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international conference on Peer-to-Peer computing

作者： R. Delaviz N. Andrade J. A. Pouwelse Parallel and Distributed Systems Group Department of Computer Science Delft University of Technnology Netherlands

P2P systems can benefit from reputation mechanisms to promote cooperation and help peers to identify good service providers. However, in spite of a large number of proposed reputation mechanisms, few have been investigated in real situations. BarterCast is a distributed reputation mechanism used by our Internet-deployed Bittorent-based file-sharing client Tribler. In BarterCast, each peer uses messages received from other peers to build a weighted, directed subjective graph that represents the upload and download activity in the system. A peer calculates the reputations of other peers by applying the maxflow algorithm to its subjective graph. For efficiency reasons, only paths of at most two hops are considered in this calculation. In this paper, we identify and assess three potential modifications to BarterCast for improving its accuracy and coverage (fraction of peers for which a reputation value can be computed). First, a peer executes maxflow from the perspective of the node with the highest betweenness centrality in its subjective graph instead of itself. Second, we assume a gossiping protocol that gives each peer complete information about upload and download activities in the system, and third, we lift the path length restriction in the maxflow algorithm. To assess these modifications, we crawl the Tribler network and collect the upload and download actions of the peers for three months. We apply BarterCast with and without the modifications on the collected data and measure accuracy and coverage.

关键词： Peer to peer computing Accuracy Crawlers Protocols Testing Training Measurement

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Finding Tropical Cyclones on a Cloud computing Cluster: Using parallel Virtualization for Large-Scale Climate Simulation Analysis

Finding Tropical Cyclones on a Cloud Computing Cluster: Usin...

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IEEE international conference on Cloud computing Technology and Science (CloudCom)

作者： D. Hasenkamp A. Sim M. Wehner K. Wu Lawrence Berkeley National Laboratory USA

Extensive computing power has been used to tackle issues such as climate changes, fusion energy, and other pressing scientific challenges. These computations produce a tremendous amount of data, however, many of the data analysis programs currently only run a single processor. In this work, we explore the possibility of using the emerging cloud computing platform to parallelize such sequential data analysis tasks. As a proof of concept, we wrap a program for analyzing trends of tropical cyclones in a set of virtual machines (VMs). This approach allows the user to keep their familiar data analysis environment in the VMs, while we provide the coordination and data transfer services to ensure the necessary input and output are directed to the desired locations. This work extensively exercises the networking capability of the cloud computing systems and has revealed a number of weaknesses in the current cloud system software. In our tests, we are able to scale the parallel data analysis job to a modest number of VMs and achieve a speedup that is comparable to running the same analysis task using MPI. However, compared to MPI based parallelization, the cloud-based approach has a number of advantages. The cloud-based approach is more flexible because the VMs can capture arbitrary software dependencies without requiring the user to rewrite their programs. The cloud-based approach is also more resilient to failure, as long as a single VM is running, it can make progress while as soon as one MPI node fails the whole analysis job fails. In short, this initial work demonstrates that a cloud computing system is a viable platform for distributed scientific data analyses traditionally conducted on dedicated supercomputing systems.

关键词： Meteorology Virtual machining Lead Analytical models Data models Tropical cyclones Computational modeling

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distributed classification using class-association rules mining algorithm

Distributed classification using class-association rules min...

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international conference on Machine and Web Intelligence (ICMWI)

作者： Djamila Mokeddem Hafida Belbachir Department of Computer Sciences LSSD Laboratory University of Sciences and Technology-Mohamed Boudiaf Oran Algeria

Associative classification algorithms have been successfully used to construct classification systems. The major strength of such techniques is that they are able to use the most accurate rules among an exhaustive list of class-association rules. This explains their good performance in general, but to the detriment of an expensive computing cost, inherited from association rules discovery algorithms. We address this issue by proposing a distributed methodology based on FP-growth algorithm. In a shared nothing architecture, subsets of classification rules are generated in parallel from several data partitions. An inter-processor communication is established in order to make global decisions. This exchange is made only in the first level of recursion, allowing each machine to subsequently process all its assigned tasks independently. The final classifier is built by a majority vote. This approach is illustrated by a detailed example, and an analysis of communication cost.

关键词： Classification algorithms Program processors Association rules Algorithm design and analysis Itemsets Training data

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Logical optimization of dataflows for data mining and integration processes

Proceedings - 6th IEEE International Conference on e-Science...

