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Letteratura scientifica selezionata sul tema "Computation speedup"

Autore: Grafiati

Pubblicato: 10 dicembre 2022

Ultima modifica: 29 gennaio 2023

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Articoli di riviste sul tema "Computation speedup"

Zhang, Guiming, e Jin Xu. "Multi-GPU-Parallel and Tile-Based Kernel Density Estimation for Large-Scale Spatial Point Pattern Analysis". ISPRS International Journal of Geo-Information 12, n. 2 (18 gennaio 2023): 31. http://dx.doi.org/10.3390/ijgi12020031.

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Kernel density estimation (KDE) is a commonly used method for spatial point pattern analysis, but it is computationally demanding when analyzing large datasets. GPU-based parallel computing has been adopted to address such computational challenges. The existing GPU-parallel KDE method, however, utilizes only one GPU for parallel computing. Additionally, it assumes that the input data can be held in GPU memory all at once for computation, which is unrealistic when conducting KDE analysis over large geographic areas at high resolution. This study develops a multi-GPU-parallel and tile-based KDE algorithm to overcome these limitations. It exploits multiple GPUs to speedup complex KDE computation by distributing computation across GPUs, and approaches density estimation with a tile-based strategy to bypass the memory bottleneck. Experiment results show that the parallel KDE algorithm running on multiple GPUs achieves significant speedups over running on a single GPU, and higher speedups are achieved on KDE tasks of a larger problem size. The tile-based strategy renders it feasible to estimate high-resolution density surfaces over large areas even on GPUs with only limited memory. Multi-GPU parallel computing and tile-based density estimation, while incurring very little computational overhead, effectively enable conducting KDE for large-scale spatial point pattern analysis on geospatial big data.

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Gao, Wen Hua, Li Qin Duan, Wei Zhou e Pei Xin Ye. "Information-Based Complexity of Integration in the Randomized and Quantum Computation Model". Advanced Materials Research 403-408 (novembre 2011): 367–71. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.367.

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In this paper, we investigate the integration of the Hölder-Nikolskii classes in the randomized and quantum computation model. We develop randomized and quantum algorithms for integration of functions from this class and analyze their convergence rates. Comparing our result with the convergence rates in the deterministic setting, we see that quantum computing can reach an exponential speedup over deterministic classical computation and a quadratic speedup over randomized classical computation.

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MORENO MAZA, MARC, e YUZHEN XIE. "BALANCED DENSE POLYNOMIAL MULTIPLICATION ON MULTI-CORES". International Journal of Foundations of Computer Science 22, n. 05 (agosto 2011): 1035–55. http://dx.doi.org/10.1142/s0129054111008556.

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In symbolic computation, polynomial multiplication is a fundamental operation akin to matrix multiplication in numerical computation. We present efficient implementation strategies for FFT-based dense polynomial multiplication targeting multi-cores. We show that balanced input data can maximize parallel speedup and minimize cache complexity for bivariate multiplication. However, unbalanced input data, which are common in symbolic computation, are challenging. We provide efficient techniques, that we call contraction and extension, to reduce multivariate (and univariate) multiplication to balanced bivariate multiplication. Our implementation in Cilk++ demonstrates good speedup on multi-cores.

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Xu, Zhiqiang, Yiming Wang, Naidi Sun, Zhengying Li, Song Hu e Quan Liu. "Parallel Computing for Quantitative Blood Flow Imaging in Photoacoustic Microscopy". Sensors 19, n. 18 (16 settembre 2019): 4000. http://dx.doi.org/10.3390/s19184000.

