In this paper three image quality metrics are compared: mean-square error (MSB), noise quality measure (NQM), and structural information metric (SIM). Such a comparison is made in order to evaluate the performance of ...
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A distributed scheme for dynamic partitioning is investigated. Distributed procedures to split a subsystem and to combine subsystems are presented. The correctness of each of these two procedures is shown, and the com...
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A distributed scheme for dynamic partitioning is investigated. Distributed procedures to split a subsystem and to combine subsystems are presented. The correctness of each of these two procedures is shown, and the complexity is analyzed. The procedures are applicable to parallelcomputers that use interconnection networks, such as hypercube, omega, multistage cube, and extra-stage cube networks.< >
Photonic structures at the wavelength scale offer innovative energy solutions for a wide range of applications,from high-efficiency photovoltaics to passive cooling,thus reshaping the global energy *** cooling based o...
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Photonic structures at the wavelength scale offer innovative energy solutions for a wide range of applications,from high-efficiency photovoltaics to passive cooling,thus reshaping the global energy *** cooling based on structural and material design presents new opportunities for sustainable carbon neutrality as a zero-energy,ecologically friendly cooling *** this review,in addition to introducing the fundamentals of the basic theory of radiative cooling technology,typical radiative cooling materials alongside their cooling effects over recent years are summarized and the current research status of radiative cooling materials is outlined and ***,technical challenges and potential advancements for radiative cooling are forecast with an outline of future application scenarios and development *** the future,radiative cooling is expected to make a significant contribution to global energy saving and emission reduction.
In the relay-trading mode of wireless cognitive radio networks the secondary user (SU) can achieve a promised spectrum access opportunity by relaying for the primary user (PU). How to utilize the exchanged resource ef...
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We, for the first time, estimate total fluctuation resulting from random dopants, interface traps and work functions using experimentally calibrated 3D statistical device simulation on 16-nm-gate high-κ/metal gate pl...
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Discusses the advantages of computing with heterogeneous parallel machines, and examines the research challenges for automating the use of such systems. One type of heterogeneous computing system is a mixed-mode machi...
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Discusses the advantages of computing with heterogeneous parallel machines, and examines the research challenges for automating the use of such systems. One type of heterogeneous computing system is a mixed-mode machine, where a single machine can operate in different modes of parallelism. Another is a mixed-machine system, where a suite of different kinds of parallel machines are interconnected by high-speed links. To exploit such systems, a task must be decomposed into subtasks, where each subtask is computationally homogeneous. The subtasks are then assigned to and executed with the machines (or modes) that will result in a minimal overall execution time. Typically, users must specify this decomposition and assignment. One long-term pursuit in heterogeneous computing is to do this automatically. An overview of a conceptual model of what this involves is given. As an example of the research in this area, a genetic-algorithm-based approach to the subtask assignment and scheduling problem is explored. Open problems in heterogeneous computing are described.
The communication latency problem is presented with special emphasis on RISC (reduced instruction set computer) based multiprocessors. An interprocessor communication model for parallel programs based on locality is p...
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The communication latency problem is presented with special emphasis on RISC (reduced instruction set computer) based multiprocessors. An interprocessor communication model for parallel programs based on locality is presented. This model enables the programmer to manipulate locality at the language level and to take advantage of currently available system hardware to reduce latency. A hardware node architecture for a latency-tolerant RISC-based multiprocessor, called Seamless, that supports this model, is presented. The Seamless architecture includes the addition of a hardware locality manager to each processing element, as well as an integral runtime environment and compiler.< >
The system of equations that govern kinematically redundant manipulators is commonly solved by finding the singular value decomposition (SVD) of the corresponding Jacobian matrix. This can require considerable amounts...
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The system of equations that govern kinematically redundant manipulators is commonly solved by finding the singular value decomposition (SVD) of the corresponding Jacobian matrix. This can require considerable amounts of time to compute, thus a parallel SVD algorithm minimizing execution time is sought. The approach employed here lends itself to parallelization by using Givens rotations and information from previous decompositions. The key contributions of this research include the presentation and implementation of a new variation of a parallel SVD algorithm to compute the SVD for a set of post-fault Jacobians. Results from implementation of the algorithm on a MasPar MP-1 and an IBM SP2 are provided. Specific issues considered for each implementation include how data is mapped to the processing elements, the effect that increasing the number of processing elements has on execution time, and the type of parallel architecture used.
In a dedicated mixed-machine heterogeneous computing (HC) system, an application program may be decomposed into subtasks, then each subtask assigned to the machine where it is best suited for execution. Subtask data r...
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In a dedicated mixed-machine heterogeneous computing (HC) system, an application program may be decomposed into subtasks, then each subtask assigned to the machine where it is best suited for execution. Subtask data relocation is defined as selecting the sources for their needed data items. This study focuses on theoretical issues for data relocation using a stochastic HC model. It is assumed that multiple independent subtasks of an application program can be executed concurrently on different machines whenever possible. A stochastic model for HC is proposed, in which the computation times of subtasks and communication times for inter-machine data transfers can be random variables. The optimization problem for finding the optimal matching, scheduling, and data relocation schemes to minimize the total execution time of an application program is defined based on this stochastic HC model. The optimization criteria and search space for the above optimization problem are described. It is proven that a greedy algorithm based approach will generate the optimal data relocation scheme with respect to any fixed matching and scheduling schemes. This result indicates that a greedy algorithm based approach is the best strategy for developing data relocation heuristics in practice.
Principal components analysis (PCA) has been widely used in many applications, particularly, data compression. Independent component analysis (ICA) has been also developed for blind source separation along with many o...
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Principal components analysis (PCA) has been widely used in many applications, particularly, data compression. Independent component analysis (ICA) has been also developed for blind source separation along with many other applications such as channel equalization, speech processing. Recently, it has been shown that the ICA can be also used for hyperspectral data compression. This paper investigates these two transforms in hyperspectral data compression and further evaluates their strengths and weaknesses in applications of target detection, mixed pixel classification and abundance quantification. In order to take advantage of the strengths of both transform, a new transform, called mixed PCA/ICA transform is developed in this paper. The idea of the proposed mixed PCA/ICA transform is derived from the fact that it can integrate different levels of information captured by the PCA and ICA. In doing so, it combines m principal components (PCs) resulting from the PCA and n independent components (ICs) generated by the ICA to form a new set of (m+n) mixed components used for hyperspectral data compression. The resulting transform is referred to as mixed (m,n)-PCA/ICA transform. In order to determine the total number of components, p needed to be generated for the mixed (m,m)-PCA/ICA transform, a recently developed virtual dimensionality (VD) is introduced to estimate the p where p = m + n. If m = p and n = 0, then mixed (m,n)-PCA/ICA transform is reduced to PCA transform. On the other hand, if m = 0 and n = p, then mixed (m,n)-PCA/ICA transform is reduced to ICA. Since various combinations of m and n have different impacts on the performance of the mixed PCA/ICA spectral/spatial compression in applications, experiments based on subpixel detection and mixed pixel quantification are conducted for performance evaluation.
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