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检索条件"任意字段=IASTED International Conference on Parallel and Distributed Computing and Networks, PDCN 2007"

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Task allocation method for avoiding contentions by the information of concurrent communications

Task allocation method for avoiding contentions by the infor...

引用

10th iasted international conference on parallel and distributed computing and networks, pdcn 2011

作者： Morie, Yoshiyuki Nanri, Takeshi Kurokawa, Motoyoshi Research Institute for Information Technology Kyushu University 6-10-1 Hakozakl Higashi-Ku Fukuoka Japan Advanced Center for Computing and Communication RIKEN Wako Japan

ISBN: (纸本)9780889868649

This paper proposes an optimization method of task-allocation for reducing contentions. There have been some attempts for optimizing task-allocation that minimizes the product of the amount of communications and the number of the communication hops. However, since those methods do not consider the occurrence of contentions, the effect has not been sufficient. The method proposed in this paper uses information of concurrent communication to estimate the effect of contentions to find the optimal task-allocation. In three environments examined on the experiments, the proposed method has shown a better effect than the existing method on two environments, tree and fat tree. On these environments, the maximum gain of performance over the existing method was about 25%. On the other hand, on a mesh environment, IBM BlueGene/L, the existing method better effect than the proposed method. As one of the reasons for this, the influence of the packet priority on the network of BlueGene/L to the behavior of the proposed method is discussed.

关键词： Network topology

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On the tradeoff between speedup and energy consumption in high performance computing - A bioinformatics case study

On the tradeoff between speedup and energy consumption in hi...

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9th iasted international conference on parallel and distributed computing and networks, pdcn 2010

作者： Pawaskar, Sachin Ali, Hesham H. Department of Computer Science College of Information Science and Technology University of Nebraska at Omaha Omaha NE 68182 United States

ISBN: (纸本)9780889868205

High Performance computing has been very useful to researchers in the Bioinformatics, Medical and related fields. The bioinformatics domain is rich in applications that require extracting useful information from very large and continuously growing sequence of databases. Automated techniques such as DNA sequencers, DNA microarrays & others are continually growing the dataset that is stored in large public databases such as GenBank and Protein DataBank. Most methods used for analyzing genetic/protein data have been found to be extremely computationally intensive, providing motivation for the use of powerful computers or systems with high throughput characteristics. In this paper, we provide a case study for one such bioinformatics application called BLAT running in a high performance computing environment. We use sequences gathered from researchers and parallelize the runs to study the performance characteristics under three different query and data partitioning models. This research highlights the need to carefully develop a parallel model with energy awareness in mind, based on our understanding of the application and then appropriately designing a parallel model that works well for the specific application and domain. We found that the BLAT program is highly parallelizable and a high degree of speedup is achievable. The experiments suggest that the speed up depends on model used for query and database segmentation.

关键词： Bioinformatics

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An adaptive multi-agent approach for distributed alarm correlation and fault identification

An adaptive multi-agent approach for distributed alarm corre...

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9th iasted international conference on parallel and distributed computing and networks, pdcn 2010

作者： Mohamed, Abduljalil A. Basir, Otman Department of Systems Design Engineering University of Waterloo Waterloo ON Canada Department of Electrical and Computer Engineering University of Waterloo Waterloo ON Canada

ISBN: (纸本)9780889868205

Network fault management systems rely heavily on observed alarms to identify the root causes of network failures. Due to the increasing complexity of modern computer networks, the information carried by these alarms may in fact be vague, imprecise, and inconsistent. Thus, these alarms often possess different diagnostic capabilities and should not be treated equally. In this paper, we propose a new distributed alarm correlation approach that effectively tackles the aforementioned data deficiencies. According to the proposed approach, the managed network is first divided into a disjoint set of management domains and each domain is assigned an intelligent agent. Within the framework of Dempster-Shafer evidence theory, the intelligent agent perceives each network entity in its domain as a source of information. As such, alarms emitted by these entities are expected to exhibit different information qualities and are assigned different weights accordingly. Based on their weights, the observed alarms are then correlated by their respective agent into a single local fuzzy composite alarm. Since local composite alarms constitute only partial views of the managed network, they are correlated, by a higher management entity, into a global alarm that accurately reflects a comprehensive view of the managed network.

关键词： Alarm systems

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Efficient data service design for a SOA approach to scientific computing

Efficient data service design for a SOA approach to scientif...

