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Parallel Computation for the Bandwidth Minimization Problem
2009The bandwidth minimization problem is a classical combinatorial optimization problem that has been studied since around 1960. It is formulated as follows. Given a connected graph G = (V;E) with n nodes and m edges, find a labeling π, i.e. a bijection between V and {1; 2;… ; n}, such that the maximum difference |π(u)–(v)|, uv e E, is minimized.
Khoa T. Vo, Gerhard Reinelt
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Resource and Bandwidth Allocation on a Computational Grid with Tree Topology
2006 Fifth International Conference on Grid and Cooperative Computing (GCC'06), 2006Grid computing systems (machines) pool together the resources of a heterogeneous collection of computing systems that are widely distributed, possibly around the globe, to create a virtual computing organization. Users can "draw" resources either from local or from remote computing resources to execute their jobs. We only consider such a system in tree
Shaoqiang Zhang, Chunyong Ding, Gang Hou
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Computing invariants in graphs of small bandwidth
Mathematics and Computers in Simulation, 1999Abstract Many graph invariants (chromatic number, rook polynomial, Tutte polynomial, etc.) are known to be computable for general graphs in exponential time only. Algorithms for their computation usually depend on special properties of the invariants and are not extendable to slightly different problems.
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Envelope process and computation of the equivalent bandwidth of multifractal flows
Computer Networks, 2005Internet Protocol flows present high variability at small time scales as well as long range dependence, which can be captured by multifractal models. Estimating the bandwidth to support the Quality of Service required by these flows is the key to Traffic Engineering.
Cesar A. V. Melo +1 more
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Interleaved Memory Bandwidth in a Model of a Multiprocessor Computer System
IEEE Transactions on Computers, 1979An approximate analysis is performed of an often studied model of an interleaved memory, multiprocessor system consisting of M memory modules and N processors. A closed-form solution is obtained and the one approximation used is found to result in negligible error. This solution is about an order of magnitude more accurate than the best previous result.
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How Is Bandwidth Used in Computers?
2007This chapter will explore the issue of bandwidth: how it is used, and how that effects the performance of an individual processor in a system, as well as how it impacts the overall system. It will examine the current trends in system evolution, and explain what those trends imply in light of bandwidth. Finally, the chapter will explore the technologies
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Optical Computations for Image Bandwidth Compression.
1982Abstract : This report summarizes the previous year's research in optical processing and optical/digital processing methods for image data compression. The following topics are discussed: (1) Radiometric and spatial transformations to achieve adaptive image data compression; (2) Spatial optical subsampling and spectral/spatial reconstruction for image ...
R. Schowengerdt, B. R. Hunt
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Towards compact bandwidth and efficient privacy-preserving computation
2023Im Gegensatz zu traditionellen kryptografischen Aufgaben, bei denen Kryptografie verwendet wird, um die Sicherheit und Integrität von Kommunikation oder Speicherung zu gewährleisten und der Gegner typischerweise ein Außenstehender ist, der versucht, die Kommunikation zwischen Sender und Empfänger abzuhören, ist die Kryptografie, die in der ...
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Computational holographic bandwidth compression
IBM Systems Journal, 1996A novel technique to compute holographic fringe patterns for real-time display is described. Hogel-vector holographic bandwidth compression, a diffraction-specific approach, treats a fringe as discretized in space and spatial frequency. By undersampling fringe spectra, hogel-vector encoding achieves a compression ratio of 16:1 with an acceptably small ...
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Collaborative Object Detectors Adaptive to Bandwidth and Computation
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022Juliano S. Assine +2 more
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