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检索条件"任意字段=Proceedings of the IEEE Workshop on Advances in Parallel and Distributed Systems"

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The strategy of distributed load balancing based on hybrid scheduling

The strategy of distributed load balancing based on hybrid s...

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International workshop on Computational Transportation Science

作者： Shi, Jianhui Meng, Chunlei Ma, Lingli Department of Humanistic and Social Science Institute of Disaster Prevention Sanhe Hebei China Department of Urban Ecological Meteorology Institute of Urban Meteorology CMA Beijing China Surveying and Mapping Engineering Institute Sichuan Earthquake Administration Yaan Sichuan China

ISBN: (纸本)9780769543352

A strategy of distributed load balancing based on hybrid scheduling (LBHS) is proposed in this paper. This method is a hybrid scheduling strategy, which is based on the static allocation, and used dynamic scheduling system with the amply consideration of all the factors in the process of load balancing. This method can improve the utilization of the processor. The method is tested in the land surface disaster and ecology model. The result indicates that the strategy could improve the performance of parallel computing effectively, especially in the case that the size and data of the task is partially mastered beforehand. © 2011 ieee.

关键词： Scheduling

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Design considerations of a flexible data stream processing middleware

Design considerations of a flexible data stream processing m...

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15th East-European Conference on advances in Databases and Information systems: Research Communications, ADBIS 2011

作者： Cipriani, Nazario Grossmann, Matthias Sanftmann, Harald Mitschang, Bernhard Universität Stuttgart Institute of Parallel and Distributed Systems Universitässtraße 38 70569 Stuttgart Germany Universität Stuttgart Visualization Institute Universitätsstraße 38 70569 Stuttgart Germany

Techniques for efficient and distributed processing of huge, unbound data streams have made some impact in the database community. distributed data stream processing systems have emerged providing a distributed environment to process these potentially unbound streams of data by a set of processing nodes. A wide range of real-time applications process stream-based data. Sensors and data sources, such as position data of moving objects, continuously produce data that is consumed by, e.g., location-aware applications. Depending on the domain of interest, the processing of such data often depends on domain-specific functionality. For instance, an application which visualizes stream-based data has stringent timing constraints, or may even need a specific hardware environment to smoothly process the data. Furthermore, users may add additional constraints. E.g., for security reasons they may want to restrict the set of nodes that participates in processing. In this paper we review context-aware applications which, despite their different application fields, share common data processing principles. We analyse these applications and extract common requirements which data stream processing systems must meet to support these applications. Finally, we show how such applications are implemented using NexusDS, our extensible stream processing middleware.

关键词： Middleware

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PARSE 2.0: A tool for parallel application run time behavior evaluation

PARSE 2.0: A tool for parallel application run time behavior...

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International workshop on Specialized Ad Hoc Networks and systems

作者： Evans, Jeffrey J. Lucas, Charles E. Purdue University 401 N. Grant St. West Lafayette IN 47907 United States PC Krause and Associates Inc. 3000 Kent Avenue West Lafayette IN 47906 United States

ISBN: (纸本)9780769543864

Run time variability of parallel applications continues to be a significant challenge in high performance computing (HPC) systems. We are currently studying run time variability in the context of both systemic performance and energy management. Our perspective is from that of the application, focusing on the interactions of the inter-process communication system on the set of concurrently executing parallel applications. In such a scenario, application run time can be extended and become highly variable. While some applications may be more sensitive to these interactions, others may in fact be generating the interactions that cause inconsistent run time, thus forming the notion of application-level behavioral attributes. To gain insight into this problem, our earlier work developed a framework that emulates parallel applications, called PACE. We also introduced a parallel Application Run time Sensitivity Evaluation (PARSE) function that uses the PACE framework to study the run time effects of controlled network performance degradation on applications. Inter-process communication has evolved over the last decade from network communication between single-processor, single-core nodes to hybrid systems whose compute nodes contain several multi-core processor units. Motivated by the evolution of compute hardware and systems software, this work introduces PARSE 2.0, which is a nearly complete re-write that extends PARSE capabilities to include fully automating the processes of evaluating and quantifying run time critical parallel application-level behavioral attributes. We present an overview of the tool and the attributes being evaluated, and present experimental results from tests conducted on several widely used parallel benchmarks and application code fragments. The results re-enforce our earlier work, demonstrating that parallel applications can be classified according to their behavioral attributes, in the context of communication system resources. © 2011 ieee.

关键词： Hybrid systems

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Performance problems online detection in cloud computing systems via analyzing request execution paths

Performance problems online detection in cloud computing sys...

