Researchers often demand bursts of computing power to quickly obtain the results of certain simulation activities. Multimedia communication simulations usually belong to such category. They may require several days on...
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Researchers often demand bursts of computing power to quickly obtain the results of certain simulation activities. Multimedia communication simulations usually belong to such category. They may require several days on a generic PC to test a comprehensive set of conditions depending on the complexity of the scenario. This paper proposes to use a cloud computing framework to accelerate these simulations and, consequently, research activities, while at the same time reducing the overall costs. A practical simulation example is shown, representative of a typical simulation of H.264/AVC video communications over a wireless channel. This work shows that, by means of a commercial cloud computing provider, the gains of the proposed technique compared to more traditional solutions using dedicated computers can be significant in terms of speed and cost reduction.
Chemical computing was initially proposed as an intuitive paradigm to capture the essence of parallelcomputing. Within such a model, a program is a solution of information-carrying molecules, that, at run time, colli...
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Chemical computing was initially proposed as an intuitive paradigm to capture the essence of parallelcomputing. Within such a model, a program is a solution of information-carrying molecules, that, at run time, collide non-deterministically to produce new data. Such a paradigm allowed the programmers to focus on the logic of the problem to be solved in parallel, without having to worry about implementation's considerations. Throughout the years, the model has been enriched with various features related to program structure, control and practicability. More importantly, the model was raised to the higher order, increasing again its expressiveness. With the rise of service-oriented computing, such models have recently regained a lot of interest. They have been shown to provide adequate abstractions to enhance service-oriented architectures with autonomic properties such as self-adaptation, self-healing, or self-organisation. However, the deployment of chemical programs over large scale distributed platforms is still a widely open problem, hindering the model to be leveraged in practice. This paper studies the possibility of building a distributed execution environment for chemical programs. A generic peer-to-peer-based runtime model and distributed algorithms for large scale chemical computing are discussed. To complete this study, a software prototype was developed and experimented over the Grid'5000 test-bed. Experimental performance results are detailed, allowing for a discussion of the feasibility and performance of such a runtime, thus lifting a barrier towards the enactment of the chemical programming model.
Today modern computing systems leverage distributed models such as cloud, grid, etc. One of the obstacles of wide spreading these distributedcomputing models is security challenges which includes access control probl...
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ISBN:
(纸本)9781467309745
Today modern computing systems leverage distributed models such as cloud, grid, etc. One of the obstacles of wide spreading these distributedcomputing models is security challenges which includes access control problem. These computing models because of providing features like on-demand self-service, ubiquitous network access, rapid elasticity and scalability, having dynamic infrastructure and offering measured service, need a powerful and continuous control over access and usage session. Usage control (UCON) model is emerged to cover some drawbacks of traditional access control models with features like attribute mutability and continuity of control. Several recent works have been done to apply UCON for distributedcomputing environments, but none of them could cover all aspects of the model. In this paper we propose an architecture for applying UCON model in cloud environments. Moreover we present a new architecture for obligation handling. We also introduce a new approach to handle attribute mutability. For implementation we have extended XACML syntax and semantics as policy language and leveraged Sun's OASIS XACML implementation.
In this work we present an hypervisor-independent GPU Virtualization Service named GVirtus. It instantiates virtual machines able to access to the GPU in a transparent way. GPUs allow to speed up calculations over CPU...
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In this work we present an hypervisor-independent GPU Virtualization Service named GVirtus. It instantiates virtual machines able to access to the GPU in a transparent way. GPUs allow to speed up calculations over CPUs. Therefore, virtualizing GPUs is a major trend and can be considered a revolutionary tool for HPC. To test the performances of GVirtus we used a fluid simulator. Morover to exploit the computational power of GPUs in cloud computing we virtualized three different plugins for GVirtus Framework : Cuda Runtime, Cuda Driver and OpenCL plugins. Our results show that the overhead introduced by virtualization is almost irrelevant.
In order to obtain more accurate solutions of polynomial systems with numerical continuation methods we use multiprecision arithmetic. Our goal is to offset the overhead of double double arithmetic accelerating the pa...
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ISBN:
(纸本)9781467309745
In order to obtain more accurate solutions of polynomial systems with numerical continuation methods we use multiprecision arithmetic. Our goal is to offset the overhead of double double arithmetic accelerating the path trackers and in particular Newton's method with a general purpose graphics processing unit. In this paper we describe algorithms for the massively parallel evaluation and differentiation of sparse polynomials in several variables. We report on our implementation of the algorithmic differentiation of products of variables on the NVIDIA Tesla C2050 computing Processor using the NVIDIA CUDA compiler tools.
Considered a combination of Software-as-a-Service and Business Process Outsourcing, Business Process as a Service has the potential to provide the killer applications able to propel Cloud computing to a higher technol...
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Considered a combination of Software-as-a-Service and Business Process Outsourcing, Business Process as a Service has the potential to provide the killer applications able to propel Cloud computing to a higher technological level. Following a general overview of the current state-of-the-art in research and implementation of the BPaaS, we propose a mind switch towards the applicability of re-usable business process patterns and a multi-modeling approach for BPaaS design, deployment and operation. In order to demonstrate the feasibility of the approach we provide two examples of BPaaSs that can take advantage of Cloud computing in order to gain clear benefits in terms of services' efficiency.
Topology-based techniques are useful for multiscale exploration of the feature space of scalar-valued functions, such as those derived from the output of large-scale simulations. The Morse-Smale (MS) complex, in parti...
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Topology-based techniques are useful for multiscale exploration of the feature space of scalar-valued functions, such as those derived from the output of large-scale simulations. The Morse-Smale (MS) complex, in particular, allows robust identification of gradient-based features, and therefore is suitable for analysis tasks in a wide range of application domains. In this paper, we develop a two-stage algorithm to construct the 1-skeleton of the Morse-Smale complex in parallel, the first stage independently computing local features per block and the second stage merging to resolve global features. Our implementation is based on MPI and a distributed-memory architecture. Through a set of scalability studies on the IBM Blue Gene/P supercomputer, we characterize the performance of the algorithm as block sizes, process counts, merging strategy, and levels of topological simplification are varied, for datasets that vary in feature composition and size. We conclude with a strong scaling study using scientific datasets computed by combustion and hydrodynamics simulations.
This work presents a stochastic local search method for efficiently solve the scheduling problem in heterogeneous computing environments. The research community has been searching for accurate schedulers for heterogen...
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This work presents a stochastic local search method for efficiently solve the scheduling problem in heterogeneous computing environments. The research community has been searching for accurate schedulers for heterogeneous computing systems, able to perform in reduced times. The stochastic search proposed in this work is based on simple operators in order to keep the computational complexity as low as possible, thus allowing to efficiently tackle large scheduling instances. The experimental analysis demonstrates that the new stochastic local search method is able to compute accurate suboptimal schedules in significantly shorter execution times than state-of-the-art schedulers.
How can the CS education community shift to teach more parallel and distributedcomputing (PDC) soon enough to prepare its graduates for their careers? The CSin parallel project implements strategies that would accomp...
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ISBN:
(纸本)9781467309745
How can the CS education community shift to teach more parallel and distributedcomputing (PDC) soon enough to prepare its graduates for their careers? The CSin parallel project implements strategies that would accomplish such a shift. An Early Adopter project to correlate CSin parallel materials and NSF/TCPP Curricular Recommendations is described. Citing research on scalability of innovations, such synergistic collaborations offer hope for scalably and rapidly adding PDC to undergraduate CS education.
Nowadays more and more users have mobile devices with high computing power. This fact allows taking advantage of that processing power to design applications that allow users to interact remotely with the system simpl...
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