There is great potential if one could effectively harness the computation power of the plethora of low priced powerful yet under-utilized workstations connected by high-speed networks. In recent years, rapid improveme...
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There is great potential if one could effectively harness the computation power of the plethora of low priced powerful yet under-utilized workstations connected by high-speed networks. In recent years, rapid improvement of advanced hardware and progress in networking technology is also making PC clusters a competitive platform for parallelcomputing. Traditionally, cluster programming has been performed with message passing libraries. As the performance, especially the latency, of the communication network improves, the expectation to support a shared-memory programming model on clusters is reviving. In this paper, we put forward a system having both a distributed shared memory cluster and heterogeneous computers as system nodes which can support automatic distribution, migration, communication and coordination of multithreaded applications on a heterogeneous platform. This will be a creative application-driven experimental infrastructure that will explore challenging problems in distribution management and control, in middleware integration and deployment, in software architecture and software engineering.
This paper proposes two distributed algorithms for the heuristic solution of the Steiner Tree Problem in Network (SPN). The problem has a practical application in the construction of a minimum cost distribution tree f...
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ISBN:
(纸本)088986392X
This paper proposes two distributed algorithms for the heuristic solution of the Steiner Tree Problem in Network (SPN). The problem has a practical application in the construction of a minimum cost distribution tree for multicast transmission. Multicast transmission represents a necessary lower network service for the wide diffusion of new multimedia network applications. Currently, given the lack of efficient distributed methods, the existing protocols build the multicast distribution tree using some selected central node. The proposed distributed algorithms allow the construction of effective distribution trees using a coordination protocol among the network nodes. The algorithms have been implemented and tested both in simulation and on experimental active networks, and their performance values are presented.
Scheduling the execution of computing tasks for heterogeneous computing systems is a widely studied problem in the field of parallel and distributedcomputing. Many algorithms belong to list scheduling algorithms in w...
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ISBN:
(纸本)9780889867741
Scheduling the execution of computing tasks for heterogeneous computing systems is a widely studied problem in the field of parallel and distributedcomputing. Many algorithms belong to list scheduling algorithms in which tasks are scheduled sequentially in the order of their pre-assigned priorities. The determination of task priorities is typically based on problem-specific heuristics, which is critical to the performance of a list scheduling algorithm. We design a list scheduling algorithm for heterogeneous computing systems in which task priorities are determined by both the completion time and upward rank of a task. We extend the notion of upward ranks used in HEFT and our method of calculating a task's upward rank improves over the method used in HEFT, with the inclusion of additional domain knowledge embedded in scheduling problems. As a result, more accurate estimation of the execution time of remaining tasks can be achieved. Experimental results on benchmark task graphs show that our algorithm consistently outperforms HEFT with higher execution speedups.
Built from a need for modelling cognitive processes, a modular neural network is designed as the "brain" of a virtual robot moving in a prey-predator environment. The robot decides its path from the animals ...
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Built from a need for modelling cognitive processes, a modular neural network is designed as the "brain" of a virtual robot moving in a prey-predator environment. The robot decides its path from the animals it identifies around. Both a parallel implementation of distributed processes and a temporal coding of spiking neurons allow the robot to develop multimodal' perception with attentional mechanisms and to react in real-time to its dynamic environment.
In the last few years one of the most interesting questions in IT world is that of convergence between data and voice networks. This procedure cuts down overall expenses of implementation, usage and support of a telep...
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In the last few years one of the most interesting questions in IT world is that of convergence between data and voice networks. This procedure cuts down overall expenses of implementation, usage and support of a telephone network, as the expenses of other telephone. Beside the procedures that are prerequisite for the realization of this concept (e.g. ensuring the quality of the transferred voice), it is necessary to ensure the security of that traffic from various threats «inherited» from data traffic. This paper is about preventive protection of voice traffic transferred through a converged data/voice network.
A wide range of planning applications are combinatorial in nature, making the design of general purpose planning algorithms a still very challenging endeavor. In order to cope with this combinatorial complexity, some ...
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A wide range of planning applications are combinatorial in nature, making the design of general purpose planning algorithms a still very challenging endeavor. In order to cope with this combinatorial complexity, some of the most recent work in artificial intelligence (AI) planning focuses on the use of sophisticated heuristics, domain search control knowledge, random search and efficient abstract state space encodings such as binary decision diagrams. The additional performance needed by complex planning applications can be provided by adopting massively parallelcomputing systems, such as networks of clusters. This paper describes a simple, general approach for turning backtrack search based planners into more powerful distributed systems that run on networks of clusters. Our approach consists in distributing backtrack search points to different processes on the network. We illustrate its potential using DSHOP, a distributed version of the SHOP planner.