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10th iasted international conference on parallel and distributed computing and networks, pdcn 2011

作者： Mulerikkal, Jaison Paul Strazdins, Peter School of Computer Science Australian National University Canberra Australia

ISBN: (纸本)9780889868649

In recent years, the Service Oriented Architecture (SOA) has evolved itself into emerging technologies like cloud computing to give it more relevance. ANU-SOAM - a service oriented middleware - aims to provide convenient API, a unique data service extension and proper load-balancing techniques for high performance scientific computing. The data service extension offers both Common Data Service (CDS) and Local Data Service (LDS). CDS helps set data common to all service instances and to manipulate it using add, get, put, sync, etc. functions. The LDS allows consumer to partially replicate data among service instances to improve memory scalability. Comparable paradigms like MPI are mostly agnostic and non-responsive to heterogeneous conditions. The SOA approach enables ANU-SOAM to have load balancing techniques implemented with the help of a Resource Manager. Experiments using N Body Solver and Heat Transfer applications have shown that ANU-SOAM performs as good as most of its MPI counterparts, especially under heterogeneous conditions.

关键词： Cloud computing

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Comparison of table join execution time for parallel DBMS and MapReduce

Comparison of table join execution time for parallel DBMS an...

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12th iasted international conference on parallel and distributed computing and networks, pdcn 2014

作者： Burdakov, Aleksey V. Grigorev, Uriy A. Ploutenko, Andrey D. Bauman Moscow State Technical University 2ya Baumanskaya 5 Moscow 105005 Russia Amur State University 21 Ignatievskoe sh. Blagoveschensk Amurskaya obl. 675000 Russia

Analysis of existing research work indicates that preference for implementation of queries to structured data is given to parallel DBMS. MapReduce (MR) is perceived as supplementary to DBMS technology. We attempt to figure out behavior pattern of parallel rowstorage DBMS and MR system Hadoop on the example of Join task depending on the variation of the parameters that in other authors' experiments do not vary or differ from ours. This article presents detailed process models for table joins in the parallel row-storage DBMS and MRsystem, as well as the results of detailed calculation experiments performed on these models. The models were set up for various scalability schemes for MR (number of nodes) and DMBS (data volume in a node) and fragmentation of the joined tables by the primary key. The following parameters were varied: queried data selectivity, number of sorted resulting records and cardinality of the grouping attribute. The modeling results showed that with the increase of the stored data volume parallel DBMS starts losing against MR-system at certain thresholds.

关键词： MapReduce

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parallel nearest neighbour clustering algorithm (PNNCA) for segmenting retinal blood vessels

Parallel nearest neighbour clustering algorithm (PNNCA) for ...

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international conference on parallel and distributed computing and networks

作者： Salem, Sameh A. Nandi, Asoke K. Univ Liverpool Dept Elect & Elect Engn Signal Proc & Commun Grp Liverpool L69 3GJ Merseyside England

ISBN: (纸本)9780889866379

In this paper, the design and implementation of a recently developed clustering algorithm NNCA [1], Nearest Neighhour Clustering Algorithm, is proposed in conjunction with a Fast K Nearest Neighbour (FKNN) strategy for further reduction in processing time. The parallel algorithm (PNNCA) has the ability to cluster pixels of retinal images into those belonging to blood vessels and others not belonging to blood vessels in a reasonable time.

关键词： parallel processing retinal image segmentation data clustering unsupervised classification computer clusters

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QoS management in distributed service oriented systems

QoS management in distributed service oriented systems

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international conference on parallel and distributed computing and networks

作者： Korostelev, Andrei Lukkien, Johan Nesvadba, Jan Qian, Yuechen Eindhoven Univ Technol Dept Math & Comp Sci POB 513 NL-5600 MB Eindhoven Netherlands

ISBN: (纸本)9780889866379

The paper presents an approach to QoS management in distributed service oriented systems. We study the approach by the example of the Cassandra Framework developed at Philips Research. Cassandra is a distributed video/audio streaming and analysis platform consisting of a collection of loosely-coupled services, which can be easily combined to build distributed applications. To manage QoS of the system, two QoS attributes are selected: availability and performance. We tackle these issues in a service oriented fashion, making the system tolerant to service failures and adaptable to varying requirements of the applications.