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workshop on Proactive Failure Avoidance, Recovery, and Maintenance

作者： Mi, Haibo Wang, Huaimin Yin, Gang Cai, Hua Zhou, Qi Sun, Tingtao National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China Computing Platform Alibaba Cloud Computing Company Hangzhou China

ISBN: (纸本)9781457703751

It is quite a headache for developers to online detect performance problems in large-scale cloud computing systems. The behavior and the hidden connections among the huge amount of runtime request execution paths in cloud computing systems usually contain useful information for performance problem detection. In this paper, we propose an approach to rapidly diagnose the source of performance degradation in large-scale non-stop cloud computing systems. The approach first groups the user requests into categories with a fast clustering algorithm;then applies the principal components analysis to extract the primary methods;finally compares the normal and abnormal behaviors of the primary methods to localize the main cause of performance problems. We conduct extensive experiments over a real-world enterprise system providing services for the public. The results show that our approach can locate the prime causes of performance problems accurately and efficiently.1 © 2011 ieee.

关键词： Cloud computing

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Identifying faults in large-scale distributed systems by filtering noisy error logs

Identifying faults in large-scale distributed systems by fil...

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workshop on Proactive Failure Avoidance, Recovery, and Maintenance

作者： Rao, Xiang Wang, Huaimin Shi, Dianxi Chen, Zhenbang Cai, Hua Zhou, Qi Sun, Tingtao National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha 410073 China Computing Platform Alibaba Cloud Computing Corporation Hangzhou China

ISBN: (纸本)9781457703751

Extracting fault features with the error logs of fault injection tests has been widely studied in the area of large scale distributed systems for decades. However, the process of extracting features is severely affected by a large amount of noisy logs. While the existing work tries to solve the problem by compressing logs in temporal and spatial views or removing the semantic redundancy between logs, they fail to consider the co-existence of other noisy faults that generate error logs instead of injected faults, for example, random hardware faults, unexpected bugs of softwares, system configuration faults or the error rank of a log severity. During a fault feature extraction process, those noisy faults generate error logs that are not related to a target fault, and will strongly mislead the resulted fault features. We call an error log that is not related to a target fault a noisy error log. To filter out noisy error logs, we present a similarity-based error log filtering method SBF, which consists of three integrated steps: (1) model error logs into time series and use haar wavelet transform to get the approximate time series;(2) divide the approximate time series into sub time series by valleys;(3) identify noisy error logs by comparing the similarity between the sub time series of target error logs and the template of noisy error logs. We apply our log filtering method in an enterprise cloud system and show its effectiveness. Compared with the existing work, we successfully filter out noisy error logs and increase the precision and the recall rate of fault feature extraction.1 © 2011 ieee.

关键词： Errors

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Exploring workflow interoperability tools for neuroimaging data analysis

Exploring workflow interoperability tools for neuroimaging d...

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6th workshop on Workflows in Support of Large-Scale Science, WORKS'11, Co-located with SC'11

作者： Korkhov, Vladimir Krefting, Dagmar Kukla, Tamas Terstyanszky, Gabor Z. Caan, Matthan Olabarriaga, Silvia D. Academic Medical Center Univ. of Amsterdam PO Box 22700 1100 DE Amsterdam NL Netherlands St. Petersburg State University Universitetskii prospekt 35 Petergof St. Petersburg Russia Charité - Universitätsmedizin Berlin Hindenburgdamm 30 12200 Berlin Germany Centre for Parallel Computing Univ. of Westminster 115 New Cavendish St W1W 6UAW London United Kingdom

ISBN: (纸本)9781450311007

Neuroimaging is a field that benefits from distributed computing infrastructures (DCIs) to perform data processing and analysis, which is often achieved using grid workflow systems. Collaborative research in neuroimaging requires ways to facilitate exchange between different groups, in particular to enable sharing, re-use and interoperability of applications implemented as workflows. The SHIWA project provides solutions to facilitate sharing and exchange of workflows between workflow systems and DCI resources. In this paper we present and analyse how the SHIWA platform was used to implement various usage scenarios in which workflow exchange supports collaboration in neuroscience. The SHIWA platform and the implemented solutions are described and analysed from the "user" perspective, in this case the workflow developers and the neuroscientists. We conclude that the platform in its current form is valuable for the foreseen usage scenarios, and we identify remaining challenges concerning management of multiple credentials and data transfers across DCIs. © 2011 ACM.

关键词： Interoperability

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ON THE PERFORMANCE AND COST OF SOME PRAM MODELS ON CMP HARDWARE

ON THE PERFORMANCE AND COST OF SOME PRAM MODELS ON CMP HARDW...

