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检索条件"任意字段=5th International Conference on Algorithms and Architectures for Parallel Processing"

共 3293 条记录，以下是911-920 订阅

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Using Inaccurate Job Prediction for Detecting Machine Failures in parallel Computing Cluster

Using Inaccurate Job Prediction for Detecting Machine Failur...

引用

Big Data Intelligence and Computing (DATACOM), international conference on

作者： Lin Ting-Yu Jerry Chou Institute of Information Systems and Applications National Tsing Hua University Hsinchu Taiwan Department of Computer Science National Tsing Hua University Hsinchu Taiwan

ISBN: (数字)9781728141176

ISBN: (纸本)9781728141183

Machine failures can cause many problems, such as job execution failures and user data loss. the problem can be further aggravated for parallel computing jobs because a job can be executed across multiple nodes. One of the common approaches is to detect performance degradation as a hint of machine failures before catastrophic impacts occur. However, it is hard to accurately predict job time in practice, especially in a shared and parallel computing environment where performance can be affected by various factors in runtime environment, such as job interference, network delay, etc. therefore, instead of aiming to develop an accurate job predictor, we propose a detection algorithm that incorporates inaccurate job prediction in a more general and complex parallel computing environment. through a series data analysis techniques, we improve the machine failure detection accuracy (i.e., F1-score) by 20% to 40% comparing to the previous approaches.

关键词： Support vector machines Degradation Runtime environment Accuracy Tail Interference parallel processing

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Performance Evaluation of Scientific Applications on Intel Xeon Phi Knights Landing Clusters 16

Performance Evaluation of Scientific Applications on Intel X...

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international conference on High Performance Computing and Simulation (HPCS)

作者： Kang, Ji-Hoon Kwon, Oh-Kyoung Jeong, Jinwoo Lim, Kyunghun Ryu, Hoon Korea Inst Sci & Technol Informat Intel Parallel Comp Ctr Daejeon 34141 South Korea Moasys Corp Res Ctr Seoul 06746 South Korea

ISBN: (纸本)9781538678794

Korea Institute of Science and Technology Information (KISTI) is building its 5th supercomputer based on Intel Xeon Phi Knights Landing (KNL) processors, and plans to provide an open service to computational scientists in the near future. We perform solid benchmark tests for several well-known open/commercial application softwares in a 16 node pilot system for a preliminary performance evaluation of KNL systems. Based on their results, we present detailed discussion with a focus on the performance gain that can be obtained with unique features in KNL processors. Performance of application software measured in our KNL pilot system is compared to that obtained in the current supercomputer based on traditional multicore processors, to claim the practical benefits of Intel onboard Many-Integrated-Core architectures for large-scale scientific computing.

关键词： Xeon Phi Knights Landing processors Scientific applications High performance computing Benchmark tests

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parallel k-means Clustering of Geospatial Data Sets Using Manycore CPU architectures 18

Parallel <i>k</i>-means Clustering of Geospatial Data Sets U...

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18th IEEE international conference on Data Mining Workshops (ICDMW)

作者： Mills, Richard Tran Sripathi, Vamsi Kumar, Jitendra Sreepathi, Sarat Hoffman, Forrest M. Hargrove, William W. Argonne Natl Lab Math & Comp Sci Div Lemont IL 60439 USA Intel Corp Data Ctr Grp Hillsboro OR USA Oak Ridge Natl Lab Div Environm Sci POB 2008 Oak Ridge TN 37831 USA Oak Ridge Natl Lab Comp Sci & Math Div Oak Ridge TN USA Oak Ridge Natl Lab Computat Sci & Engn Div Oak Ridge TN USA US Forest Serv So Res Stn USDA Asheville NC USA

ISBN: (纸本)9781538692882

the increasing availability of high-resolution geospatiotemporal data sets from sources such as observatory networks, remote sensing platforms, and computational Earth system models has opened new possibilities for knowledge discovery and mining of weather, climate, ecological, and other geoscientific data sets fused from disparate sources. Many of the standard tools used on individual workstations are impractical for the analysis and synthesis of data sets of this size;however, new algorithmic approaches that can effectively utilize the complex memory hierarchies and the extremely high levels of parallelism available in state-of-the-art high-performance computing platforms can enable such analysis. Here, we describe pKluster, an open-source tool we have developed for accelerated k-means clustering of geospatial and geospatiotemporal data, and discuss algorithmic modifications and code optimizations we have made to enable it to effectively use parallel machines based on novel CPU architectures-such as the Intel Knights Landing Xeon Phi and Skylake Xeon processors-with many cores and hardware threads, and employing significant single instruction, multiple data (SIMD) parallelism. We outline some applications of the code in ecology and climate science contexts and present a detailed discussion of the performance of the code for one such application, LiDAR-derived vertical vegetation structure classification.