关键词： SOA QoS availability performance

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parallelization strategy for Hierarchical Run Length Encoded data structures

Parallelization strategy for Hierarchical Run Length Encoded...

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10th iasted international conference on parallel and distributed computing and networks, pdcn 2011

作者： Filipović, Lado Ertl, Otmar Selberherr, Siegfried Institute for Microelectronics TU Wien Gußhausstraße 27-29/E360 A-1040 Wien Austria

ISBN: (纸本)9780889868649

An efficient parallelization strategy is presented for a Hierarchical Run Length Encoded (HRLE) data structure, implemented for the Sparse Field Level Set method. In order to achieve high parallel efficiency, computational work must be distributed evenly over all available CPU threads. Since the Level Set surface must be allowed to deform and evolve, thereby increasing the simulation area, there must exist a way to increase the surface domain while keeping an efficient parallelization strategy in place. This is achieved by processing the same number of calculations across each available CPU. The addition of data to HRLE data structures is only permitted in a sequential or lexicographical order, making parallelization more complex. The presented solution uses as many HRLE data structures as there are CPUs available. Approximately 90% of operations can be performed in parallel when using the presented strategy, leading to an efficiency of up to 96% or 78.5% when using two or sixteen CPU cores of an AMD Opteron 8435 processor, clocked at 2.6GHz, respectively. Topographies with one and two moving interfaces were simulated using multi-threading, showing the speedup and efficiency for the presented strategy.

关键词： parallel programming

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Reexamining the parallelization schemes for standard full tableau simplex method on distributed memory environments

Reexamining the parallelization schemes for standard full ta...

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10th iasted international conference on parallel and distributed computing and networks, pdcn 2011

作者： Mamalis, Basilis Pantziou, Grammati Dimitropoulos, Georgios Kremmydas, Dimitrios Technological Educational Institute of Athens Ag. Spyridonos 12210 Egaleo Greece Agricultural University of Athens Iera Odos 75 11855 Athens Greece

ISBN: (纸本)9780889868649

The simplex method has been successfully used in solving linear programming problems for many years. parallel approaches have also extensively been studied due to the intensive computatios required (especially for the solution of large in size linear problems). In this paper we present a highly scaleable parallel implementation framework of the standard full tableau simplex method on a highly parallel (distributed memory) environment. Specifically, we have designed and implemented a column distribution scheme (similar to the one presented in [24]) as well as a row distribution scheme (similar to the one presented in [3]) and we have entirely tested our implementations over a considerably powerful parallel environment (a linux-cluster of eight powerful Xeon processors connected via a high speed Myrinet network interface). We then compare our approaches (a) among each other for variable number of problem size (number of rows and columns) and (b) to the corresponding ones of [3] and [24] which are two of the most recent and valuable corresponding efforts. In most cases the column distribution scheme performs quite/much better than the row distribution scheme. Moreover, both schemes (even the row distribution scheme over large scale problems) lead to particularly high speed-up and efficiency values, that are considerably better in all cases than the ones achieved by the corresponding implementations of [3] and [24].

关键词： Linear programming

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Power-efficient load distribution in heterogeneous computing environments

Power-efficient load distribution in heterogeneous computing...

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12th iasted international conference on parallel and distributed computing and networks, pdcn 2014

作者： Lenhardt, Joerg Schiffmann, Wolfram Eitschberger, Patrick Keller, Joerg Computer Architecture Group FernUniversität in Hagen Germany Parallelism and VLSI Group FernUniversität in Hagen Germany

High performance servers of heterogeneous computing environments, as can be found in data centers for cloud computing, consume immense amounts of energy even though they are usually underutilized. In times when not all computing capabilities are needed the task to be solved is how to distribute the computational load in a power-efficient manner. The question to be answered is, what load partitions should be assigned to each physical server so that all work is done with minimal energy consumption. This problem is closely related to the selection of physical servers that can be switched off completely to further reduce the power consumption. In this work, we present algorithms which calculate a power-efficient distribution of a divisible workload among multiple, heterogeneous physical servers. We assume a fully divisible load to calculate an optimized utilization of each server. Based on this distribution, an iterative process is carried out to identify servers, which can be switched off in order to further reduce the power consumption. With that information, workload (re)distribution can take place to partition appropriate subloads to the remaining servers. As before, the calculated partitioning minimizes the power consumption.

关键词： Electric power utilization

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