We present two broadcast algorithms that can be used on top of distributed hash tables (DHTs) to perform group communication and arbitrary queries. Unlike other P2P group communication mechanisms, which either embed e...
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ISBN:
(纸本)088986392X
We present two broadcast algorithms that can be used on top of distributed hash tables (DHTs) to perform group communication and arbitrary queries. Unlike other P2P group communication mechanisms, which either embed extra information in the DHTs or use random overlay networks, our algorithms take advantage of the structured DHT overlay networks without maintaining additional information. The proposed algorithms do not send any redundant messages. Furthermore the two algorithms ensure 100% coverage of the nodes in the system even when routing information is outdated as a result of dynamism in the network. The first algorithm performs some correction of outdated routing table entries with a low cost of correction traffic. The second algorithm exploits the nature of the broadcasts to extensively update erroneous routing information at the cost of higher correction traffic. The algorithms are validated and evaluated in our stochastic distributed-algorithms simulator.
The classification and selection of services within distributed, heterogeneous environments is a non trivial task. For a proper selection and composition of services in such environments - for example in a Grid or Clo...
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ISBN:
(纸本)9780889868649
The classification and selection of services within distributed, heterogeneous environments is a non trivial task. For a proper selection and composition of services in such environments - for example in a Grid or Cloud - it is required to dispose of detailed information about the existing resources and their characteristics. Particularly for applying appropriate optimization strategies these metadata are indispensable in order to decide which is the actual best resource for a given task, respectively query. It is thus a crucial task to first identify, classify and describe all system components and their attributes in a common language. Therefore a generic, high-level model of a service ontology is proposed, that exposes the fundamental building blocks of a distributed, service-oriented environment, by providing a structured collection of components and their functional and non-functional attributes. Finally, the applicability of the proposed ontology is verified by applying it to two distinct application scenarios, one from the domain of distributed Database Management Systems, and one from a High-Energy Physics experiment.
In this paper we present and evaluate the performance of two different strategies for the deployment of parallel multifrontal and multiple frontal sparse linear solvers in the context of a parallel finite element code...
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ISBN:
(纸本)0889865701
In this paper we present and evaluate the performance of two different strategies for the deployment of parallel multifrontal and multiple frontal sparse linear solvers in the context of a parallel finite element code. Direct sparse linear solvers are based on sophisticated reorganisation of the standard Gaussian elimination algorithm with the aim of exploring matrix sparsity and reducing the amount of fill-in. Such codes can be successfully applied to very large linear systems, and are especially effective when a sparse linear system needs to be solved for multiple right-hand sides. Unfortunately, many important applications, such as finite element solutions of non-linear, transient problems, require repeated factorisation of the coefficient matrix. In such cases the only way of achieving good performance is parallelisation of both the computation of the finite element matrices and the linear system solution phase. We have developed two different designs for deployment of parallel multifrontal and multiple frontal sparse linear solvers in this context, each deploying three different strategies for the assembly of the global data. These designs are suitable for parallel and heterogeneous architectures. Experiments confirm high efficiency, low communication cost, and reduced initial memory requirements of our deployment designs, compared to a standard deployment strategy.
The past decade has witnessed a boost in the acceptance of Grid computing as an alternative to traditional supercomputing environments. The evolution of Computers, networks and the Internet has boosted the growth of G...
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ISBN:
(纸本)9780889867048
The past decade has witnessed a boost in the acceptance of Grid computing as an alternative to traditional supercomputing environments. The evolution of Computers, networks and the Internet has boosted the growth of Grid computing. However applications with fine grained jobs tend to be unfavorable for this environment. Further applications that possess jobs that are dependent upon each other need to be grouped together and represented in a coarse-grained manner to lower the overheads involved with fine grained jobs, and rescheduling of dependent jobs. Also, there is a need to impose ordering on resource selection based on their processing capabilities and dynamic bandwidth scenarios. Users with different priorities must be provided differentiated Network ToS to ensure high Success Rates of job completion. In this paper, we investigate a dependency based, Network Aware, dynamic job grouping scheduler, which provides Network ToS to Users based on their deadlines.
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