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

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A Twin-Buffer Scheme for high-Throughput Logging 23rd

A Twin-Buffer Scheme for High-Throughput Logging

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23rd International conference on Database Systems for Advanced Applications (DASFAA).

作者： Meng, Qingzhong Zhou, Xuan Wang, Shan Huang, Haiyan Liu, Xiaoli Renmin Univ China DEKE MOE Key Lab Beijing Peoples R China East China Normal Univ Sch Data Sci & Engn Shanghai Peoples R China Huawei Technol Co Ltd Shenzhen Peoples R China

ISBN: (纸本)9783319914589;9783319914572

For a transactional database system, the efficiency of logging is usually crucial to its performance. The emergence of new hardware, such as NVM and SSD, eliminated the traditional I/O bottleneck of logging and released the potential of multi-core CPUs. As a result, the parallelism of logging becomes important. We propose a parallel logging subsystem called TwinBuf and implemented it in PostgreSQL. This solution can make better use of multi-core CPUs, and is generally applicable to all kinds of storage devices, such as hard disk, SSD and NVM. TwinBuf adopts per-thread logging slots to parallelize logging, and a twin-log-buffer mechanism to make sure that logging can be performed in a non-stop manner. It performs group commit to minimize the persistence overheads. Experimental evaluation was conducted to demonstrate its advantages.

关键词： program processors

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WSMeter: A performance Evaluation Methodology for Google's Production Warehouse-Scale computers 18

WSMeter: A Performance Evaluation Methodology for Google's P...

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23rd International conference on Architectural Support for programming Languages and Operating Systems (ASPLOS)

作者： Lee, Jaewon Kim, Changkyu Lin, Kun Cheng, Liqun Govindaraju, Rama Kim, Jangwoo Seoul Natl Univ Elect & Comp Engn Seoul South Korea Google Platforms Engn Mountain View CA USA

ISBN: (纸本)9781450349116

Evaluating the comprehensive performance of a warehouse-scale computer (WSC) has been a long-standing challenge. Traditional load-testing benchmarks become ineffective because they cannot accurately reproduce the behavior of thousands of distinct jobs co-located on a WSC. We therefore evaluate WSCs using actual job behaviors in live production environments. From our experience of developing multiple generations of WSCs, we identify two major challenges of this approach: 1) the lack of a holistic metric that incorporates thousands of jobs and summarizes the performance, and 2) the high costs and risks of conducting an evaluation in a live environment. To address these challenges, we propose WSMeter, a cost-effective methodology to accurately evaluate a WSC's performance using a live production environment. We first define a new metric which accurately represents a WSC's overall performance, taking a wide variety of unevenly distributed jobs into account. We then propose a model to statistically embrace the performance variance inherent in WSCs, to conduct an evaluation with minimal costs and risks. We present three real-world use cases to prove the effectiveness of WSMeter. In the first two cases, WSMeter accurately discerns 7% and 1% performance improvements from WSC upgrades using only 0.9% and 6.6% of the machines in the WSCs, respectively. We emphasize that naive statistical comparisons incur much higher evaluation costs (> 4x) and sometimes even fail to distinguish subtle differences. The third case shows that a cloud customer hosting two services on our WSC quantifies the performance benefits of software optimization (+ 9.3%) with minimal overheads (2.3% of the service capacity).

关键词： warehouse-scale computer performance evaluation statistical modeling

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NDFMF: An Author Name Disambiguation Algorithm based on the Fusion of Multiple Features 42

NDFMF: An Author Name Disambiguation Algorithm based on the ...

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42nd Annual IEEE-computer-Society computers, Software and Applications (COMPSAC) conference - Staying Smarter in a Smartening World

作者： Xu, Xiaolong Li, Yongping Liptrott, Mark Bessis, Nik Nanjing Univ Posts & Telecommun Jiangsu Key Lab Big Data Secur & Intelligent Proc Nanjing Peoples R China Nanjing Univ Posts & Telecommun Sch Comp Sci Nanjing Peoples R China Edge Hill Univ Dept Comp Ormskirk England

ISBN: (纸本)9781538626672

Author name disambiguation is a very important and complex research topic. During the retrieval and research of literature the quality of the investigation results has been reduced because of the high probability of different authors sharing the same name, which lengthens the whole cycle of the scientific research. Therefore, it is necessary to find a reasonable and efficient method to distinguish the different authors who share the same name. In this paper, an author name disambiguation algorithm based on the fusion of multiple features (NDFMF) is proposed. First we proposed a single feature similarity detection algorithm (SFSD). SFSD is used to compute the degree of similarity between two features of a paper and to assess the threshold value. Then, SFSD is used to realize the preliminary SFSD-based disambiguation algorithm (SFSDD). Furthermore, different features are evaluated according to the disambiguation results of author names and the evaluation metrics, including precision, recall and F-measure with SFSDD. The evaluation parameter of weight (W) is introduced to express each feature's influence in disambiguation. NDFMF can disambiguate author names more efficiently based on the fusion of multiple features. Experiments were implemented to test the performance of NDFMF. Experimental results show that NDFMF was effective in the disambiguation precision, recall and F-measure.