关键词： Instruction sets parallel processing Acceleration Computer architecture Clustering algorithms Geoscience

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A Comparison of Accuracy and Efficiency of parallel Solvers for Fractional Power Diffusion Problems 12th

A Comparison of Accuracy and Efficiency of Parallel Solvers ...

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12th international conference on parallel processing and Applied Mathematics (PPAM)

作者： Ciegis, Raimondas Starikovicius, Vadimas Margenov, Svetozar Kriauziene, Rima Vilnius Gediminas Tech Univ Sauletekis Ave 11 LT-10223 Vilnius Lithuania Bulgarian Acad Sci Inst Informat & Commun Technol Acad G Bonchev StBl 25A BU-1113 Sofia Bulgaria Vilnius Univ Inst Math & Informat Akad St 4 LT-08663 Vilnius Lithuania

ISBN: (纸本)9783319780245;9783319780238

In this paper, we construct and investigate parallel solvers for three dimensional problems described by fractional powers of elliptic operators. the main aim is to make a scalability analysis of parallel versions of several state of the art solvers. the originality of this work is that we also consider the accuracy of the selected numerical algorithms. For comparison of accuracy, we use solutions obtained solving the test problem by the Fourier algorithm. Such analysis enables to compare the efficiency of the proposed parallel algorithms depending on the required accuracy of solution and on a number of processes used in computations.

关键词： Fractional diffusion Finite volume method parallel numerical algorithms MPI Scalability Multigrid

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Proceedings of the 44th international conference on Very Large Data Bases, VLDB January 2018

Proceedings of the 44th International Conference on Very Lar...

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44th international conference on Very Large Data Bases, VLDB 2018

this proceedings contains 10 papers. the Proceedings of the VLDB Endowment (PVLDB) provides a high-quality publication service to the data management research community. Issue 5 contains a variety of topics ranging from transactional databases and parallel architectures for traditional data processing and for machine learning, advanced indexing including range indices and R-trees, storage, and privacy. the key terms of this proceedings include practical differential privacy, structured storage, non-volatile memory, latch-free range index, parameter server architecture, hierarchical data, flexible parallelism control, throughput Optimizing Adaptive Index (TOAIN), machine learning workloads, contention-aware lock scheduling. © 2018 VLDB Endowment 21508097/18/01.

关键词： parallel architectures

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An Approach for Optimizing the Average Waiting Time for Vehicles at the Traffic Intersection 5

An Approach for Optimizing the Average Waiting Time for Vehi...

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5th IEEE international conference on parallel, Distributed and Grid Computing (PDGC)

作者： Pandey, Kavita Jalan, Priyesh Jaypee Inst Informat Technol Comp Sci Dept Noida India

ISBN: (纸本)9781728106465

With an increase in the number of vehicles, traffic management with the traditional traffic light system has become a big challenge. the primary problem with the existing system is that people have to wait at the signals for a fixed amount of time, even if other lanes at the intersection have less or no vehicles. therefore, the solution proposed in this paper monitors the traffic density on all the lanes of the intersection by image and video processing. Furthermore, according to the traffic, dynamic time is allotted to the signals. this helps in reducing the waiting time of the vehicles. the proposed method is easy and efficient in deciding the time division for the traffic lights which proves to be a useful tool for traffic management.

关键词： Intelligent Traffic Light System Image processing Haar Cascade Vehicles Waiting Time

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Improvement and parallel Implementation of EKF Battery Algorithm Based on the Spark Streaming 5

Improvement and Parallel Implementation of EKF Battery Algor...

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5th IEEE international conference on Cloud Computing and Intelligence Systems (CCIS)

作者： Qi, Zitong Yang, Zhengqiu Liu, Chen Xiu, Jiapeng Beijing Univ Posts & Telecommun Beijing 100876 Peoples R China

ISBN: (纸本)9781538660058

Battery management system (BMS) is a system for the power balance control of power systems. this system relies on the real-time grasp of important parameters such as SOC (State of Charge), polarization resistance and OCV by EKF (extended Kalman filter) battery algorithm. It is of great significance for drivers to grasp the follow-up mileage reasonably and to control the power of BMS. With the generation of massive data, the traditional EKF battery algorithm will encounter the bottleneck of time and space when running on a single machine and cannot meet the real-time requirements of streaming big data processing. In view of the above problems, the research on EKF battery algorithm under large-scale data sets is carried out. Based on the Spark Streaming real-time streaming data processing framework, the EKF battery algorithm is improved by setting batches and performing stateful operations, and the distributed calculation of this algorithm and the dynamic allocation of computing resources are realized. the intermediate results generated during the operation are all stored in memory, thus effectively reducing the I/O consumption of data and improving the efficiency of the algorithm. the experimental results show that the optimized algorithm is superior to the traditional EKF battery algoritlun in large-scale streaming data.

