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12th international conference on Algorithms and Architectures for parallel Processing, ICA3PP 2012

作者： Rizvandi, Nikzad Babaii Taheri, Javid Moraveji, Reza Zomaya, Albert Y. Centre for Distributed and High Performance Computing School of IT University of Sydney Australia Australian Technology Park Australia

ISBN: (纸本)9783642330773

Recently, businesses have started using MapReduce as a popular computation framework for processing large amount of data, such as spam detection, and different data mining tasks, in both public and private clouds. Two of the challenging questions in such environments are (1) choosing suitable values for MapReduce configuration parameters - e.g., number of mappers, number of reducers, and DFS block size-, and (2) predicting the amount of resources that a user should lease from the service provider. Currently, the tasks of both choosing configuration parameters and estimating required resources are solely the users' responsibilities. In this paper, we present an approach to provision the total CPU usage in clock cycles of jobs in MapReduce environment. For a MapReduce job, a profile of total CPU usage in clock cycles is built from the job past executions with different values of two configuration parameters e.g., number of mappers, and number of reducers. then, a polynomial regression is used to model the relation between these configuration parameters and total CPU usage in clock cycles of the job. We also briefly study the influence of input data scaling on measured total CPU usage in clock cycles. this derived model along with the scaling result can then be used to provision the total CPU usage in clock cycles of the same jobs with different input data size. We validate the accuracy of our models using three realistic applications (WordCount, Exim MainLog parsing, and TeraSort). Results show that the predicted total CPU usage in clock cycles of generated resource provisioning options are less than 8% of the measured total CPU usage in clock cycles in our 20-node virtual Hadoop cluster. © 2012 Springer-Verlag.

关键词： MapReduce

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BIGS: A framework for large-scale image processing and analysis over distributed and heterogeneous computing resources

BIGS: A framework for large-scale image processing and analy...

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IEEE international conference on e-Science and Grid computing

作者： Raúl Ramos-Pollán Fabio A. González Juan C. Caicedo Angel Cruz-Roa Jorge E. Camargo Jorge A. Vanegas Santiago A. Pérez Jose David Bermeo Juan Sebastián Otálora Paola K. Rozo John E. Arévalo Bioingenium Research Group at Universidad Nacional de Colombia Bogotá Colombia Universidad Nacional de Colombia Bogota CO

this paper presents BIGS the Big Image Data Analysis Toolkit, a software framework for large scale image processing and analysis over heterogeneous computing resources, such as those available in clouds, grids, computer clusters or throughout scattered computer resources (desktops, labs) in an opportunistic manner. through BIGS, eScience for image processing and analysis is conceived to exploit coarse grained parallelism based on data partitioning and parameter sweeps, avoiding the need of inter-process communication and, therefore, enabling loosely coupled computing nodes (BIGS workers). It adopts an uncommitted resource allocation model where (1) experimenters define their image processing pipelines in a simple configuration file, (2) a schedule of jobs is generated and (3) workers, as they become available, take over pending jobs as long as their dependency on other jobs is fulfilled. BIGS workers act autonomously, querying the job schedule to determine which one to take over. this removes the need for a central scheduling node, requiring only access by all workers to a shared information source. Furthermore, BIGS workers are encapsulated within different technologies to enable their agile deployment over the available computing resources. Currently they can be launched through the Amazon EC2 service over their cloud resources, through Java Web Start from any desktop computer and through regular scripting or SSH commands. this suits well different kinds of research environments, both when accessing dedicated computing clusters or clouds with committed computing capacity or when using opportunistic computing resources whose access is seldom or cannot be provisioned in advance. We also adopt a NoSQL storage model to ensure the scalability of the shared information sources required by all workers, including within BIGS support for HBase and Amazon's DynamoDB service. Overall, BIGS now enables researchers to run large scale image processing pipelines in an easy, affo

关键词： Pipelines Schedules Databases Feature extraction Biomedical imaging Computers

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Validation of computational prediction of horizontal gene transfer events-XenoCluster

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JOURNAL OF SUPERcomputing 2011年第2期57卷 141-150页

作者： Walters, Jesse D. Bair, thomas B. Braun, Terry A. Scheetz, Todd E. Robinson, John P. Casavant, thomas L. Univ Iowa Coordinated Lab Computat Genom Iowa City IA 52242 USA Univ Iowa Dept Elect & Comp Engn Iowa City IA 52242 USA Univ Iowa Ctr Bioinformat & Computat Biol Iowa City IA 52242 USA Univ Iowa Dept Ophthalmol & Visual Sci Iowa City IA 52242 USA Univ Iowa Dept Biomed Engn Iowa City IA 52242 USA

