2014 International Conference on Parallel, Distributed and Grid Computing最新文献_第3页

Optimizing MPI collectives on intel MIC through effective use of cache 通过有效使用缓存优化intel MIC上的MPI集合

2014 International Conference on Parallel, Distributed and Grid Computing Pub Date : 2014-12-01 DOI: 10.1109/PDGC.2014.7030721

Pinak Panigrahi, Sriram Kanchiraju, A. Srinivasan, P. K. Baruah, C. D. Sudheer

{"title":"Optimizing MPI collectives on intel MIC through effective use of cache","authors":"Pinak Panigrahi, Sriram Kanchiraju, A. Srinivasan, P. K. Baruah, C. D. Sudheer","doi":"10.1109/PDGC.2014.7030721","DOIUrl":"https://doi.org/10.1109/PDGC.2014.7030721","url":null,"abstract":"The Intel MIC architecture, implemented in the Xeon Phi coprocessor, is targeted at highly parallel applications. In order to exploit it, one needs to make full use of simultaneous multi-threading, which permits four simultaneous threads per core. Our results also show that distributed tag directories can be a greater bottleneck than the ring for small messages when multiple threads access the same cache line. Careful design of algorithms and implementations based on these results can yield substantial performance improvement. We demonstrate these ideas by optimizing MPI collective calls. We obtain a speedup of 9x on barrier and a speed-up of 10x on broadcast, when compared with Intel's MPI implementation. We also show the usefulness of our collectives in two realistic codes: particle transport and the load balancing phase in QMC. Another important contribution of our work lies in showing that optimization techniques - such as double buffering - used with programmer controlled caches are also useful on MIC. These results can help optimize other communication intensive codes running on MIC.","PeriodicalId":311953,"journal":{"name":"2014 International Conference on Parallel, Distributed and Grid Computing","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121186640","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: 2

Performance evaluation of various symmetric encryption algorithms 各种对称加密算法的性能评估

2014 International Conference on Parallel, Distributed and Grid Computing Pub Date : 2014-12-01 DOI: 10.1109/PDGC.2014.7030724

Shaify Kansal, Meenakshi Mittal

引用次数: 29

Distributed pattern matching and document analysis in big data using Hadoop MapReduce model 基于Hadoop MapReduce模型的大数据分布式模式匹配与文档分析

2014 International Conference on Parallel, Distributed and Grid Computing Pub Date : 2014-12-01 DOI: 10.1109/PDGC.2014.7030762

A. Ramya, E. Sivasankar

{"title":"Distributed pattern matching and document analysis in big data using Hadoop MapReduce model","authors":"A. Ramya, E. Sivasankar","doi":"10.1109/PDGC.2014.7030762","DOIUrl":"https://doi.org/10.1109/PDGC.2014.7030762","url":null,"abstract":"Sequential pattern mining and Document analysis is an important data mining problem in Big Data with broad applications. This paper investigates a specific framework for managing distributed processing in dataset pattern match and document analysis context. MapReduce programming model on a Hadoop cluster is highly scalable and works with commodity machines with integrated mechanisms for fault tolerance. In this paper, we propose a Knuth Morris Pratt based sequential pattern matching in distributed environment with the help of Hadoop Distributed File System as efficient mining of sequential patterns. It also investigates the feasibility of partitioning and clustering of text document datasets for document comparisons. It simplifies the search space and acquires a higher mining efficiency. Data mining tasks has been decomposed to many Map tasks and distributed to many Task trackers. The map tasks find the intermediate results and send to reduce task which consolidates the final result. Both theoretical analysis and experimental result with data as well as cluster of varying size shows the effectiveness of MapReduce model primarily based on time requirements.","PeriodicalId":311953,"journal":{"name":"2014 International Conference on Parallel, Distributed and Grid Computing","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126847796","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

Hostile intent identification by movement pattern analysis: Using artificial neural networks 基于运动模式分析的敌对意图识别:利用人工神经网络

2014 International Conference on Parallel, Distributed and Grid Computing Pub Date : 2014-12-01 DOI: 10.13140/2.1.4429.7281

Souham Biswas, M. Nene

引用次数: 0

Distributed computing approach to optimize road traffic simulation 分布式计算方法优化道路交通仿真

2014 International Conference on Parallel, Distributed and Grid Computing Pub Date : 2014-12-01 DOI: 10.1109/PDGC.2014.7030771

