2011 12th International Conference on Parallel and Distributed Computing, Applications and Technologies最新文献_第6页

Optimization of Algorithm to Identification of Duplicate Tuples through Similarity Phonetic Based on Multithreading 基于多线程的相似语音重复元组识别算法优化

2011 12th International Conference on Parallel and Distributed Computing, Applications and Technologies Pub Date : 2011-10-20 DOI: 10.1109/PDCAT.2011.58

Tiago Luis Andrade, Rogéria Cristiane Gratão de Souza, Maurizio Babini, C. R. Valêncio

引用次数: 5

Phase Map Generation for Phase Shift Moire Using CUDA 基于CUDA的相移云纹相图生成

2011 12th International Conference on Parallel and Distributed Computing, Applications and Technologies Pub Date : 2011-10-20 DOI: 10.1109/PDCAT.2011.68

Sudhakar Sah, Y. Roh, KyoungSeop Chang, DaeHwa Jeong

引用次数: 1

A Fast Incremental Spectral Clustering for Large Data Sets 大数据集快速增量谱聚类

2011 12th International Conference on Parallel and Distributed Computing, Applications and Technologies Pub Date : 2011-10-20 DOI: 10.1109/PDCAT.2011.4

Tengteng Kong, Ye Tian, Hong Shen

引用次数: 20

Communication-Aware Task Partition and Voltage Scaling for Energy Minimization on Heterogeneous Parallel Systems 异构并行系统中基于通信感知的任务划分和电压标度的能量最小化

2011 12th International Conference on Parallel and Distributed Computing, Applications and Technologies Pub Date : 2011-10-20 DOI: 10.1109/PDCAT.2011.28

Guibin Wang, Wei Song

{"title":"Communication-Aware Task Partition and Voltage Scaling for Energy Minimization on Heterogeneous Parallel Systems","authors":"Guibin Wang, Wei Song","doi":"10.1109/PDCAT.2011.28","DOIUrl":"https://doi.org/10.1109/PDCAT.2011.28","url":null,"abstract":"Heterogeneous parallel systems have become popular in general purpose computing and even high performance computing fields. There are many studies focused on harnessing heterogeneous parallel processing for better performance. However the energy optimization for heterogeneous system has not been well studied. Owing to the differences in performance and energy consumption, the energy optimization technique for heterogeneous system is different from the existing methods designed for homogeneous system. Besides typical voltage scaling method, reasonable task partitioning is also an essential method for optimizing energy consumption on heterogeneous systems. Through partitioning a data parallel task and mapping sub-tasks onto several processors, one could achieve better performance and reduced energy consumption. As the computation cost reduces with specific accelerators, the communication overhead becomes more prominent. Therefore, the task partition optimization should holistically consider the computation improvement and communication overhead to achieve higher energy efficiency. Typically, task partition and voltage scaling are not orthogonal and influence the effect of each other in the energy optimization problem. In order to harness both two knobs efficiently, this paper proposes an integer linear programming (ILP) based energy-optimal solution designed for heterogeneous system. We present a case study of optimizing MGRID benchmark on a typical CPU-GPU heterogeneous system. The experimental results demonstrate that the proposed method could exploit the heterogeneity in different processors and achieve improved energy efficiency.","PeriodicalId":137617,"journal":{"name":"2011 12th International Conference on Parallel and Distributed Computing, Applications and Technologies","volume":"2015 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126002347","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Anonymizing Hypergraphs with Community Preservation 匿名超图与社区保存

2011 12th International Conference on Parallel and Distributed Computing, Applications and Technologies Pub Date : 2011-10-20 DOI: 10.1109/PDCAT.2011.21

Yidong Li, Hong Shen

引用次数: 2

The Multidimensional Scaling and Barycentric Coordinates Based Distributed Localization in Wireless Sensor Networks 基于多维尺度和重心坐标的无线传感器网络分布式定位

2011 12th International Conference on Parallel and Distributed Computing, Applications and Technologies Pub Date : 2011-10-20 DOI: 10.1109/PDCAT.2011.79

Cuiqin Hou, Yibin Hou, Zhangqin Huang, Huibing Zhang

引用次数: 3

An Empirical Study of the Beezone System Beezone制度的实证研究

2011 12th International Conference on Parallel and Distributed Computing, Applications and Technologies Pub Date : 2011-10-20 DOI: 10.1109/PDCAT.2011.17

Shuyu Liu, Zhengbiao Guo, Zhitang Li, Hao Tu

引用次数: 0

Dacoop: Accelerating Data-Iterative Applications on Map/Reduce Cluster doop:加速Map/Reduce集群上的数据迭代应用

2011 12th International Conference on Parallel and Distributed Computing, Applications and Technologies Pub Date : 2011-10-20 DOI: 10.1109/PDCAT.2011.32