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Photoacoustic microscopy (PAM) is an emerging biomedical imaging technology capable of quantitative measurement of the microvascular blood flow by correlation analysis. However, the computational cost is high, limiting its applications. Here, we report a parallel computation design based on graphics processing unit (GPU) for high-speed quantification of blood flow in PAM. Two strategies were utilized to improve the computational efficiency. First, the correlation method in the algorithm was optimized to avoid redundant computation and a parallel computing structure was designed. Second, the parallel design was realized on GPU and optimized by maximizing the utilization of computing resource in GPU. The detailed timings and speedup for each calculation step were given and the MATLAB and C/C++ code versions based on CPU were presented as a comparison. Full performance test shows that a stable speedup of ~80-fold could be achieved with the same calculation accuracy and the computation time could be reduced from minutes to just several seconds with the imaging size ranging from 1 × 1 mm2 to 2 × 2 mm2. Our design accelerates PAM-based blood flow measurement and paves the way for real-time PAM imaging and processing by significantly improving the computational efficiency.

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Zhang, Zhigang, Songfeng Lu, Jie Sun e Qing Zhou. "The Constant Speedup Mechanism on Adiabatic Quantum Computation". Journal of Computational and Theoretical Nanoscience 13, n. 10 (1 ottobre 2016): 7262–65. http://dx.doi.org/10.1166/jctn.2016.5997.

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In the adiabatic quantum computation model, a computational procedure is described by the continuous time evolution of a time dependent Hamiltonian. Classically, the unstructured search problem can be solved only in a running time of order O(G). However, by modifying the structure of local Hamiltonian or using specific interpolating functions, it is possible to do the calculation in constant time for a quantum computer. This paper reveals the cause that lead to the speedup. We analyze two kinds of specific adiabatic quantum models, and conclude that the value of relevant elements in back-diagonal of the local Hamiltonian is the main factors affecting the time complexity of adiabatic quantum algorithms. According to the speedup mechanism, we have proposed two kinds of adiabatic quantum algorithms to make a constant time complexity.

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AKL, SELIM G. "INHERENTLY PARALLEL GEOMETRIC COMPUTATIONS". Parallel Processing Letters 16, n. 01 (marzo 2006): 19–37. http://dx.doi.org/10.1142/s0129626406002447.

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A new computational paradigm is described which offers the possibility of superlinear (and sometimes unbounded) speedup, when parallel computation is used. The computations involved are subject only to given mathematical constraints and hence do not depend on external circumstances to achieve superlinear performance. The focus here is on geometric transformations. Given a geometric object A with some property, it is required to transform A into another object B which enjoys the same property. If the transformation requires several steps, each resulting in an intermediate object, then each of these intermediate objects must also obey the same property. We show that in transforming one triangulation of a polygon into another, a parallel algorithm achieves a superlinear speedup. In the case where a convex decomposition of a set of points is to be transformed, the improvement in performance is unbounded, meaning that a parallel algorithm succeeds in solving the problem as posed, while all sequential algorithms fail.

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Su, Huayou, Kaifang Zhang e Songzhu Mei. "On the Transformation Optimization for Stencil Computation". Electronics 11, n. 1 (23 dicembre 2021): 38. http://dx.doi.org/10.3390/electronics11010038.

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Stencil computation optimizations have been investigated quite a lot, and various approaches have been proposed. Loop transformation is a vital kind of optimization in modern production compilers and has proved successful employment within compilers. In this paper, we combine the two aspects to study the potential benefits some common transformation recipes may have for stencils. The recipes consist of loop unrolling, loop fusion, address precalculation, redundancy elimination, instruction reordering, load balance, and a forward and backward update algorithm named semi-stencil. Experimental evaluations of diverse stencil kernels, including 1D, 2D, and 3D computation patterns, on two typical ARM and Intel platforms, demonstrate the respective effects of the transformation recipes. An average speedup of 1.65× is obtained, and the best is 1.88× for the single transformation recipes we analyze. The compound recipes demonstrate a maximum speedup of 1.92×.

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Wani, Mohsin Altaf, e Manzoor Ahmad. "Statically Optimal Binary Search Tree Computation Using Non-Serial Polyadic Dynamic Programming on GPU's". International Journal of Grid and High Performance Computing 11, n. 1 (gennaio 2019): 49–70. http://dx.doi.org/10.4018/ijghpc.2019010104.

