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A grid service for interactive dataset analysis

A grid service for interactive dataset analysis

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international symposium on parallel and distributed Processing (IPDPS)

作者： D.A. Alexander B. Miller T. Johnson M. Turri V. Serbo Tech-X Corporation Boulder CO USA Stanford Linear Accelerator Center Stanford CA USA

Summary form only given. Grid tools currently available are most often geared towards running batch-oriented dataset analysis jobs on a set of distributed heterogeneous computers in a production setting where the data is assumed to be in files, and do not automatically collect the results from multiple analysis jobs. This is insufficient for interactive dataset analysis, where complicated communications between the analysis jobs and the scheduler are required for interactivity and where datasets are abstracted from files, collections of files, database objects, and even virtual datasets for which only a generation algorithm exists. We describe a prototype for a system based on a set of grid services to provide interactive dataset analysis that extends the Globus Toolkit grid tools. An existing Java-based dataset analysis and visualization client tool are used to access the grid service and provide the interactive user interface for the client.

关键词： Data analysis Algorithm design and analysis distributed computing Grid computing Job production systems Processor scheduling Visual databases Scheduling algorithm Prototypes Java

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parallel genetic algorithms: advances, computing trends, applications and perspectives

Parallel genetic algorithms: advances, computing trends, app...

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international symposium on parallel and distributed Processing (IPDPS)

作者： Z. Konfrst Department of Cybernetics FEE Czech Technical University Prague Czech Republic

Summary form only given. This article gives a brief overview of theoretical advances, computing trends, applications and future perspectives in parallel genetic algorithms. It explains basic terms and behavior of (parallel) genetic algorithms. Genetic algorithms are easily parallelized algorithms, therefore two kinds of possible parallelism, data parallelism and control parallelism, are mentioned and described towards them. parallelism of genetic algorithms brings many advantages and gains. Classifications of these algorithms are often based on the type of computing model, a walk strategy and the used computing machinery. Afterwards significant milestones in the theory with latest advances are briefly mentioned. Then current trends in parallel computing with stress computer architectures of parallel systems, interconnection topologies, operating systems, parallel (genetic) libraries and programming paradigms are reviewed shortly. The sufficient space is devoted to the latest applications of parallel genetic algorithms. After the discussion section, perspectives of the algorithms are predicted till the year 2005. The information in the article is segregated into two periods before and after the year 2000 in all chapters. The second period is more interesting and of higher importance, because it highlights recent research efforts and gives some hints about possible future trends. That is why we devote much space to the second period. As there is no such an overview of the recent period of parallel genetic algorithms, our investigation could be appealing and useful in many aspects.

关键词： Genetic algorithms Computer applications Concurrent computing parallel processing Classification algorithms Machinery Stress Computer architecture Topology Operating systems

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Flecc: a flexible cache coherence protocol for dynamic component-based systems

Flecc: a flexible cache coherence protocol for dynamic compo...

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international symposium on parallel and distributed Processing (IPDPS)

作者： A. Ivan Vijay Karamcheti Computer Science Department Courant Institute of Mathematical Sciences New York University New York NY USA

Summary form only given. An increasing number of distributed applications are currently being constructed as sets of connected components and dynamically deployed in wide area networks using frameworks such as CORBA, .NET, and Web Services. Such dynamic deployments enable applications to flexibly adapt to changes in client QoS requirements and network properties, but introduce a consistency problem because of replicated components. Ideally, the frameworks deploying the applications should ensure that the application consistency requirements are satisfied, even though the requirements can range from weak to strong and dynamically change at run-time. Thus, a key challenge is to design a flexible cache coherence protocol that uses application-specific information while still being application-neutral. We describe Flecc, an application-neutral cache coherence protocol used by a component-based framework (Partitionable Services Framework) to satisfy the consistency requirements of deployed applications. Flecc allows applications to specify appropriate consistency and granularity levels and define complex synchronization decisions as simple functions. We demonstrate the benefits of our cache coherence protocol by analyzing the behavior of a component-based application modeling an airline reservation system.

关键词： Protocols distributed databases Web services Runtime Coherence File systems Switches Computer science Application software Wide area networks

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Construct a grid computing environment for bioinformatics

Construct a grid computing environment for bioinformatics

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international symposium on parallel Architectures, Algorithms and Networks (ISPAN)

作者： Yu-Lun Kuo Chao-Tung Yang Chuan-Lin Lai Tsai-Ming Tseng High-Performance Computing Laboratory Department of Computer Science and Information Engineering Tunghai University Taichung Taiwan

ISBN: (纸本)0769521355

Internet computing and grid technologies promise to change the way we tackle complex problems. They will enable large-scale aggregation and sharing of computational, data and other resources across institutional boundaries. And harnessing these new technologies effectively will transform scientific disciplines ranging from high-energy physics to the life sciences. The computational analysis of biological sequences is a kind of computation driven science. Cause the biology data growing quickly and these databases are heterogeneous. We can use the grid system sharing and integrating the heterogeneous biology database. As we know, bioinformatics tools can speed up analysis the large-scale sequence data, especially about sequence alignment. The FASTA is a tool for aligning multiple protein or nucleotide sequences. FASTA which we used is a distributed and parallel version. The software uses a message-passing library called MPl (Message Passing Interface) and runs on distributed workstation clusters as well as on traditional parallel computers. A grid computing environment is proposed and constructed on multiple Linux PC clusters by using Globus Toolkit (GT) and SUN Grid Engine (SGE). The experimental results and performances of the bioinformatics tool using on grid system are also presented in this paper.