In this paper, we assess the biological accuracy and relevance of XenoCluster results compared to a reported set of known xenologs in yeast (Hall et al. Eukaryot. Cell 4(6):1102-1115, 2005). We were able to assign a high-priority rank to all reported yeast xenologs for which we had sufficient genomic sequence data. Additionally, we now report on a fine-grained extension to our previous implementation (Walters et al. 8th international parallel computing technologies conference (PaCT), LNCS, vol. 3606, pp. 355-366, Springer, Berlin, 2005), in which we achieved 80% efficiency on 8 CPU cores. In the coarse-grained component, high degrees parallelism (up to 65x speedup on 4,096 processors) was reported. While an obvious candidate for coarse-grained implementation, this paper now describes a multiple granularity parallelism solution that includes exploitation of multicore shared memory nodes to address fine-grained aspects in the tree-clustering phase of our previous deployment of XenoCluster (Walters et al. 8th international parallel computing technologies conference (PaCT), LNCS, vol. 3606, pp. 355-366, Springer, Berlin, 2005).

关键词： Multi-scale parallel computing Genome annotation DNA Evolution

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parallel immune algorithm for lung cancer detection in X-ray images based on object shared space

Parallel immune algorithm for lung cancer detection in X-ray...

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2011 12th international conference on parallel and distributed computing, applications and technologies, PDCAT 2011

作者： Peng, Gang Yang, Xiong Liu, Li Dept. of Computer Science and Technology Huizhou University Huizhou City Guangdong 516007 China

ISBN: (纸本)9780769545646

this paper discusses a parallel immune algorithm (IA) for detection of lung cancer in chest X-ray images based on object shared space. the template matching method is combined to the algorithm and JavaSpaces is used as object shared space. the experiment results show that the algorithm is efficient for detecting suspected lung cancer in chest X-ray images. © 2011 IEEE.

关键词： Diseases

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Unleash your memory-constrained applications: A 32-node non-coherent distributed-memory prototype cluster

Unleash your memory-constrained applications: A 32-node non-...

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13th IEEE international Workshop on FTDCS 2011, the 8th international conference on ATC 2011, the 8th international conference on UIC 2011 and the 13th IEEE international conference on HPCC 2011

作者： Montaner, Héctor Silla, Federico Fröning, Holger Duato, José Universitat Politècnica de València Departament d'Informàtica de Sistemes I Computadors Camino de Vera s/n 46022 Valencia Spain University of Heidelberg Computer Architecture Group Building B 68131 Mannheim Germany

ISBN: (纸本)9780769545387

Improvements in hardware for parallel shared-memory computing usually involve increments in the number of computing cores and in the amount of memory available for a given application. However, many shared-memory applications do not require more computing cores than available in current motherboards because their scalability is bounded to a few tens of parallel threads. Nevertheless, they may still benefit from having more memory resources. Additionally, the performance of extended systems involving more cores is typically constrained by the glueing coherency protocol, whose overhead lowers the performance of the final system. In this paper we present a 32-node prototype of a new non-coherent distributed-memory architecture for clusters, aimed to provide applications additional memory borrowed from other nodes without providing them more cores, thus avoiding the penalty of maintaining coherency among nodes of the cluster. Results from the execution of real applications in this prototype demonstrate that our proposal truly works, as well as its performance is assessed. © 2011 IEEE.

关键词： Cluster computing

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A multi-constraint preemption algorithm for parallel job scheduling

A multi-constraint preemption algorithm for parallel job sch...

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2011 12th international conference on parallel and distributed computing, applications and technologies, PDCAT 2011

作者： Luo, Hongbing Wu, Linping Wang, Wei Applied Physics and Computional Mathematics High Performance Computing Center Institute 100094 Beijing China

ISBN: (纸本)9780769545646

Using effective scheduling strategies to improve turnaround time, slowdown, and utilization is an important consideration in large supercomputing environments. Since such machines have traditionally used non-preemption strategies to accommodate multiple jobs at the same time, a number of questions remain unanswered regarding the practical effect of preemptive scheduling. In this paper, we first discuss how to improve the turnaround time, slowdown, and utilization using an appropriate suspension criterion. We then develop a new multi-constraint preemptive scheduling algorithm (MCPS). Finally, we describe the experiments on a simulator with several realistic workloads. the experimental results show that MCPS is better than the conventional no-preemption strategies, and outperforms other preemptive scheduling strategies by its balanced performance. © 2011 IEEE.

