Porting to the cloud large scientific applications designed and optimized for a standard HPC facility does not always pay off, mainly because of the implied communication pattern. By profiling the applications, resear...
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ISBN:
(纸本)9781728116440
Porting to the cloud large scientific applications designed and optimized for a standard HPC facility does not always pay off, mainly because of the implied communication pattern. By profiling the applications, researchers can build a performance model, which is able to give insights about how the application will perform on the cloud. To validate this approach, we use a hemodynamic application that embeds both heavy computations and extensive communications with several collective operations to exchange data across all processes. We expect that this case instance is a model for other applications. Our approach is based on profiling and modeling, and builds an analytical model for the communication pattern of the chosen hemodynamic application. We collect data both on an on-premise HPC system and on the Google Cloud infrastructure, and assess the prediction based on the analytic model. The outcome suggests that the prediction consistently underestimates the actual execution time, but correctly guess the scalability, thus allowing to strike a good balance between performance and costs. Finally, we introduce a figure of merit to assess cost vs performance between cloud and on-premise implementation, and validate a first version of such a model.
With the rapid development of Internet technology, online applications have become an indispensable part of government, enterprise and engineering fields. Most enterprises have utilized the advantages of cloud computi...
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ISBN:
(纸本)9781538637906
With the rapid development of Internet technology, online applications have become an indispensable part of government, enterprise and engineering fields. Most enterprises have utilized the advantages of cloud computing and refactored the applications with the service-oriented architecture (SOA) in order to solve the huge number of online users, soaring data and fluctuant load. According to the cloud services quality which evaluated in different cloud computing resources, developer choose the suitable size of the service cluster to meet the needs of enterprise services in the distributed service cluster. It can not only ensure the stable operation of online applications, but also maximize the reduction of basic costs. Therefore, it is important to evaluate the quality of cloud services accurately. This paper proposes an evaluation method of cloud service quality based on queuing model. The M/M/1 and M/M/s queuing models are used to analyze and evaluate the quality of single node service and cluster service respectively. By the method proposed in this paper can not only choose the suitable size of the service cluster for online applications, but also perform dynamic scheduling of cloud resources. Finally, the feasibility and practicability of this method is verified by experiments.
The problem of solving tridiagonal linear systems on paralleldistributed-memory environments is considered in this paper. In particular, two common direct methods for solving such systems are considered: odd-even cyc...
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The problem of solving tridiagonal linear systems on paralleldistributed-memory environments is considered in this paper. In particular, two common direct methods for solving such systems are considered: odd-even cyclic reduction and prefix summing. For each method, a variety of lower bounds on execution time for solving tridiagonal linear systems are presented. Specifically, lower bounds are presented that (a) hold when the number of data items per processor is bounded, (b) are general lower bounds, and (c) for specific data layouts commonly used in designing parallel algorithms to solve tridiagonal linear systems. Furthermore, algorithms are presented that have running times within a constant factor of the lower bounds provided. Lastly, a comparison of bounds for odd-even cyclic reduction and prefix summing is given.
This paper presents our research towards efficient Demand Migration Systems (DMSs) in the General Intensional Programming System (GIPSY) environment. Basically, a DMS is the combination ofboth paradigms ofEvent-Driven...
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ISBN:
(纸本)1601320841
This paper presents our research towards efficient Demand Migration Systems (DMSs) in the General Intensional Programming System (GIPSY) environment. Basically, a DMS is the combination ofboth paradigms ofEvent-Driven Architecture and Message-Oriented Middleware. From the design perspective, a DMS is an instance ofthe Demand Migration Framework, which establishes the context to perform demand migration in the heterogeneous and distributed GIPSY environment. In this paper, we present our design and implementation approach to DMS based on JINI and JMS. Further, we benchmark these two versions by performing early experimental investigations to evaluate their behavior, capabilities and limitations for demand migration. The article concludes with a comprehensive conclusion, based on our experimental results.
Increase in intensive applications with different computational requirements, coupled with the unification of remote and diverse resources thanks to advances in the wide-area network technologies and the low cost of c...
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ISBN:
(纸本)9780769527840
Increase in intensive applications with different computational requirements, coupled with the unification of remote and diverse resources thanks to advances in the wide-area network technologies and the low cost of components, have-encouraged the development of grid computing. To exploit the promising potentials of geographically distributed resources, effective and efficient mapping algorithms are fundamental. Since the problem of optimally mapping is NP-complete, the development of evolutionary techniques to find near-optimal solutions is welcome. In this paper a distributed system based on Differential Evolution is designed and implemented to face the mapping problem in a gild environment aiming at reducing the degree of use of the grid resources. This system is tested on some different resource allocation scenarios.