关键词： Spark Streaming power battery distributed stream processing EKF algorithm

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MULESOFT - SALESFORCE INTEGRATION USING BATCH processing 5

MULESOFT - SALESFORCE INTEGRATION USING BATCH PROCESSING

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5th ACIS international conference on Computational Science/Intelligence and Applied Informatics (CSII)

作者： Seth, Manvi Cisco Syst Bangalore Karnataka India

ISBN: (纸本)9781538678756

Mulesoft has the capability to process messages in batches. It splits the large messages into individual records that are processed asynchronously within batch jobs. Batch processing can be used for integrating large or small datasets and process the records in parallel. Further, one can set or remove variables on individual records so that during batch processing, Mule can route or otherwise act upon records in a batch according to a record variable. With the batch approach, large volumes of incoming data from any upstream system can be extracted, transformed, and loaded (ETL) into any destination system in real time. In this paper upstream system used is Oracle database and destination system used profoundly is Salesforce. Salesforce is a cloud computing platform which stores data in the form of data objects. this paper identifies challenges that are encountered when upstream systems have complex data storage formats and hence the conversions that are necessary to perform efficacious data transfers are discussed. To help provide a deeper insight, this paper discusses many components that are very specific to batch processing and can be used to implement business logic along with some general scenarios that form the basis of any batch flow. Uses Cases wherein up to 52 million records were retrieved from database, transformed and upserted successfully to Salesforce along with appropriate error handling mechanisms are discussed. Also, the recent news of Salesforce acquiring Mulesoft opens up vast opportunities to integrate data with Salesforce using powerful Mulesoft capabilities like the Batch processing.

关键词： Mulesoft Salesforce ETL Batch processing Record Variables Error Handling

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Functional words removal techniques: A review 5

Functional words removal techniques: A review

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5th IEEE international conference on parallel, Distributed and Grid Computing (PDGC)

作者： Gandotra, Sonam Arora, Bhavna Cent Univ Jammu Dept Comp Sci & IT Jammu Jammu & Kashmir India

ISBN: (纸本)9781728106465

With the growth of internet activities, electronic documents has become the key source of data and optimization of this data is very important for various research tasks such as Information Retrieval, Natural Language processing, Web mining, Text mining etc. the data which is present in the web is a combination of both structured as well as unstructured data which mostly contains textual data. Hence, text processing is required for extracting useful information from that type of data which can then be used for further processes. Preprocessing plays a vital role in all text processing activities. Stop-word removal is one of the most important pre-processing techniques which eliminate the functional words from the document. thus, helps in improving the performance of the system. In this paper, all the stop-word removal techniques used for Indian text are discussed along with the analysis of results produced by using those techniques for various Indian languages is also presented.

关键词： Text pre-processing Stop-words Dictionary-based Frequency-based

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12th international conference on parallel processing and Applied Mathematics, PPAM 2017

12th International Conference on Parallel Processing and App...

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12th international conference on parallel processing and Applied Mathematics, PPAM 2017

ISBN: (纸本)9783319780238

the proceedings contain 101 papers. the special focus in this conference is on parallel processing and Applied Mathematics. the topics include: Performance and energy analysis of scientific workloads executing on LPSoCs;Energy Efficient dynamic load balancing over multiGPU heterogeneous systems;scheduling data gathering with maximum lateness objective;Fair scheduling in grid VOs with anticipation heuristic;a security-driven approach to online job scheduling in IaaS cloud computing systems;dynamic load balancing algorithm for heterogeneous clusters;multi-objective extremal optimization in processor load balancing for distributed programs;pardis: A process calculus for parallel and distributed programming in haskell;towards high-performance python;Using GPGPU accelerated interpolation algorithms for marine bathymetry processing with on-premises and cloud based computational resources;actor model of a new functional language - Anemone;Almost optimal column-wise prefix-sum computation on the GPU;A combination of intra- and inter-place work stealing for the APGAS library;Benchmarking molecular dynamics with OpenCL on many-core architectures;efficient language-based parallelization of computational problems using cilk plus;a taxonomy of task-based technologies for high-performance computing;Interoperability of GASPI and MPI in large scale scientific applications;Evaluation of the parallel performance of the java and PCJ on the intel KNL based systems;Fault-tolerance mechanisms for the java parallel codes implemented with the PCJ library;Exploring graph analytics with the PCJ toolbox;Relaxing the correctness conditions on concurrent data structures for multicore CPUs. A numerical case study;Big data analytics in java with PCJ library: Performance comparison with hadoop;parallel exact diagonalization approach to large molecular nanomagnets modelling.

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