2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops & PhD Forum最新文献_第9页

Discovering Cellular Automata Rules for Binary Classification Problem with Use of Genetic Algorithm 利用遗传算法发现二元分类问题的元胞自动机规则

2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops & PhD Forum Pub Date : 2012-05-21 DOI: 10.1109/IPDPSW.2012.81

A. Piwonska, F. Seredyński, M. Szaban

引用次数: 1

On Running Windowed Image Computations on a Pipeline 关于在管道上运行窗口图像计算

2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops & PhD Forum Pub Date : 2012-05-21 DOI: 10.1109/IPDPSW.2012.100

R. Vaidyanathan, Phaneendra Vinukonda

{"title":"On Running Windowed Image Computations on a Pipeline","authors":"R. Vaidyanathan, Phaneendra Vinukonda","doi":"10.1109/IPDPSW.2012.100","DOIUrl":"https://doi.org/10.1109/IPDPSW.2012.100","url":null,"abstract":"Many image processing operations manipulate an individual pixel using the values of other pixels in the given pixel's neighborhood. Such operations are called windowed operations. The size of the windowed operation is a measure of the size of the given pixel's neighborhood. A windowed computation applies a windowed operation on all pixels of the image. An image processing application is typically a sequence of windowed computations. While windowed computations admit high parallelism, the cost of inputting and outputting the image often restricts the computation to a few computational units. In this paper we analytically study the running of a sequence of z windowed computations, each of size w, on a z-stage pipelined computational model. For an N × N image and n × n input/output bandwidth per stage, we show that the sequence of windowed computations can be run in N2/n2 (1 + δ) steps, where δ = (n/N + 3n2/wN + zw/N). This produces a speed-up of z/1+δ over a single stage. Generally, N ≫ n >; z, w; so the overhead, δ, is dominated by the term which is typically small. This also indicates the time to be relatively independent of the number of stages z.","PeriodicalId":378335,"journal":{"name":"2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops & PhD Forum","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131419107","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: 1

MapReduce Based Skyline Services Selection for QoS-aware Composition 基于MapReduce的qos感知组合的Skyline服务选择

2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops & PhD Forum Pub Date : 2012-05-21 DOI: 10.1109/IPDPSW.2012.253

Liang Chen, Li Kuang, Jian Wu

引用次数: 7

Statistics-based Workload Modeling for MapReduce 基于统计的MapReduce工作负载建模

2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops & PhD Forum Pub Date : 2012-05-21 DOI: 10.1109/IPDPSW.2012.254

Hailong Yang, Zhongzhi Luan, Wenjun Li, D. Qian, Gang Guan

{"title":"Statistics-based Workload Modeling for MapReduce","authors":"Hailong Yang, Zhongzhi Luan, Wenjun Li, D. Qian, Gang Guan","doi":"10.1109/IPDPSW.2012.254","DOIUrl":"https://doi.org/10.1109/IPDPSW.2012.254","url":null,"abstract":"Large-scale data-intensive computing with MapReduce framework in Cloud is becoming pervasive for the core business of many academic, government, and industrial organizations. Hadoop is by far the most successful realization of MapReduce framework. While MapReduce is easy-to-use, efficient and reliable for data-intensive computations, the excessive configuration parameters in Hadoop cause unexpected challenges when running various workloads with Hadoop cluster effectively. Consequently, developers who have less experience with the Hadoop configuration system may devote a significant effort to write an application with poor performance, because they have no idea how these configurations would influence the performance, or they are not even aware that these configurations exist. In this paper, we propose a statistic analysis approach to identify the relationships among workload characteristics, Hadoop configurations and workload performance. Several non-intuitive relationships between workload characteristics and relative performance are revealed and the experimental results demonstrate that our regression models accurately predict the performance of MapReduce workloads under different Hadoop configurations.","PeriodicalId":378335,"journal":{"name":"2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops & PhD Forum","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132385312","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: 24

On-line Batch Scheduling in Distributed Optical Networks 分布式光网络中的在线批调度

2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops & PhD Forum Pub Date : 2012-05-21 DOI: 10.1109/IPDPSW.2012.109