关键词： Grid computing Bioinformatics Sequences Biology computing Large-scale systems databases Internet Physics Proteins Software libraries

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On modeling wireless sensor networks

On modeling wireless sensor networks

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international symposium on parallel and distributed Processing (IPDPS)

作者： D. Gracanin M. Eltoweissy S. Olariu A. Wadaa Department of Computer Science Virginia Technology Falls Church VA USA Department of Computer Science Old Dominion University Norfolk VA USA

Summary form only given. Most of the current research in wireless sensor networks (WSN, for short) is constraint driven and focuses on optimizing the use of limited resources (for example, power) at each sensor. While such constraints are important, there is a need for more general performance metrics describing the effectiveness of WSNs. There is also a need for a unified model that would enable comparison of different types of WSNs. We propose a new service-centric model that focuses on services provided by a WSN and their corresponding performance metrics. A WSN is modeled at different levels of abstraction. For each level, a set of services and a set of metrics are defined. A mapping between metrics at different levels relates high-level, mission-oriented metrics to low-level capability-oriented metrics. The proposed model consists of mission, network, region, sensor, and capability layers. Within each layer, four planes are identified, namely, communications, management, application, and generation learning. The proposed model provides a flexible, open framework for expressing and evaluating capabilities, functionalities, management, behavior, and evolution of a WSN. In addition, the proposed model provides a holistic approach to comparing WSNs and to measuring their effectiveness. The generation learning plane is unique in that it serves to extend the longevity of the network and to enhance the network effectiveness over time.

关键词： Wireless sensor networks Web services Measurement Sensor systems Computer science Quality of service Constraint optimization Operating systems Eyes distributed databases

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Utilizing home node prediction to improve the performance of software distributed shared memory

Utilizing home node prediction to improve the performance of...

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international symposium on parallel and distributed Processing (IPDPS)

作者： S. Peng Computer Systems Laboratory Cornell University Ithaca NY

Summary form only given. Many researchers use a home-based lazy release consistent protocol (HLRC) to provide a simple, effective, and scalable way to build software distributed shared memory (DSM) systems. However, the performance of HLRC is notoriously sensitive to the initial page distribution among home nodes. We propose an adaptive HLRC protocol in which the home page designation is able to change according to the observed application sharing pattern. Our system differs from HLRC and other adaptive derivatives in the following respects. First, the number of home nodes for each shared page can be varied, as opposed to having only a single home node. second, we use prediction in a novel way to dynamically change the the location of home nodes according to different memory access patterns. The home node of each shared page is able to propagate, perish, and migrate. An online home predictor determine whether or not the current node should remain a home node or drop from the current set of home nodes for a given page. Finally, all decisions concerning home node group membership are made locally, eliminating the costly global decision-making communication present in many other systems. Performance evaluations using six well-known DSM benchmarks show that our adaptive protocol outperforms conventional HLRC by up to 60%.

关键词： Software performance System performance Access protocols Coherence distributed computing Home computing Laboratories Application software Decision making Workstations

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Large-scale simulation of Eukaryotic cell signaling processes

Large-scale simulation of Eukaryotic cell signaling processe...

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international symposium on parallel and distributed Processing (IPDPS)

作者： J.M. Miller F. Zheng School of Electrical Engineering and Computer Science Washington State University Tri-Cities Richland WA USA

Summary form only given. A database of rate constants and related quantities has been assembled by Schoeberl et al. for intracellular signaling downstream of the epidermal growth factor receptor (EGFR). This information was combined with data on metalloprotease activation to build a model of autocrine signal transduction by cancer cells exposed to ionizing radiation. The model predicts prompt activation of mitogen-activated-protein-kinase (MAPK) pathways in response to a radiation-induced shift in the RasGDP /spl harr/ RasGTP equilibrium toward more RasGTP. A secondary MAPK activation is predicted due to metalloprotease activity that releases transforming growth factor alpha (TGF/spl alpha/), an autocrine ligand of EGFR. Model predictions were compared to data by Dent et al. on extracellular regulated kinase (ERK) activation following a 2 Gy exposure of carcinoma cells in vitro. Good agreement was obtained with the magnitude of prompt and secondary ERK activation; however, the experimental secondary response was delayed relative the prompt peak more than predicted by our model. A mechanistic understanding of radiation-induced growth factors is needed to improve treatment of cancer by radiation therapy. Inhibitors of the signaling pathways modeled in this study may reduce a potentially self-limiting aspect of radiation therapy whereby induced growth factors accelerate repopulation of treated tumor volumes.