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Proceedings - 6th IEEE international conference on e-Science Workshops, e-ScienceW 2010 2010年 117-122页

作者： Wöhrer, Alexander Mehofer, Eduard Brezany, Peter University of Vienna Faculty of Computer Science Department of Scientific Computing Vienna Austria

ISBN: (纸本)9780769542959

Modern scientific collaborations require large-scale data mining and integration processes. Their investigations involve multi-disciplinary expertise and large-scale computational experiments on top of large amounts of data that are located in distributed data repositories running various software systems, and managed by different organizations. Higher-level dataflow languages are used on top of parallel dataflow systems to enable faster program development and more maintainable code. Logical and physical optimization should be applied prior to its execution to improve performance. In this paper we present the rationale, theory, design and application of logical optimization of dataflows for data mining and integration processes. A dataflow model is defined and several optimization algorithms, namely dead elements elimination, process re-ordering, parallelization, and data by-passing are developed. The first research prototype of the framework has been implemented in the context of the ADMIRE Data Mining and Integration Process Designer for logical optimization of specifications expressed in the DISPEL language developed in the ADMIRE project. © 2010 IEEE.

关键词： Data integration

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Cross-Layer Design to Merge Structured P2P Networks over MANET

Cross-Layer Design to Merge Structured P2P Networks over MAN...

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international conference on parallel and distributed systems (ICPADS)

作者： Nadir Shah Depei Qian Sino-German Joint Software Institute Beihang University Beijing China

Peer-to-peer (P2P) network is an alternative of client/server system for sharing resources, e.g. files. P2P network is a robust, distributed and fault tolerant architecture. There are basic two types of P2P networks, structured P2P network and unstructured P2P network. Each of them has its own applications and advantages. Due recent advances in wireless and mobile technology, the P2P network can be deployed over mobile ad hoc network (MANET). We consider the scenarios of P2P network over MANET where all nodes are not the members of P2P network. Due to limited radio range and the mobility of nodes in MANET, there can occur network partition and merging of networks in the physical network. This can also lead to P2P network partition and merging at overlay layer. When two physical networks merge by coming into communication range of each other then their P2P networks would not be connected at overlay layer. Because P2P network operates at application layer as an overlay network. That is their P2P networks are connected in physical network but these P2P networks are disconnected at overlay layer. To detect this situation and merge these P2P networks at overlay layer, we extend the ODACP, an address auto-configuration protocol. Then we propose an approach to efficiently merge P2P networks such that routing traffic is minimized. Considering limited radio range and mobility of nodes, the simulation results shows that CAN over MANET performs better as compared to Chord over MANET in term of routing traffic and false-negative ratio.

关键词： Peer to peer computing Mobile ad hoc networks Merging Routing Bridges IP networks Network topology

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Real-time distributed tracking with non-overlapping cameras

Real-time distributed tracking with non-overlapping cameras

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IEEE international conference on Image Processing

作者： Youlu Wang Li He Senem Velipasalar Department of Electrical Engineering University of Nebraska Lincoln Lincolnshire NE USA

We present a real-time distributed system for tracking with non-overlapping camera views. Each camera performs multi-object tracking, and cameras communicate with each other in a peer-to-peer manner for consistent labeling. To match objects across non-overlapping views, we employ multiple features, namely color histogram, height, travel time and speed. First, camera configuration and reference values of different features are learned in the training phase. Then, we combine multiple evidences by computing an overall similarity score, which is a weighted sum of the similarity scores of different features. Communication and frame processing run in parallel and share memory. Experimental results show the success of the presented system in real-time tracking with non-overlapping cameras and in handling merge cases.

关键词： Cameras Histograms Image color analysis Real time systems Training Image edge detection Target tracking

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Power analysis and optimizations for GPU architecture using a power simulator

Power analysis and optimizations for GPU architecture using ...

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international conference on Advanced Computer Theory and Engineering, ICACTE

作者： Guibin Wang National Laboratory of Parallel and Distributed Processing School of Computer National University of Defense Technology Changsha Hunan China

ISBN: (纸本)9781424465392

As one of the most popular many-core architecture, GPUs have illustrated power in many non-graphic applications. Traditional general purpose computing systems tend to integrate GPU as the co-processor to accelerate parallel computing tasks. Meanwhile, GPUs also result in high power consumption, which accounts for a large proportion of the total system power consumption. In this paper, we mainly focus on the power analysis and optimizations for GPU architecture. The main contributions of this paper are: firstly, we establish a GPU power research platform, which is extended from an existing GPU simulator with several power models; secondly, we validate that, as the gap between shader core and memory speed becomes larger and larger, integrating more shader cores or enhancing running frequencies may not bring better performance, but results in higher energy consumption; thirdly, we show that traditional power optimization methods for CPUs, such as dynamic frequency scaling and concurrency-throttling, could be effectively applied on GPU architectures for better power efficiency, especially for memory-intensive applications.

