Traditionally, complex engineering applications (CEAs), which consist of numerous components (software) and require a large amount of computing resources, usu- ally run in dedicated clusters or highperformance co...
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Traditionally, complex engineering applications (CEAs), which consist of numerous components (software) and require a large amount of computing resources, usu- ally run in dedicated clusters or highperformancecomputing (HPC) centers. Nowadays, Cloud computing system with the ability of providing massive computing resources and cus- tomizable execution environment is becoming an attractive option for CEAs. As a new type on Cloud applications, CEA also brings the challenges of dealing with Cloud resources. In this paper, we provide a comprehensive survey of Cloud resource management research for CEAs. The survey puts forward two important questions: 1) what are the main chal- lenges for CEAs to run in Clouds? and 2) what are the prior research topics addressing these challenges? We summarize and highlight the main challenges and prior research topics. Our work can be probably helpful to those scientists and en- gineers who are interested in running CEAs in Cloud envi- ronment.
In this paper, we report on implementing an experimental distributed computing application for bioinformatics consisting of basic high-performancecomputing environments (Grid and PC Cluster systems), multiple interfa...
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ISBN:
(纸本)1595934804;9781595934802
In this paper, we report on implementing an experimental distributed computing application for bioinformatics consisting of basic high-performancecomputing environments (Grid and PC Cluster systems), multiple interfaces at user portals that provide useful graphical interfaces to enable biologists who are not IT specialists to benefit directly from the use of high-performance technology. Copyright 2007 ACM.
Distributed video coding (DVC) is a new paradigm of coding that makes very interest to itself in the past decade. It's usually based on temporal correlations between successive frames which are called key frames. ...
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Container-based highperformancecomputing (HPC) has started gaining popularity due to its almost negligible performance penalty compared to the BareMetal hardware. Although HPC hardware architectures and programming ...
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Memristive technology has been widely explored, due to its distinctive properties, such as nonvolatility, high density,versatility, and CMOS compatibility. For memristive devices, a general compact model is highly fav...
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Memristive technology has been widely explored, due to its distinctive properties, such as nonvolatility, high density,versatility, and CMOS compatibility. For memristive devices, a general compact model is highly favorable for the realization of its circuits and applications. In this paper, we propose a novel memristive model of TiOx-based devices, which considers the negative differential resistance(NDR) behavior. This model is physics-oriented and passes Linn's criteria. It not only exhibits sufficient accuracy(IV characteristics within 1.5% RMS), lower latency(below half the VTEAM model),and preferable generality compared to previous models, but also yields more precise predictions of long-term potentiation/depression(LTP/LTD). Finally, novel methods based on memristive models are proposed for gray sketching and edge detection applications. These methods avoid complex nonlinear functions required by their original counterparts. When the proposed model is utilized in these methods, they achieve increased contrast ratio and accuracy(for gray sketching and edge detection, respectively) compared to the Simmons model. Our results suggest a memristor-based network is a promising candidate to tackle the existing inefficiencies in traditional image processing methods.
This paper discusses a parallel implementation of the Finite-Difference Time-Domain (FDTD) method using Unified Parallel C (UPC). UPC is an extension of ANSI C - primarily designed for programming distributed memory p...
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Scientific computing has become one of the key players in the advance of modern science and technologies. In the meantime, due to the success of developments in processor fabrication, the computing power of Personal C...
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Scientific computing has become one of the key players in the advance of modern science and technologies. In the meantime, due to the success of developments in processor fabrication, the computing power of Personal computer (PC) is not to be ignored as well. Lots of high throughput type of applications can be satisfied by using the current desktop PCs, especially for those in computerized classrooms, and leave the supercomputers for the demands from large scale highperformance parallel computations. The goal of this work is to develop an automated mechanism for cluster computing to utilize the computing power such as resides in computerized classroom. The PCs in computerized classroom are usually setup for education and training purpose during the daytime, and shut down at night. After well deployment, these PCs can be transformed into a pre-configured cluster computing resource immediately without touching the existing education/training environment installed on these PCs. Thus, the training activities will not be affected by this additional activity to harvest idle computing cycles. To echo today's energy saving issues, a dynamic power management is also developed to minimize energy cost. This development not only greatly reduces the management efforts and time to build a cluster, but also implies the reduction of the power consumption by such a mechanism.
Computational intelligence is the computational simulation of the bio-intelligence, which includes artificial neural networks, fuzzy systems and evolutionary computations. This article summarizes the state of the art ...
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Computational intelligence is the computational simulation of the bio-intelligence, which includes artificial neural networks, fuzzy systems and evolutionary computations. This article summarizes the state of the art in the field of simulated modeling of vibration systems using methods of computational intelligence, based on some relevant subjects and the authors' own research work. First, contributions to the applications of computational intelligence to the identification of nonlinear characteristics of packaging are reviewed. Subsequently, applications of the newly developed training algorithms for feedforward neural networks to the identification of restoring forces in multi-degree-of-freedom nonlinear systems are discussed. Finally, the neural-network-based method of model reduction for the dynamic simulation of microelectromechanical systems (MEMS) using generalized Hebbian algorithm (GHA) and robust GHA is outlined. The prospects of the simulated modeling of vibration systems using techniques of computational intelligence are also indicated.
Hadoop framework consists of multiple components. One set of configuration parameters may not be suitable for all types of applications. Hence, for optimum performance, each framework parameter needs to be carefully c...
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highperformancecomputing and its applications are innumerable and the fact that it has seen a tremendous change in the recent years has given it the chance of becoming the future of computing world. The growing need...
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