关键词： name disambiguation single feature multiple features fusion

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Decision Support Model for Supplier Selection Using Fuzzy Logic Concept 3

Decision Support Model for Supplier Selection Using Fuzzy Lo...

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3rd International conference on Information Management and Technology, ICIMTech 2018

作者： Gunawan, Ferdi Wang, Gunawan Utama, Ditdit Nugeraha Komsiyah, Siti Suharjito Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Information Systems Management Department Bina Nusantara University BINUS Graduate Program-Master of Information Systems Management Jakarta11480 Indonesia Computer Science Department Bina Nusantara University BINUS Graduate Program-Master of Computer Science Jakarta11480 Indonesia Mathematics Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9781538658215

Improving the company's performance to compete globally, in rapid growth market economy condition, is practically required. One of the important things is right decision in issues of supplier selection. The improper supplier affects consequence negatively to the quality of company's business process. Thus, the right way to answer the issues is incredibly crucial to be proposed. This study aims to design an application to determine the sub-criteria weight with Fuzzy-AHP method, select the best supplier via Fuzzy-TOPSIS method, and calculate the allocation of quota to each supplier thru Fuzzy-MOLP method. The study was conducted on high class store by taking the object of material gymnastic product (spandex). Simulation confidently demonstrates that the Fuzzy-AHP approach is able to be operated to generate parameter Quality Product as the best sub-criteria (with value 0.221), the Fuzzy-TOPSIS technique can be used to ring out the supplier (where CV. Maju Jaya Abadi as the best supplier), and the method Fuzzy-MOLP is exploited to calculate the allocation of quota (where CV. Maju Jaya Abadi as a supplier with the highest percentage of 44.40%). © 2018 IEEE.

关键词： Fuzzy logic

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Advanced Autonomy on a Low-Cost Educational Drone Platform

Advanced Autonomy on a Low-Cost Educational Drone Platform

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2019 IEEE/RSJ International conference on Intelligent Robots and Systems (IROS)

作者： Luke Eller Théo Guérin Baichuan Huang Garrett Warren Sophie Yang Josh Roy Stefanie Tellex Department of Computer Science Brown University Providence RI USA

PiDrone is a quadrotor platform created to accompany an introductory robotics course. Students build an autonomous flying robot from scratch and learn to program it through assignments and projects. Existing educational robots do not have significant autonomous capabilities, such as high-level planning and mapping. We present a hardware and software framework for an autonomous aerial robot, in which all software for autonomy can run onboard the drone, implemented in Python. We present an Unscented Kalman Filter (UKF) for accurate state estimation. Next, we present an implementation of Monte Carlo (MC) Localization and FastSLAM for Simultaneous Localization and Mapping (SLAM). The performance of UKF, localization, and SLAM is tested and compared to ground truth, provided by a motion-capture system. Our evaluation demonstrates that our autonomous educational framework runs quickly and accurately on a Raspberry Pi in Python, making it ideal for use in educational settings.

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Classfication of Categorized KMUTT-BKT's Landscape Images using RGB Color Feature 14

Classfication of Categorized KMUTT-BKT's Landscape Images us...

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14th International conference on Signal Image Technology & Internet Based Systems (SITIS)

作者： Phetnuam, Siriphan Yingthawornsuk, Thaweesak King Mongkuts Univ Technol Thonburi Media Technol Program Bangkok Thailand

ISBN: (纸本)9781538693858

This study proposes how to implement the computer based program able to process the image, estimate and classify images the landscape images based on adaption of RGB Color Space technique into the procedure of image processing. The database consisted of total 705 satellite images categorized into main four groups of landscapes: Building, Agricultural, Forest and Water. The procedure of study included image segmentation, histogram approximation for RUB color intensity, feature estimation and classification. The results obtained from processing have shown that the histograms of RGB among four categorized image groups are different in color intensity represented in term of dominant peaks and their intensity location. As visually observed, it can be found that most images of water resource have their histogram with a very high peak of color intensity obviously different from forest, building and agriculture. This kind of similar trend on histogram intensity can be found for all three color spaces of Red, Green and Blue. Therefore, only the Red histogram was selected for further procedure. The color intensity value and location were then chosen to serve as input feature set to classification. Based on the comparative performance resulted from classification, the Maximum likelihood (ML) classifier revealed its performance to be the highest accuracy at approximately 87.85% and the lowest accuracy of 51.69%, and another classifier the Least Square (LS) showed its highest accuracy at 87.85% and the lowest at 60.54%. Both types of classifiers have a very similar performance. The results from this study could suggest the applicable identification of various landscapes in images based simply on the intensity of color in histogram of image as the common effective feature set for identification of landscape images.