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Modern GPUs perform computation at a very high rate when compared to CPUs; as a result, they are increasingly used for general purpose parallel computation. Determining if a statically optimal binary search tree is an optimization problem to find the optimal arrangement of nodes in a binary search tree so that average search time is minimized. Knuth's modification to the dynamic programming algorithm improves the time complexity to O(n2). We develop a multiple GPU-based implementation of this algorithm using different approaches. Using suitable GPU implementation for a given workload provides a speedup of up to four times over other GPU based implementations. We are able to achieve a speedup factor of 409 on older GTX 570 and a speedup factor of 745 is achieved on a more modern GTX 1060 when compared to a conventional single threaded CPU based implementation.

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YONG, XIE, e HSU WEN-JING. "ALIGNED MULTITHREADED COMPUTATIONS AND THEIR SCHEDULING WITH PERFORMANCE GUARANTEES". Parallel Processing Letters 13, n. 03 (settembre 2003): 353–64. http://dx.doi.org/10.1142/s0129626403001331.

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This paper considers the problem of scheduling dynamic parallel computations to achieve linear speedup without using significantly more space per processor than that required for a single processor execution. Earlier research in the Cilk project proposed the "strict" computational model, in which every dependency goes from a thread x only to one of x's ancestor threads, and guaranteed both linear speedup and linear expansion of space. However, Cilk threads are stateless, and the task graph that Cilk language expresses is series-parallel graph, which is a proper subset of arbitrary task graph. Moreover, Cilk does not support applications with pipelining. We propose the "aligned" multithreaded computational model, which extends the "strict" computational model in Cilk. In the aligned multithreaded computational model, dependencies can go from arbitrary thread x not only to x's ancestor threads, but also to x's younger brother threads, that are spawned by x's parent thread but after x. We use the same measures of time and space as those used in Cilk: T1 is the time required for executing the computation on 1 processor, T∞ is the time required by an infinite number of processors, and S1 is the space required to execute the computation on 1 processor. We show that for any aligned computation, there exists an execution schedule that achieves both efficient time and efficient space. Specifically, we show that for an execution of any aligned multithreaded computation on P processors, the time required is bounded by O(T1/P + T∞), and the space required can be loosely bounded by O(λ·S1P), where λ is the maximum number of younger brother threads that have the same parent thread and can be blocked during execution. If we assume that λ is a constant, and the space requirements for elder and younger brother threads are the same, then the space required would be bounded by O(S1P). Based on the aligned multithreaded computational model, we show that the aligned multithreaded computational model supports pipelined applications. Furthermore, we propose a multithreaded programming language and show that it can express arbitrary task graph.

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Al-Neama, Mohammed W., Naglaa M. Reda e Fayed F. M. Ghaleb. "An Improved Distance Matrix Computation Algorithm for Multicore Clusters". BioMed Research International 2014 (2014): 1–12. http://dx.doi.org/10.1155/2014/406178.

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Distance matrix has diverse usage in different research areas. Its computation is typically an essential task in most bioinformatics applications, especially in multiple sequence alignment. The gigantic explosion of biological sequence databases leads to an urgent need for accelerating these computations.DistVectalgorithm was introduced in the paper of Al-Neama et al. (in press) to present a recent approach for vectorizing distance matrix computing. It showed an efficient performance in both sequential and parallel computing. However, the multicore cluster systems, which are available now, with their scalability and performance/cost ratio, meet the need for more powerful and efficient performance. This paper proposesDistVect1as highly efficient parallel vectorized algorithm with high performance for computing distance matrix, addressed to multicore clusters. It reformulatesDistVect1vectorized algorithm in terms of clusters primitives. It deduces an efficient approach of partitioning and scheduling computations, convenient to this type of architecture. Implementations employ potential of both MPI and OpenMP libraries. Experimental results show that the proposed method performs improvement of around 3-fold speedup upon SSE2. Further it also achieves speedups more than 9 orders of magnitude compared to the publicly available parallel implementation utilized in ClustalW-MPI.

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Tesi sul tema "Computation speedup"

Terner, Olof, e Hedbjörk Villhelm Urpi. "Quantum Computational Speedup For The Minesweeper Problem". Thesis, Uppsala universitet, Teoretisk fysik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-325945.