关键词： Scheduling algorithms

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Proceedings - 2011 IEEE international conference on High Performance computing and Communications, HPCC 2011 - 2011 IEEE international Workshop on Future Trends of distributed computing Systems, FTDCS 2011 - Workshops of the 2011 international conference on Ubiquitous Intelligence and computing, UIC 2011 - Workshops of the 2011 international conference on Autonomic and Trusted computing, ATC 2011

Proceedings - 2011 IEEE International Conference on High Per...

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13th IEEE international Workshop on FTDCS 2011, the 8th international conference on ATC 2011, the 8th international conference on UIC 2011 and the 13th IEEE international conference on HPCC 2011

ISBN: (纸本)9780769545387

the proceedings contain 142 papers. the topics discussed include: distributed caching strategies in peer-to-peer systems;a power-aware based storage architecture for high performance computing;a distributed reconfigurable active SSD platform for data intensive applications;a parallel processing scheme for large-size sliding-window applications;algebraic models for the cube connected cycles and shuffle exchange graphs;a high-performance and energy-efficient virtually tagged stack cache architecture for multi-core environments;providing quality of science in volunteer computing;an effective dynamic scheduling runtime and tuning system for heterogeneous multi and many-core desktop platforms;on the social aspects of personalized ranking for web services;stable adaptive work-stealing for concurrent multi-core runtime systems;rule pattern parallelization of packet filters on multi-core environments;and memory-intensive applications on a many-core processor.

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8th international conference on Autonomic computing, ICAC 2011 Co-located Workshops - Proceedings of the 3rd Workshop on Biologically Inspired Algorithms for distributed Systems, BADS 2011

8th International Conference on Autonomic Computing, ICAC 20...

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3rd Workshop on Bio-Inspired and Self-Algorithms for distributed Systems, Co-located with the 8th IEEE/ACM international conference on Autonomic computing, ICAC 2011

ISBN: (纸本)9781450307338

the proceedings contain 7 papers. the topics discussed include: memetic algorithm for web service selection;model-driven performance engineering for wireless sensor networks with feature modeling and event calculus;description and composition of bio-inspired design patterns: the gradient case;methods for self-organizing distributed software;protein structure prediction using particle swarm optimization and a distributed parallel approach;discrete optimization problem solving with three variants of hybrid binary particle swarm optimization;and self-organized invasive parallel optimization.

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Trusted Block as a Service: Towards Sensitive applications on the Cloud

Trusted Block as a Service: Towards Sensitive Applications o...

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Int Joint conference of 10th IEEE Int Conf on Trust, Security and Privacy in computing and Communications (TrustCom) / 8th IEEE Int Conf on Embedded Software and Systems (ICESS) / 6th Int Conf on Frontier of Computer Science and Technology (FCST)

作者： Hao, Jianan Cai, Wentong Nanyang Technol Univ Sch Comp Engn Parallel & Distributed Comp Ctr Singapore Singapore

ISBN: (纸本)9780769546001

Cloud computing grows rapidly as today's advanced information technology. However, by allowing outsourcing computation on the Cloud, users risk of disclosing privacy and obtaining forged results. these potential threats block sensitive applications to join the Cloud. In this paper, we characterize sensitive applications on the Cloud (SAND) problem and define two critical security requirements: confidentiality and verifiability. the former refers to the protection of sensitive programs/data from disclosing to other users or even the Cloud administrators. the latter concerns with user's capability to verify whether computing results are faithfully calculated. To address SAND, we propose a new Cloud model, Trusted Block as a Service (TBaaS), to provide a confidential and verifiable environment for each sensitive application. TBaaS limits Cloud provider's access of sensitive applications while granting user the ability to verify whether the computation is faithfully carried out. Moreover, it offers high flexibility and low performance overhead.

关键词： Cloud computing Cryptography Hypervisor Information Security Trusted computing

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Secure E-commerce based on distributed processing

Secure E-commerce based on distributed processing

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2011 12th international conference on parallel and distributed computing, applications and technologies, PDCAT 2011

作者： Peng, Kun Institute for Inforcomm Research Singapore

ISBN: (纸本)9780769545646

A new secret-sharing-based e-auction scheme is proposed. distributed bid opening is employed to protect bid privacy. It can achieve all the desired properties for sealed-bid auctions at a reasonable cost. Moreover, attacks existing in the current secret-sharing-based sealed-bid e-auction schemes are prevented in the new scheme. In addition, it does not need any trust assumption. © 2011 IEEE.

关键词： distributed processing electronic commerce Secure Scheme Privacy

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