Signal, image and Synthetic Aperture Radar imagery algorithms in recent time are used in a daily routine. Due to huge data and complexity, their processing is almost impossible in a real time. Often image processing a...
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ISBN:
(纸本)9781538669792
Signal, image and Synthetic Aperture Radar imagery algorithms in recent time are used in a daily routine. Due to huge data and complexity, their processing is almost impossible in a real time. Often image processingalgorithms are inherently parallel in nature, so they fit nicely into parallelarchitectures multicore Central processing Unit (CPU) and Graphics processing Unit GPUs. In this paper image processingalgorithms were evaluated, which are capable to execute in parallel manner on several platforms CPU and GPU. All algorithms were tested in TensorFlow, which is a novel framework for deep learning, but also for image processing. Relative speedups compared to CPU were given for all algorithms. TensorFlow GPU implementation can outperform multi-core CPUs for tested algorithms, obtained speedups range from 3.6 to 15 times.
It is presented in this paper that the design and analysis of finite difference domain decomposition algorithms for the two-dimensional heat equation and the numerical results have shown the stability and accuracy of ...
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ISBN:
(纸本)0769515126
It is presented in this paper that the design and analysis of finite difference domain decomposition algorithms for the two-dimensional heat equation and the numerical results have shown the stability and accuracy of the algorithms. the algorithms in the paper have further extended those developed by Dawson and the others [6].
the parallel versions of bioinspired algorithms are presented in the paper. the parallel evolutionary algorithms and artificial immune systems are described. the applications of bioinspired algorithms to optimization ...
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ISBN:
(纸本)9783540681052
the parallel versions of bioinspired algorithms are presented in the paper. the parallel evolutionary algorithms and artificial immune systems are described. the applications of bioinspired algorithms to optimization of mechanical structures are shown. the numerical tests presented in the paper were computed with use of grid based on Alchemi framework.
Scalability and performance are crucial for simulations as much as accuracy is. Due to the limited availability and access to the variety of resources, cloud and MapReduce solutions are often evaluated on simulator pl...
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ISBN:
(纸本)9781479978816
Scalability and performance are crucial for simulations as much as accuracy is. Due to the limited availability and access to the variety of resources, cloud and MapReduce solutions are often evaluated on simulator platforms. As the complexity of the architectures and algorithms keep increasing, simulations themselves become large and resource-hungry. Simulators can be designed to be adaptive, exploiting the clusters and data-grid platforms. this paper describes the research for the design, development, and evaluation of a complete fully parallel and distributed cloud and MapReduce simulator (Cloud(2)Sim), leveraging the Java in-memory data grid platforms. Cloud(2)Sim provides a concurrent and distributed cloud simulator, by extending CloudSim cloud simulator, using Hazelcast in-memory key-value store. It also provides an assessment of the MapReduce implementations of Hazelcast and Infinispan, with means of simulating MapReduce executions. Cloud(2)Sim scales out the cloud and MapReduce simulations to multiple nodes running Hazelcast and Infinispan, based on load. the distributed execution model and adaptive scaling solution could further be leveraged as a general purpose auto-scaler middleware for a multi-tenanted deployment.
Massively parallel processor array architectures can be used as hardware accelerators for a plenty of dataflow dominant applications. Bilateral filtering is an example of a state-of-the-art algorithm in medical imagin...
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ISBN:
(纸本)0769526829
Massively parallel processor array architectures can be used as hardware accelerators for a plenty of dataflow dominant applications. Bilateral filtering is an example of a state-of-the-art algorithm in medical imaging, which falls in the class of 2D adaptive filter algorithms. In this paper we propose a semi-automatic mapping methodology for the generation of hardware accelerators for such a generic class of adaptive filtering applications in image processing. the final architecture deliver similar synthesis results as a hand-tuned design.
the Critical Node Detection Problem (CNDP) is a well-known NP-complete, graph-theoretical problem with many real-world applications in various fields such as social network analysis, supply-chain network analysis, tra...
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ISBN:
(纸本)9781479989379
the Critical Node Detection Problem (CNDP) is a well-known NP-complete, graph-theoretical problem with many real-world applications in various fields such as social network analysis, supply-chain network analysis, transport engineering, network immunization, and military strategic planning. We present the first parallelalgorithms for CNDP solving in general, and for fast, approximated CND on GPU and in the cloud in particular. Finally, we discuss results of our experimental performance analysis of these solutions.
this paper proposes a novel approach to program development for highly parallelarchitectures, primarily as far as debugging is concerned. the visual nature of the debugging stage, when dealing with image-processing a...
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A type of incomplete decomposition preconditioner based on local block factorization is considered, for the matrices derived from discreting 2-D or 3-D elliptic partial differential equations. We prove that the condit...
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ISBN:
(纸本)0769515126
A type of incomplete decomposition preconditioner based on local block factorization is considered, for the matrices derived from discreting 2-D or 3-D elliptic partial differential equations. We prove that the condition numbers of the preconditioned matrices are small, which means that the constructed preconditioners are effective. Further we consider an efficient parallel version of the preconditioner which depends only on a single integer argument. When its value is small, the iterations needed on multiple processors to converge is much more than on a single processor But withthe increase of this value, the difference decreases step by step. Finally, we have many experiments on a cluster of 6 PCs with main frequencies of 1.8GHz the results show that the local block factorizations constructed are efficient in serial implementation, if compared to some well-known effective preconditioners, and the parallel versions are efficient also.
Embedded computing architectures can be designed to meet a variety of application specific requirements. However, optimized hardware can require compiler support to realize the potential of the hardware. this is espec...
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ISBN:
(纸本)0769526373
Embedded computing architectures can be designed to meet a variety of application specific requirements. However, optimized hardware can require compiler support to realize the potential of the hardware. this is especially true for embedded image processing systems where significant architectural variation is possible, and targeted software can change drastically based on architectural variation. this paper presents methods to compile a single high-level source given a fundamental variation in data-parallel target architectures processor granularity ranging from a single processor to a massively parallel processor array. the approach uses single PPE virtualization, which supports pixel-level data-parallel expressions that operate on a virtual one pixel per processing element (PPE) network and applies pixel-locating transformations to retarget the code into a given target PPE. Unlike mainstream parallel computing techniques, this technique can be applied to lightweight SIMD targets that do not provide global communication hardware or shared memory.
Improving the computation efficiency is a key issue in image processing, especially in edge detection, because edge detection is very computationally intensive. Withthe development of real-time application of image p...
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ISBN:
(纸本)0769515126
Improving the computation efficiency is a key issue in image processing, especially in edge detection, because edge detection is very computationally intensive. Withthe development of real-time application of image processing, fast processing response is becoming more critical. In this paper, a technique for distributed image processing on Spiral Architecture is proposed, which provides a platform for speeding up image processing based on clusters.
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