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Quantum computing is a young but intriguing field of science. It combines quantum mechanics with information theory and computer science to potentially solve certain formerly computationally expensive tasks more efficiently. Classical computers are based on bits that can take on the value zero or one. The values are distinguished by voltage differences in transistors. Quantum computers are instead based on quantum bits, or qubits, that are represented physically by something that exhibits quantum properties, like for example electrons. Qubits also take on the value zero or one, which could correspond to spin up and spin down of an electron. However, qubits can also be in a superposition state between the quantum states corresponding to the value zero and one. This property is what causes quantum computers to be able to outperform classical computers at certain tasks. One of these tasks is searching through an unstructured database. Whereas a classical computer in the worst case has to search through the whole database in order to find the sought element, i.e. the computation time is proportional to the size of the problem, it can be shown that a quantum computer can find the solution in a time proportional to the square root of the size of the problem. This report aims to illustrate the advantages of quantum computing by explicitly solving the classical Windows game Minesweeper, which can be reduced to a problem resembling the unstructured database search problem. It is shown that solving Minesweeper with a quantum algorithm gives a quadratic speedup compared to solving it with a classical algorithm. The report also covers introductory material to quantum mechanics, quantum gates, the particular quantum algorithm Grover's algorithm and complexity classes, which is necessary to grasp in order to understand how Minesweeper can be solved on a quantum computer.

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Mezher, Rawad. "Randomness for quantum information processing". Electronic Thesis or Diss., Sorbonne université, 2019. https://accesdistant.sorbonne-universite.fr/login?url=https://theses-intra.sorbonne-universite.fr/2019SORUS244.pdf.

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Cette thèse est basée sur la génération et la compréhension de types particuliers des ensembles unitaires aleatoires. Ces ensembles est utile pour de nombreuses applications de physique et de l’Information Quantique, comme le benchmarking aléatoire, la physique des trous noirs, ainsi qu’à la démonstration de ce que l’on appelle un "quantum speedup" etc. D'une part, nous explorons comment générer une forme particulière d'évolution aléatoire appelée epsilon-approximateunitary t-designs . D'autre part, nous montrons comment cela peut également donner des exemples de quantum speedup, où les ordinateurs classiques ne peuvent pas simuler en temps polynomiale le caractère aléatoire. Nous montrons également que cela est toujours possible dans des environnements bruyants et réalistes
This thesis is focused on the generation and understanding of particular kinds of quantum randomness. Randomness is useful for many tasks in physics and information processing, from randomized benchmarking , to black hole physics , as well demonstrating a so-called quantum speedup , and many other applications. On the one hand we explore how to generate a particular form of random evolution known as a t-design. On the other we show how this can also give instances for quantum speedup - where classical computers cannot simulate the randomness efficiently. We also show that this is still possible in noisy realistic settings. More specifically, this thesis is centered around three main topics. The first of these being the generation of epsilon-approximate unitary t-designs. In this direction, we first show that non-adaptive, fixed measurements on a graph state composed of poly(n,t,log(1/epsilon)) qubits, and with a regular structure (that of a brickwork state) effectively give rise to a random unitary ensemble which is a epsilon-approximate t-design. This work is presented in Chapter 3. Before this work, it was known that non-adaptive fixed XY measurements on a graph state give rise to unitary t-designs , however the graph states used there were of complicated structure and were therefore not natural candidates for measurement based quantum computing (MBQC), and the circuits to make them were complicated. The novelty in our work is showing that t-designs can be generated by fixed, non-adaptive measurements on graph states whose underlying graphs are regular 2D lattices. These graph states are universal resources for MBQC. Therefore, our result allows the natural integration of unitary t-designs, which provide a notion of quantum pseudorandomness which is very useful in quantum algorithms, into quantum algorithms running in MBQC. Moreover, in the circuit picture this construction for t-designs may be viewed as a constant depth quantum circuit, albeit with a polynomial number of ancillas. We then provide new constructions of epsilon-approximate unitary t-designs both in the circuit model and in MBQC which are based on a relaxation of technical requirements in previous constructions. These constructions are found in Chapters 4 and 5

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Pandya, Ajay Kirit. "Performance of multithreaded computations on high-speed networks". Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ32212.pdf.