A. Sinha, Tapas Saini, S. Srikanth

{"title":"Distributed computing approach to optimize road traffic simulation","authors":"A. Sinha, Tapas Saini, S. Srikanth","doi":"10.1109/PDGC.2014.7030771","DOIUrl":"https://doi.org/10.1109/PDGC.2014.7030771","url":null,"abstract":"Distributed computing is the method of running CPU intensive computations on multiple computers collectively in order to achieve a common objective. Common problems that can be solved on the distributed systems include climate/weather modeling, earthquake simulation, evolutionary computing problems and so on. These type of problems may involve billions or even trillions of computations. A single computer is not capable to finish these computations in short span of time, which is typically in days. Distributed computation helps to solve these problems in hours, which could take weeks to solve on a single computer. Distributed computing generally uses the existing resources of the organization. Traffic simulation is the process of simulating transportation systems through software on a virtual road network. Traffic simulation helps in analyzing city traffic at different time intervals of a single day. Common use cases could be analyzing city wide traffic, estimating traffic demand at a particular traffic junction and so on. This paper discusses about the approach to use distributed computing paradigm for optimizing the traffic simulations. Optimizing simulations involves running a number of traffic simulations followed by estimating the nearness of that simulation to the real available traffic data. This real data could be obtained by either manual counting at traffic junctions, or using the probes such as loop inductors, CCTV cameras etc. This distributed computing based approach works to find the best traffic simulation corresponding to the real data in hand, using evolutionary computing technique.","PeriodicalId":311953,"journal":{"name":"2014 International Conference on Parallel, Distributed and Grid Computing","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130350954","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: 8

Performance analysis of cloud based load balancing techniques 基于云的负载平衡技术的性能分析

2014 International Conference on Parallel, Distributed and Grid Computing Pub Date : 2014-12-01 DOI: 10.1109/PDGC.2014.7030714

Aayush Agarwal, G. Manisha, R. Milind, S. Shylaja

引用次数: 3

Challenges and issues in underwater acoustics sensor networks: A review 水声传感器网络的挑战与问题综述

2014 International Conference on Parallel, Distributed and Grid Computing Pub Date : 2014-12-01 DOI: 10.1109/PDGC.2014.7030751

Himanshu Jindal, S. Saxena, Singara Singh

{"title":"Challenges and issues in underwater acoustics sensor networks: A review","authors":"Himanshu Jindal, S. Saxena, Singara Singh","doi":"10.1109/PDGC.2014.7030751","DOIUrl":"https://doi.org/10.1109/PDGC.2014.7030751","url":null,"abstract":"The Underwater Acoustic Sensor Networks (UWASN) consists of sensors that are deployed underwater for gathering information for the unexplored parts of oceans or rivers. UWASN consists of variable number of floating and anchored sensors, sink and vehicles that are deployed over an area to be explored. The characteristics of UWASN are mainly node mobility for floating, capacity for data collection and recording and autonomous vehicles which are battery operable. The communication is possible among underwater devices through optical waves, radio waves, electromagnetic and acoustics. Out of these, acoustics communication is best suited as it can carry digital information through underwater channel and can travel to longer distances. The communication can be classified in two parts: Single and multi hoping. But in underwater we use multi-hop communication for sending data from end nodes to sink nodes. The various challenges to UWASN are limited bandwidth, multipath fading, limited battery, limited data capacity and delay in propagation. Hence, in this paper we have focussed on various issues and challenges in underwater wireless sensor networks for acoustic communications.","PeriodicalId":311953,"journal":{"name":"2014 International Conference on Parallel, Distributed and Grid Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131192449","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: 34

Thermal variance-aware application mapping for mesh based network-on-chip design using Kernighan-Lin partitioning 基于Kernighan-Lin分区的基于网格的片上网络设计的热方差感知应用映射

2014 International Conference on Parallel, Distributed and Grid Computing Pub Date : 2014-12-01 DOI: 10.1109/PDGC.2014.7030755

K. Manna, Vedic Choubey, S. Chattopadhyay, I. Sengupta

引用次数: 15

Cluster head selection technique for optimization of energy conservation in MANET 基于簇头选择的MANET节能优化技术

2014 International Conference on Parallel, Distributed and Grid Computing Pub Date : 2014-12-01 DOI: 10.1109/PDGC.2014.7030712

K. Govil, S. Gupta, A. Agarwal

引用次数: 25

Proposed optimized algorithm for coverage area with capacity calculation 提出了基于容量计算的覆盖面积优化算法

2014 International Conference on Parallel, Distributed and Grid Computing Pub Date : 2014-12-01 DOI: 10.1109/PDGC.2014.7030790

L. Sharma, H. Saini, Geetanjali Rathee, T. C. Panda

引用次数: 0