关键词： satellite image histogram Classifcation RGB Color Space

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A Learning-Based Recommender System for Autotuning Design FIows of Industrial high-performance Processors

A Learning-Based Recommender System for Autotuning Design FI...

引用

Design Automation conference

作者： Jihye Kwon Matthew M. Ziegler Luca P. Carloni Department of Computer Science Columbia University New York NY USA IBM T. J. Watson Research Center Yorktown Heights NY USA

ISBN: (纸本)9781728124261

Logic synthesis and physical design (LSPD) tools automate complex design tasks previously performed by human designers. One time-consuming task that remains manual is configuring the LSPD flow parameters, which significantly impacts design results. To reduce the parameter-tuning effort, we propose an LSPD parameter recommender system that involves learning a collaborative prediction model through tensor decomposition and regression. Using a model trained with archived data from multiple state-of-the-art 14nm processors, we reduce the exploration cost while achieving comparable design quality. Furthermore, we demonstrate the transfer-learning properties of our approach by showing that this model can be successfully applied for 7nm designs.

关键词： Tuning Recommender systems program processors Collaboration Task analysis Measurement Optimization

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performance evaluation of Jacobi iterative solution for sparse linear equation system on multicore and manycore architectures 1st

引用

1st International conference on Infrastructure, Technologies and Applications, SCITA 2017

作者： Alzahrani, Samiah Ikbal, Mohammad Rafi Mehmood, Rashid Fayez, Mahmoud Katib, Iyad Faulty of Information Technology King Abdul Aziz University Jeddah Saudi Arabia Fujitsu Technology Solutions Jeddah Saudi Arabia High Performance Computing Center King Abdulaziz University Jeddah Saudi Arabia

ISBN: (纸本)9783319941790

One of the common and pressing challenges in solving real-world problems in various domains, such as in smart cities, involves solving large sparse systems of linear equations. Jacobi iterative method is used to solve such systems in case if they are diagonally dominant. This research focuses on the parallel implementation of the Jacobi method to solve large systems of diagonally dominant linear equations on conventional CPUs and Intel Xeon Phi co-processor. The performance is reported on the two architectures with a comparison in terms of the execution times. © 2018, ICST Institute for computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： program processors

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Research and Optimization of Massive Music Data Access Based on HDFS 17

Research and Optimization of Massive Music Data Access Based...

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17th IEEE/ACIS International conference on computer and Information Science, ICIS 2018

作者： Ouyang, Tong Cao, Yizhen School of Computer Science Communication University of China Beijing China

ISBN: (纸本)9781538658925

To build a storage management platform for music big data, we need to collect massive heterogeneous music resources from the Internet and store them on big data platforms. Therefore, it is a key problem to build a storage management system that is high performance, extensible, scalable and capable of supporting big data. Building big data platform based on HDFS is a feasible scheme. However, HDFS has good performance for accessing large files, but it is very inefficient for small files such as music source files and music metadata. In view of this, this paper proposes a geared to the needs of mass music based on HDFS small file access optimization scheme, using the format of the music data classification, build multistage merger queue, merging small files into large files in order to reduce the number of files, and create an indexing mechanism to access small files. The index file is then stored in the Phoenix + HBase storage repository and associated with the music metadata to improve the reading efficiency of music small files and music metadata. The experimental test verifies the effectiveness of the optimized scheme and meets the demand of music big data storage management platform. © 2018 IEEE.

关键词： Big data

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Efficient make before break capacity defragmentation 19

Efficient make before break capacity defragmentation

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19th IEEE International conference on high performance Switching and Routing, HPSR 2018

作者： Duong, Huy Jaumard, Brigitte Coudert, David Armolavicius, Ron Computer Science and Software Engineering Concordia University Montreal Canada Université Côte d'Azur Inria CNRS I3S Sophia Antipolis France CIENA Ottawa Canada

ISBN: (纸本)9781538678015

Optical multilayer optimization continuously reorganizes layer 0-1-2 network elements to handle both existing and dynamic traffic requirements in the most efficient manner. This delays the need to add new resources for new requests, saving CAPEX and leads to optical network defragmentation. The focus of this paper is on Layer 2, i.e., on capacity defragmentation at the OTN layer when routes (e.g., LSPs in MPLS networks) are making unnecessarily long detours to evade congestion. Reconfiguration into optimized routes can be achieved by re-defining the routes, one at a time, so that they use the vacant resources generated by the disappearance of services using part of a path that transits the congested section. For the Quality of Service, it is desirable to operate under Make Before Break (MBB), with the minimum number of rerouting. The challenge is to identify the rerouting order, one connection at a time, while minimizing the bandwidth requirement. We propose an exact and scalable optimization model for computing a minimum bandwidth rerouting scheme subject to MBB in the OTN layer of an optical network. Numerical results show that we can successfully apply it on networks with up to 30 nodes, a very significant improvement with the state of the art. We also provide some defragmentation analysis in terms of the bandwidth requirement vs. the number of reroutings. © 2018 IEEE.

关键词： Optical multilayers

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