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Chitty, Darren M. "Improving the computational speed of genetic programming". Thesis, University of Bristol, 2015. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.686812.

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Genetic Programming (GP) is well known as a computationally intensive technique especially when considering regression or classification tasks with large datasets. Consequently, there has been considerable work conducted into improving the computational speed of GP. Recently, this has concentrated on exploiting highly parallel architectures in the form of Graphics Processing Units (GPUs). However, the reported speeds fall considerably short of the computational capabilities of these GPUs. This thesis investigates this issue, seeking to considerably improve the computational speed of GP. Indeed, this thesis will demonstrate that considerable improvements in the speed of GP can be achieved when fully exploiting a parallel Central Processing Unit (CPU) exceeding the performance of the latest GPU implementations. This is achieved by recognising that GP is as much a memory bound technique as a compute bound technique. By adopting a two dimensional stack approach, better exploitation of memory resources is achieved in addition to reducing interpreter overheads. This approach is applied to CPU and GPU implementations and compares favorably with compiled versions of GP. The second aspect of this thesis demonstrates that although considerable performance gains can be achieved using parallel hardware, the role of efficiency within GP should not be forgotten. Efficiency saving can boost the computational speed of parallel GP significantly. Two methods are considered, parsimony pressure measures and efficient tournament selection. The second efficiency technique enables a CPU implementation of GP to outperform a GPU implementation for classification type tasks even though the CPU has only a tenth of the computational power. Finally both CPU and GPU are combined for ultimate performance. Speedups of more than a thousand fold over a basic sequential version of GP are achieved and three fold over the best GPU implementation from the literature. Consequently, this speedup increases the usefulness of GP as a machine learning technique.

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Yousefi, Mojir Kayran. "A Computational Model for Optimal Dimensional Speed on New High-Speed Lines". Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-37230.

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High Speed Lines (HSL) in rail passenger services are regarded as one of the most significant projects in many countries comparing to other projects in the transportation area. According to the EU (European Council Directive 96/48/EC,2004) , high-speed lines are either new-built lines for speeds of 250km/h or greater, or in some cases upgraded traditional lines. At the beginning of 2008, there were 10,000 km of new HSL lines in operation, and by taking into account the upgraded conventional lines, in total, there were 20,000 km line in the world. The network is growing fast because of the demand for short travelling time and comfort isincreasing rapidly. Since HSL projects require a lot of capital, it is getting more important for governments and companies to estimate and to calculate the total costs and benefits of building, maintaining, and operating of HSL so that they can decide better and more reliable in choosing between projects. There are many parameters which affect the total costs and benefits of an HSL. The most important parameter is dimensional speed which has a great influence on other parameters. For example, tunnels need larger cross section for higher speed which increases construction costs. More important, higher speed also influences the number of passengers attracted from other modes of transport. Due to a large number of speed-dependant parameters, it is not a simple task to estimate an optimal dimensional speed by calculating the costs and benefits of an HSL manually. It is also difficult to do analysis for different speeds, as speed changes many other relevant parameters. As a matter of fact, there is a need for a computational model to calculate the cost-benefit for different speeds. Based on the computational model, it is possible to define different scenarios and compare them to each other to see what the potentially optimal speed would be for a new HSL project. Besides the optimal speed, it is also possible to analyze and find effects of two other important parameters, fare and frequency, by cost-benefit analysis (CBA). The probability model used in the calculation is based on an elasticity model, and input parameters are subject to flexibility to calibrate the model appropriately. Optimal high-speed line (OHSL) tool is developed to make the model accessible for the users.

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Brown, Kieron David. "Computational analysis of low speed axial flow rotors". Thesis, University of Bristol, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.389158.

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Zhu, Yu Ping. "Computational study of shock control at transonic speed". Thesis, Cranfield University, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.323930.

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Yildirim, Erkan. "Computational study of high speed blade-vortex interaction". Thesis, Imperial College London, 2012. http://hdl.handle.net/10044/1/10994.