关键词： Computational modeling Benchmark testing Graphics processing unit Arrays Analytical models Clocks Integrated circuit interconnections

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Task allocation in distributed database system design 10

Task allocation in distributed database system design

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Proceedings of the international conference and Workshop on Emerging Trends in Technology

作者： Gautam Borkar Leena M. Borkar Prashant Jawade

ISBN: (纸本)9781605588124

Task allocation in distributed database systems is an research problem. In DDBS systems Data & operation allocation are both closely interrelated & highly dependent on each other. Here it is represented along with model of allocation and development of such a model in general. Task allocation Models, Algorithms, Issues and Tools, General models and objective function explained in this paper. It can be treated as basic platform for research in this area of task allocation. The characteristics of DDBS like distributed data, distributed operations from query tree and result file are mentioned as tools to be taken in this field of research. An objective function can be derived by modifying the terms present in general model, which in turn depend on characteristics of the system concerned ex. distributed computing system, distributed database system, parallel system & multiprocessors etc.

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Optimization and Implementation of LBM Benchmark on Multithreaded GPU

Optimization and Implementation of LBM Benchmark on Multithr...

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international conference on Data Storage and Data Engineering (DSDE)

作者： Xiaoguang Ren Yuhua Tang Guibin Wang Tao Tang Xudong Fang National Laboratory of Parallel and Distributed Processing School of Computer National University of Defense Technology Changsha China

ISBN: (纸本)9781424456789;9780769539584

With fast development of transistor technology, Graphic Processing Unit(GPU) is increasingly used in the non-graphics applications, and major GPU hardware vendors have introduced software stacks for their own GPUs, such as Brook+ for AMD GPU. Compared with the traditional parallel systems, heterogeneous systems integerating stream-based multi-threaded GPUs provide higher parallel computing capabilities with lower cost. However, porting traditional applications to the heterogeneous systems makes new demand of application optimization on GPU. Based on the AMD's Brook+ platform, we explored application optimization features on AMD GPU by optimizing and implementing the benchmark LBM from SPEC2006. To improve the program locality, we optimized the original data layout of LBM. Using the short vector data types mechanism provided by Brook+, we also optimized the GPU's bandwidth utilization and its thread processors' efficiency. Through the branch elimination technique, we reduced the performance lose caused by branch divergences in the kernel, which is due to the GPU's SIMD executing mode. The experiment results show that data layout, memory bandwidth, branch paths and other factors have a close effect on the performance of program execution on the GPU. Through all the optimizations, we finally got a speedup of 22x (single-precision) and 19x (double-precision) over the original serial benchmark code on a Quad-core CPU, and a speedup of 4x (single-precision) and 8.7x (double-precision) over the original OMP benchmark code on a 8-core CPU.

关键词： Application software Graphics processing unit parallel processing Computer architecture Biomedical computing Computational fluid dynamics Computational modeling

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Multi-level topology-aware and multi-level parallelism on Grid computing environments: A comparison of Global Arrays and Open MP implementations

Multi-level topology-aware and multi-level parallelism on Gr...

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international conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON

作者： Sirod Sirisup Suriya U-ruekolan Large-Scale Simulation Research Laboratory National Electronics and Computer Technology Center Klong Luang Pathum Thani Thailand

ISBN: (纸本)9781424456062;9789746724913

The Global Arrays toolkit is a library that allows programmers to write parallel programs that use large arrays distributed across processing nodes through the Aggregate Remote Memory Copy Interface (ARMCI). OpenMP is an application programming interface that supports shared memory multiprocessing on many architectures and platforms. In the Symmetric-Multi Processors (SMP), the Global Arrays toolkit will expose the programmers quite similar to that provided by OpenMP. In this study, we will further our investigation on the performance of a parallel application implemented with the Global Arrays toolkit and OpenMP on Grid computing environment. The investigation focuses on the case that an SMP cluster is included in the Grid computing environment. The multi-level parallelism together with multi-level topology-aware techniques have been used in both implementations. We have found that performance of the evaluating application implemented with Global Arrays technique is comparable to that of the application implemented with OpenMP. This implies that programmer can directly port the Global Arrays application directly to the SMP cluster yet its performance is not dropped compared to the native implementation.

关键词： parallel processing Grid computing Libraries Network topology Concurrent computing Programming profession Computer networks Large-scale systems Aggregates Delay

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