Yang Wang, Xiaojun Cao, A. Caciula, Qian Hu

{"title":"On-line Batch Scheduling in Distributed Optical Networks","authors":"Yang Wang, Xiaojun Cao, A. Caciula, Qian Hu","doi":"10.1109/IPDPSW.2012.109","DOIUrl":"https://doi.org/10.1109/IPDPSW.2012.109","url":null,"abstract":"Batch scheduling accommodates a group of tasks with the start/end time constraints to maximize the revenue from scheduling tasks over a number of servers, which has been extensively studied in the context of Job-machine scheduling. In optical networks, batch scheduling refers to the process of scheduling a group of data units (i.e., the jobs) that competing for the same set of wavelength channels (i.e., the machines). Classical Job-machine scheduling studies considered both the case of a pure-loss system, and the case with waiting rooms (i.e., buffers), which are generally in the form of Random Access Memory (RAM). In optical networks, the buffering is achieved by feeding the optical signal into a fixed length of fiber, namely Fiber Delay Lines, since optical RAM is not yet available. The unique feature of the discrete and predefined buffering time in fact instantiates a new type of problem, namely Job-machine scheduling with Discrete-time Buffers. In this work, we comprehensively study batch scheduling in optical networks. We show that batch scheduling with and without FDLs corresponds to two different instances of Job-machine scheduling problem. While proving their NP-Completeness, we mathematically model both cases using Integer Linear Programming formulations to provide an optimal scheduling. Given the timeliness request for on-line batch scheduling and the dramatic problem size in optical networks, we also propose polynomial-time heuristic algorithms, which are shown to be near-optimal in our simulations.","PeriodicalId":378335,"journal":{"name":"2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops & PhD Forum","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132439279","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: 1

The Development of Parallel Adaptive Sampling Algorithms for Analyzing Biological Networks 生物网络分析中并行自适应采样算法的发展

2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops & PhD Forum Pub Date : 2012-05-21 DOI: 10.1109/IPDPSW.2012.90

K. Dempsey, K. Duraisamy, S. Bhowmick, H. Ali

{"title":"The Development of Parallel Adaptive Sampling Algorithms for Analyzing Biological Networks","authors":"K. Dempsey, K. Duraisamy, S. Bhowmick, H. Ali","doi":"10.1109/IPDPSW.2012.90","DOIUrl":"https://doi.org/10.1109/IPDPSW.2012.90","url":null,"abstract":"The availability of biological data in massive scales continues to represent unlimited opportunities as well as great challenges in bioinformatics research. Developing innovative data mining techniques and efficient parallel computational methods to implement them will be crucial in extracting useful knowledge from this raw unprocessed data, such as in discovering significant cellular subsystems from gene correlation networks. In this paper, we present a scalable combinatorial sampling technique, based on identifying maximum chordal sub graphs, that reduces noise from biological correlation networks, thereby making it possible to find biologically relevant clusters from the filtered network. We show how selecting the appropriate filter is crucial in maintaining the key structures from the original networks and uncovering new ones after removing noisy relationships. We also conduct one of the first comparisons in two important sensitivity criteria - the perturbation due to the vertex numbers of the network and perturbations due to data distribution. We demonstrate that our chordal-graph based filter is effective across many different vertex permutations, as is our parallel implementation of the sampling algorithm.","PeriodicalId":378335,"journal":{"name":"2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops & PhD Forum","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128131133","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: 14

Scalable Hybrid Implementation of Graph Coloring Using MPI and OpenMP 使用MPI和OpenMP的图形着色的可伸缩混合实现

2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops & PhD Forum Pub Date : 2012-05-21 DOI: 10.1109/IPDPSW.2012.216

Ahmet Erdem Sarıyüce, Erik Saule, Ümit V. Çatalyürek

引用次数: 14

Defeating against Sybil-attacks in Peer-to-peer Networks 在点对点网络中击败sybil攻击

2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops & PhD Forum Pub Date : 2012-05-21 DOI: 10.1109/IPDPSW.2012.149

X. Xiang

引用次数: 4

Towards High-Level Programming of Multi-GPU Systems Using the SkelCL Library 利用SkelCL库实现多gpu系统的高级编程

2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops & PhD Forum Pub Date : 2012-05-21 DOI: 10.1109/IPDPSW.2012.229

Michel Steuwer, Philipp Kegel, S. Gorlatch

引用次数: 20

A Comparison of DAG and Mesh Topologies for Coarse-Grain Reconfigurable Array 粗粒度可重构阵列的DAG和网格拓扑比较

2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops & PhD Forum Pub Date : 2012-05-21 DOI: 10.1109/IPDPSW.2012.24

Jonathan Antusiak, Antoine Trouvé, K. Murakami

引用次数: 6