关键词： Large-scale systems Signal processing Predictive models Cancer Biomedical applications of radiation databases Assembly Epidermis Ionizing radiation Extracellular

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Strategies for using additional resources in parallel hash-based join algorithms 04

Strategies for using additional resources in parallel hash-b...

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international symposium on High Performance distributed Computing

作者： Xi Zhang T. Kurc T. Pan U. Catalyurek S. Narayanan P. Wyckoff J. Saltz Dept. of Biomedical Informatics The Ohio State University Columbus OH USA Dept. of Biomedical Informatics The Ohio State University Columbus OH Ohio Supercomputer Center Columbus OH

Hash-based join is a compute- and memory-intensive algorithm. It achieves good performance and scales well to large datasets, if sufficient memory is available to hold the hash table and the distribution of computing had across nodes is balanced. We compare three adaptive algorithms that start with a partitioning of the hash table across a group of nodes and expand during the hash table building phase to additional resources, when memory on a node is used up. The split-based algorithm partitions the hash table range assigned to the node, on which memory is full, into two segments and assigns one of the segments to a new node in the system. The replication-based algorithm replicates the hash table range on a new node. The hybrid algorithm combines the first and second strategies in order to address each strategy's short comings. We perform an experimental performance evaluation of these algorithms on a PC cluster. Our results show that among the three algorithms, in most cases the hybrid algorithm either performs close to the better of the two or is the best algorithm.

关键词： Clustering algorithms Partitioning algorithms distributed computing Biomedical computing Filters Biomedical informatics Adaptive algorithm Performance evaluation databases Subcontracting

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A dichotomous algorithm for association rule mining

A dichotomous algorithm for association rule mining

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international Workshop on Database and Expert systems Applications

作者： T.-Y. Jen R. Taouil D. Laurent IT Department HELP Institute Kuala Lumpur Malaysia LI Université de Tours Blois France LICP Université de Cergy Pontoise Cergy-Pontoise France

The analysis of large amounts of data requires important computing resources that may not be available, even in current environment, and there are traditionally two main ways for solving this problem. The first is to use multiprocessor machines, and the second is to use computer clusters. The main drawbacks of these solutions are the expensive cost of machines and their specific utilization. In order to avoid these drawbacks, distributed algorithms for mining association rules have been proposed. However, these algorithms either run high-synchronous methods or lack flexibility to be adapted to machines with limited available resources. A distributed dichotomous algorithm (DDA) is proposed for association rule mining. The main features of DDA are that this algorithm does not require a high level of synchronization and that it does not process data replication and redundant calculations. In addition, DDA can partition recursively the tasks and the data set so as to be processed by machines with limited available resources.

关键词： Association rules Data mining Partitioning algorithms Clustering algorithms distributed algorithms Costs Concurrent computing Transaction databases Algorithm design and analysis parallel algorithms

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Discouraging free riding in a peer-to-peer CPU-sharing grid 04

Discouraging free riding in a peer-to-peer CPU-sharing grid

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international symposium on High Performance distributed Computing

作者： N. Andrade F. Brasileiro W. Cirne M. Mowbray Departamento de Sistemas e Computação Universidade Federal de Campina Grande Campina Grande Brazil HP Labs Bristol HP Labs Bristol UK

Grid computing has excited many with the promise of access to huge amounts of resources distributed across the globe. However, there are no largely adopted solutions for automatically assembling grids, and this limits the scale of today's grids. Some argue that this is due to the overwhelming complexity of the proposed economy-based solutions. Peer-to-peer grids Iwve emerged as a less complex alternative. We are currently deploying OurGrid, one such peer-to-peer grid. OurGrid is a CPU-sharing grid that targets bag-of-tasks applications (i.e. parallel applications whose tasks are independent). In order to ease system deployment, OurGrid is based on a very lightweight autonomous reputation scheme. Free riding is an important issue for any peer-to-peer system. The aim is to show that OurGrid's reputation system successfully discourages free riding, making it in each peer s own interest to collaborate with the peer-to-peer community. We show this in two steps. First, we analyze the conditions under which a reputation scheme can discourage free riding in a CPU-sharing grid. second, we show that OurGrid's reputation scheme satisfies these conditions, even in the presence of malicious peers. Unlike other distributed mechanisms for discouraging free riding, OurGrid's reputation scheme achieves this without requiring a shared cryptographic infrastructure or specialized storage.

关键词： Peer to peer computing Grid computing Collaboration distributed computing Cryptography Assembly Production systems Resource management Incentive schemes

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