describes Stannis, a DNN training framework that improves on the shortcomings of existing distributed training frameworks by dynamically tuning the training hyperparameters in heterogeneous systems to maintain the maximum overall processing speed in term of processed images per second and energy efficiency. Experimental results on image classification training benchmarks show up to 3.1x improvement in performance and 2.45x reduction in energy consumption when using Stannis plus CSD compare to the generic systems.

关键词： Training Task analysis Engines Servers program processors Neural networks Distributed databases

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How Do Students Talk About Intelligence? An Investigation of Motivation, Self-efficacy, and Mindsets in computer Science 19

How Do Students Talk About Intelligence? An Investigation of...

引用

15th ACM Annual International Computing Education Research (ICER) conference

作者： Gorson, Jamie O'Rourke, Eleanor Northwestern Univ Evanston IL 60208 USA

ISBN: (纸本)9781450361859

Undergraduate programs in computer science (CS) face high dropout rates, and many students struggle while learning to program. Studies show that perceived programming ability is a significant factor in students' decision to major in CS. Fortunately, psychology research shows that promoting the growth mindset, or the belief that intelligence grows with effort, can improve student persistence and performance. However, mindset interventions have been less successful in CS than in other domains. We conducted a small-scale interview study to explore how CS students talk about their intelligence, mindsets, and programming behaviors. We found that students' mindsets rarely aligned with definitions in the literature;some present mindsets that combine fixed and growth attributes, while others behave in ways that do not align with their mindsets. We also found that students frequently evaluate their self-efficacy by appraising their programming intelligence, using surprising criteria like typing speed and ease of debugging to measure ability. We conducted a survey study with 103 students to explore these self-assessment criteria further, and found that students use varying and conflicting criteria to evaluate intelligence in CS. We believe the criteria that students choose may interact with mindsets and impact their motivation and approach to programming, which could help explain the limited success of mindset interventions in CS.

关键词： Growth Mindset Self-efficacy Motivation Qualitative methods

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