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By Guojun Wang, Albert Zomaya, Gregorio Martinez, Kenli Li

This 4 quantity set LNCS 9528, 9529, 9530 and 9531 constitutes the refereed court cases of the fifteenth overseas convention on Algorithms and Architectures for Parallel Processing, ICA3PP 2015, held in Zhangjiajie, China, in November 2015.

The 219 revised complete papers provided including seventy seven workshop papers in those 4 volumes have been rigorously reviewed and chosen from 807 submissions (602 complete papers and 205 workshop papers). the 1st quantity includes the subsequent subject matters: parallel and disbursed architectures; disbursed and network-based computing and net of items and cyber-physical-social computing. the second one quantity contains themes akin to immense facts and its functions and parallel and disbursed algorithms. the themes of the 3rd quantity are: functions of parallel and disbursed computing and repair dependability and safeguard in disbursed and parallel platforms. The coated subject matters of the fourth quantity are: software program structures and programming versions and function modeling and evaluation.

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Read or Download Algorithms and Architectures for Parallel Processing: 15th International Conference, ICA3PP 2015, Zhangjiajie, China, November 18-20, 2015, Proceedings, Part II PDF

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Extra resources for Algorithms and Architectures for Parallel Processing: 15th International Conference, ICA3PP 2015, Zhangjiajie, China, November 18-20, 2015, Proceedings, Part II

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Fahui Jia, Chao Wang, Xi Li, and Xuehai Zhou 106 HDCat: Effectively Identifying Hot Data in Large-Scale I/O Streams with Enhanced Temporal Locality . . . . . . . . . . . . . . . . Jiahao Chen, Yuhui Deng, and Zhan Huang 120 LuBase: A Search-Efficient Hybrid Storage System for Massive Text Data . . Debin Jia, Zhengwei Liu, Xiaoyan Gu, Bo Li, Jingzi Gu, Weiping Wang, and Dan Meng 134 XLVIII Contents – Part II Enhancing Parallel Data Loading for Large Scale Scientific Database .

This paper proposed preference model and implements Preference-Aware HDFS for Hybrid Storage (PAHDFS). For hybrid environment composed of variety types of storage devices, PAHDFS tracks read/write characteristics of data, and analyses the most fitting device on which data can obtain best access performance according to device read and write ability of device. So access performance and resource utilization can be improved if data are placed on suitable devices. Beside, data size of access request is considered in preference model, and small files with high access frequency may have priority to store on high performance device such like SSD.

Rong Gu, Lei Jin, Yongwei Wu, Jingying Qu, Tao Wang, Xiaojun Wang, Chunfeng Yuan, and Yihua Huang 31 52 DBSCAN-M: An Intelligent Clustering Algorithm Based on Mutual Reinforcement . . . . . . . . . . . . . . . . . . . . . . Yin Li, Chuyuan Guo, Ronghua Shi, Xiaoqun Liu, and Yan Mei 66 An Effective Method for Gender Classification with Convolutional Neural Networks . . . . . . . . . . . . . . . . . .

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