The Travelling Salesman Problem (TSP) is one of the typical combinatorial optimization problems that is easy to describe but hard to solve. In this work, we present a novel solution that integrates a genetic algorithm...
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ISBN:
(纸本)9781538637906
The Travelling Salesman Problem (TSP) is one of the typical combinatorial optimization problems that is easy to describe but hard to solve. In this work, we present a novel solution that integrates a genetic algorithm, local-search heuristics, and a greedy algorithm. For the genetic algorithm we keep the evolutionary technique to generate children from parents, which uses operators like mutation, selection of the most fitted element, and crossover, but the latter is enhanced with a local-search heuristic. We also use the local search heuristic for its strong climbing ability, as well as to find local optima efficiently in the TSP space. The greedy algorithm is used to generate new greedy children from parents. The experimental evaluation shows that the optimization algorithm presented provides higher quality solutions for TSP with respect to previous genetic algorithms, within reasonable computational time.
Functional safety is aimed at avoiding unacceptable risks and safety damages due to system functional failures, and it is a critical demand for the automotive embedded systems. For safety-critical distributed automoti...
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ISBN:
(纸本)9781538637906
Functional safety is aimed at avoiding unacceptable risks and safety damages due to system functional failures, and it is a critical demand for the automotive embedded systems. For safety-critical distributed automotive functions, reliability is an important functional safety requirement and reliability goal should be assured. In general, the key of reliability goal assurance method is to transfer the reliability goal of a distributed function to that of each task. This study proposes an effective reliability goal assurance method called RGAGM for automotive functional safety. The core idea of this method is defining two kinds of geometric mean for tasks and function, respectively, and preassigning geometric mean-based reliability values for unassigned tasks, thereby saving more resources for systems. The correctness of the proposed RGAGM method is proved. Experiment results on the real-life automotive function and the randomly generated distributed automotive functions show that the proposed method can effectively ensure the reliability goal and reduce resource consumption cost compared with the stateof-the-art MRCRG method.
Efficient processing of similarity joins is important for a large class of data analysis and data-mining applications. This primitive finds all pairs of records within a predefined distance threshold of each other. Ho...
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ISBN:
(纸本)9780769539393
Efficient processing of similarity joins is important for a large class of data analysis and data-mining applications. This primitive finds all pairs of records within a predefined distance threshold of each other. However, most of the existing approaches have been based on spatial join techniques designed primarily for data in a vector space. Treating data collections as metric objects brings a great advantage in generality, because a single metric technique can be applied to many specific search problems quite different in nature. In this paper, we concentrate our attention on a special form of join, the Self Similarity Join, which retrieves pairs from the same dataset. In particular, we consider the case in which the dataset is split into subsets that are searched for self similarity join independently (e.g, as in a distributed computing environment). To this end, we formalize the abstract concept of epsilon-Cover, prove its correctness, and demonstrate its effectiveness by applying it to two real implementations on a real-life large dataset.
In the previous research, the assessment of author's influence is mainly based on the historical information of literature, such as the number of author's publications and times cited, and the reference relati...
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ISBN:
(纸本)9781538637906
In the previous research, the assessment of author's influence is mainly based on the historical information of literature, such as the number of author's publications and times cited, and the reference relationship. However, the author influence is not only reflected in the amount of static data, but also in the behavior that the author's point of view is noticed and communicated. Meanwhile, the influence spreads through the relational path of cooperation and citation between authors, on which the authors should have similar academic interests. Therefore, this paper proposed an influence spreading model with the author's co-citation interest similarity and the path of citation and cooperation. On the basis of this, a novel algorithm of influence spreading prediction is designed, and carried on the experiment verification using the public literature information resources. The results of AUC indicator show the effectiveness on the proposed method.
The extreme scale, complexity and performance variability of future high performance computing systems pose many new challenges to parallel programming models and runtime systems. The Open Community Runtime (OCR) is a...
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ISBN:
(纸本)9781467387767
The extreme scale, complexity and performance variability of future high performance computing systems pose many new challenges to parallel programming models and runtime systems. The Open Community Runtime (OCR) is a recent effort for a task-based runtime system for extreme scale parallel systems. We have implemented the OCR specification in a shared-memory environment on top of TBB, providing an alternative to the implementation created by the OCR consortium. We have created an experimental extension that supports parallel accelerators programmed with OpenCL. We also have an implementation that targets distributed-memory systems. Despite being in an early stage of development, our implementations can achieve reasonable performance with some applications. We describe the main aspects of our OCR implementations and report on early experimental results on shared-memory and distributed-memory systems.
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