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10th workshop on advances in parallel and distributed Computational Models/22nd ieee International parallel and distributed Processing Symposium

作者： Forsell, Martti VTT Tech Res Ctr Finland Platform Architectures Team FI-90571 Oulu Finland

ISBN: (纸本)9781424416943

The parallel Random Access Machine is a very strong model of parallel computing that has resisted cost-efficient implementation attempts for decades. Recently, the development of VLSI technology has provided means for indirect on-chip implementation, but there are different variants of the PRAM model that provide different performance, area and power figures and it is not known how their implementations compare to each others. In this paper we measure the performance and estimate the cost of practical implementations of four PRAM models including EREW, Limited Arbitrary CRCW, Full Arbitrary CRCW, Full Arbitrary Multioperation CRCW on our Eclipse chip multiprocessor framework. Interestingly, the most powerful model shows the lowest simulation cost and highest performance/area and performance/power figures.

关键词： parallel computing PRAM performance silicon area power consumption

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A general lock-free algorithm for parallel state space construction

A general lock-free algorithm for parallel state space const...

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9th International workshop on parallel and distributed Methods in Verification, PDMC 2010 - Joint with the 2nd International workshop on High-Performance Computational systems Biology, HiBi 2010

作者： Saad, Rodrigo T. Dal Zilio, Silvano Berthomieu, Bernard

ISBN: (纸本)9780769542652

Verification via model-checking is a very demanding activity in terms of computational resources. While there are still gains to be expected from algorithmic improvements, it is necessary to take advantage of the advances in computer hardware to tackle bigger models. Recent improvements in this area take the form of multiprocessor and multicore architectures with access to large memory space. We address the problem of generating the state space of finitestate transition systems;often a preliminary step for modelchecking. We propose a novel algorithm for enumerative state space construction targeted at shared memory systems. Our approach relies on the use of two data structures: a shared Bloom filter to coordinate the state space exploration distributed among several processors and local dictionaries to store the states. The goal is to limit synchronization overheads and to increase the locality of memory access without having to make constant use of locks to ensure data integrity. Bloom filters have already been applied for the probabilistic verification of systems;they are compact data structures used to encode sets, but in a way that false positives are possible, while false negatives are not. We circumvent this limitation and propose an original multiphase algorithm to perform exhaustive, deterministic, state space generations. We assess the performance of our algorithm on different benchmarks and compare our results with the solution proposed by Inggs and Barringer. © 2010 ieee.

关键词： Locks (fasteners)

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Exploring multi-grained parallelism in compute-intensive DEVS simulations 10

Exploring multi-grained parallelism in compute-intensive DEV...

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24th Annual workshop on Principles of Advanced and distributed Simulation, PADS 2010

作者： Liu, Qi Wainer, Gabriel Department of Systems and Computer Engineering Carleton University Ottawa ON Canada

ISBN: (纸本)9781424472918

We propose a computing technique for efficient parallel simulation of compute-intensive DEVS models on the IBM Cell processor, combining multi-grained parallelism and various optimizations to speed up the event execution. Unlike most existing parallelization strategies, our approach explicitly exploits the massive fine-grained event-level parallelism inherent in the simulation process, while most of the logical processes are virtualized, making the achievable parallelism more deterministic and predictable. Together, the parallelization and optimization strategies produced promising experimental results, accelerating the simulation of a 3D environmental model by a factor of up to 33.06. The proposed methods can also be applied to other multicore and shared-memory architectures. © 2010 ieee.

关键词： parallel processing systems

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DiVinE: parallel distributed model checker

DiVinE: Parallel distributed model checker

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9th International workshop on parallel and distributed Methods in Verification, PDMC 2010 - Joint with the 2nd International workshop on High-Performance Computational systems Biology, HiBi 2010

作者： Barnat, J. Brim, L. Češka, M. Ročkai, P. Faculty of Informatics Masaryk University Botanicka 68a 60200 Brno Czech Republic

ISBN: (纸本)9780769542652

Model checking became a standard method of analyzing complex systems in many application domains. No doubt, a number of applications is placing great demands on model checking tools. The process of analysis of complex and real-life systems often requires vast computation resources, memory in particular. This phenomenon, referred to as the state space explosion problem, has been tackled by many researchers during the past two decades. A plethora of more or less successful techniques to fight the problem have been introduced, including parallel and distributed-memory processing. DiVinE is a tool for LTL model checking and reach ability analysis of discrete distributed systems. The tool is able to efficiently exploit the aggregate computing power of multiple network-interconnected multi-cored workstations in order to deal with extremely large verification tasks. As such it allows to analyze systems whose size is far beyond the size of systems that can be handled with regular sequential tools. While the main focus of the tool is on high-performance explicit state model checking, an emphasis is also put on ease of deployment and usage. Additionally, the component architecture and publicly available source code of Divine allow for its usage as a platform for research on parallel and distributed-memory model checking techniques. © 2010 ieee.

关键词： Model checking

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