Yi Liang, Guangrui Li, Lei Wang, Yanpeng Hu

{"title":"Dacoop: Accelerating Data-Iterative Applications on Map/Reduce Cluster","authors":"Yi Liang, Guangrui Li, Lei Wang, Yanpeng Hu","doi":"10.1109/PDCAT.2011.32","DOIUrl":"https://doi.org/10.1109/PDCAT.2011.32","url":null,"abstract":"Map/reduce is a popular parallel processing framework for massive-scale data-intensive computing. The data-iterative application is composed of a serials of map/reduce jobs and need to repeatedly process some data files among these jobs. The existing implementation of map/reduce framework focus on perform data processing in a single pass with one map/reduce job and do not directly support the data-iterative applications, particularly in term of the explicit specification of the repeatedly processed data among jobs. In this paper, we propose an extended version of Hadoop map/reduce framework called Dacoop. Dacoop extends Map/Reduce programming interface to specify the repeatedly processed data, introduces the shared memory-based data cache mechanism to cache the data since its first access, and adopts the caching-aware task scheduling so that the cached data can be shared among the map/reduce jobs of data-iterative applications. We evaluate Dacoop on two typical data-iterative applications: k-means clustering and the domain rule reasoning in sementic web, with real and synthetic datasets. Experimental results show that the data-iterative applications can gain better performance on Dacoop than that on Hadoop. The turnaround time of a data-iterative application can be reduced by the maximum of 15.1%.","PeriodicalId":137617,"journal":{"name":"2011 12th International Conference on Parallel and Distributed Computing, Applications and Technologies","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116380701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

A Task Based Sensor-Centric Model for Overall Energy Consumption 基于任务的整体能耗传感器中心模型

2011 12th International Conference on Parallel and Distributed Computing, Applications and Technologies Pub Date : 2011-10-20 DOI: 10.1109/PDCAT.2011.12

N. Kamyabpour, D. Hoang

{"title":"A Task Based Sensor-Centric Model for Overall Energy Consumption","authors":"N. Kamyabpour, D. Hoang","doi":"10.1109/PDCAT.2011.12","DOIUrl":"https://doi.org/10.1109/PDCAT.2011.12","url":null,"abstract":"Sensors have limited resources so it is important to manage the resources efficiently to maximize their use. A sensor's battery is a crucial resource as it singly determines the lifetime of sensor network applications. Since these devices are useful only when they are able to communicate with the world, radio transceiver of a sensor as an I/O and a costly unit plays a key role in its lifetime. This resource often consumes a big portion of the sensor's energy as it must be active most of the time to announce the existence of the sensor in the network. As such the radio component has to deal with its embedded sensor network whose parameters and operations have significant effects on the sensor's lifetime. In existing energy models, hardware is considered, but the environment and the network's parameters did not receive adequate attention. Energy consumption components of traditional network architecture are often considered individually and separately, and their influences on each other have not been considered in these approaches. In this paper we consider all possible tasks of a sensor in its embedded network and propose an energy management model. We categorize these tasks in five energy consuming constituents. The sensor's Energy Consumption (EC) is modeled on its energy consuming constituents and their input parameters and tasks. The sensor's EC can thus be reduced by managing and executing efficiently the tasks of its constituents. The proposed approach can be effective for power management, and it also can be used to guide the design of energy efficient wireless sensor networks through network parameterization and optimization.","PeriodicalId":137617,"journal":{"name":"2011 12th International Conference on Parallel and Distributed Computing, Applications and Technologies","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121341426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

jMigBSP: Object Migration and Asynchronous One-Sided Communication for BSP Applications jMigBSP: BSP应用的对象迁移和异步单向通信

2011 12th International Conference on Parallel and Distributed Computing, Applications and Technologies Pub Date : 2011-10-20 DOI: 10.1109/PDCAT.2011.48

Lucas Graebin, R. Righi

{"title":"jMigBSP: Object Migration and Asynchronous One-Sided Communication for BSP Applications","authors":"Lucas Graebin, R. Righi","doi":"10.1109/PDCAT.2011.48","DOIUrl":"https://doi.org/10.1109/PDCAT.2011.48","url":null,"abstract":"This paper describes the rationale for developing jMigBSP - a Java programming library that offers object rescheduling. It was designed to work on grid computing environments and offers an interface that follows the BSP (Bulk Synchronous Parallel) style. jMigBSP's main contribution focuses on the rescheduling facility in two different ways: (i) by using migration directives on the application code directly and (ii) through automatic load balancing at middleware level. Especially, this second idea is feasible thanks to the Java's inheritance feature, in which transforms a simple jMigBSP application in a migratable one only by changing a single line of code. In addition, the presented library makes the object interaction easier by providing one-sided message passing directives and hides network latency through asynchronous communications. Finally, a BSP-based FFT application was developed and its execution shows jMigBSP as a competitive library when comparing performance with a C-based library called BSPlib. Besides its user-friendly Java interface, the strengths of jMigBSP also considers the migration tests where it outperforms the time spent with BSPlib.","PeriodicalId":137617,"journal":{"name":"2011 12th International Conference on Parallel and Distributed Computing, Applications and Technologies","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133524800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5