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This thesis presents inviscid compressible simulations for the orthogonal blade-vortex interaction. A numerical model between the tail rotor of a helicopter and the trailing vortex system formed by the main rotor blades is assumed. The study takes a ‘building-block’ approach to investigating this problem. Firstly, the impulsive instantaneous blocking of the axial core flow by a flat plate is considered. In the second step, the three-dimensional gradual cutting of the vortex by a sharp flat-plate that moves at a finite speed through the vortex is performed. Finally the chopping of the vortex by a blunt leading edge aerofoil, which incorporates both the blocking effect and also the stretching and distortion of the vortex lines is studied. The solutions reveal that the compressibility effects are strong when the axial core flow of the vortex is impulsively blocked. This generates a weak shock-expansion structure propagating along the vortex core on opposite sides of the cutting surface. The shock and expansion waves are identified as the prominent acoustic signatures in the interaction. In a simplified, two-dimensional axisymmetric model, the modelling of the physical evolution of the vortex, including the evolution of the complex vortical structures that controls the vortex core size near the cutting surface, are studied. Furthermore, the three dimensional simulations revealed that there is a secondary and a tertiary noise sources due to compressibility effects at the blade leading edge and due to the shock-vortex interaction taking place on the blade, which is exposed to a transonic free-stream flow.

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Rohrseitz, Nicola. "The computation of linear speed for visual flight control in Drosophila melanogaster /". Zürich : ETH, 2009. http://e-collection.ethbib.ethz.ch/show?type=diss&nr=18165.

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Lord, Steven John. "Computational and experimental study of hydraulic shock". Thesis, Imperial College London, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.265850.

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Libri sul tema "Computation speedup"

Roberts, Leonard. Computation of high speed transport aerodynamics. Stanford, Calif: Stanford University, Dept. of Aeronautics and Astronautics, 1991.

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Abolhassani, Jamshid S. Topology and grid adaption for high-speed flow computations. Hampton, Va: Langley Research Center, 1989.

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Tauber, Michael E. A review of high-speed, convective, heat-transfer computation methods. Moffett Field, Calif: Ames Research Center, 1989.

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Rostand, Philippe. Algebraic turbulence models for the computation of two-dimensional high speed flows using unstructured grids. Hampton, Va: ICASE, 1988.

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Gentzsch, Wolfgang. High speed and large scale scientific computing. Amsterdam: IOS Press, 2009.

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Gentzsch, Wolfgang. High speed and large scale scientific computing. Amsterdam: IOS Press, 2009.

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Thareja, R. R. Applications of an adaptive unstructured solution algorithm to the analysis of high speed flows. Washington, D. C: American Institute of Aeronautics and Astronautics, 1990.

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Coirier, William J. Efficient real gas Navier-Stokes computations of high speed flows using an LU scheme. [Washington, DC]: National Aeronautics and Space Administration, 1990.

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Taki, Mustafa. Computation of the aerodynamic performance of high-lift aerofoil systems at low-speed and transonic flow conditions. Manchester: UMIST, 1997.

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Groth, Clinton P. T. TVD flux-difference split methods for high-speed thermochemical nonequilibrium flows with strong shocks. [Toronto, Ont.]: University of Toronto, Graduate Dept. of Aerospace Science and Engineering, 1993.

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Capitoli di libri sul tema "Computation speedup"

Hines, Peter. "Quantum Speedup and Categorical Distributivity". In Computation, Logic, Games, and Quantum Foundations. The Many Facets of Samson Abramsky, 122–38. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38164-5_9.

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Demaine, Erik D., Mohammad Taghi Hajiaghayi e Dimitrios M. Thilikos. "Exponential Speedup of Fixed-Parameter Algorithms on K 3,3-Minor-Free or K 5-Minor-Free Graphs". In Algorithms and Computation, 262–73. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-36136-7_24.

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Kosheleva, Olga, e Vladik Kreinovich. "Relativistic Effects Can Be Used to Achieve a Universal Square-Root (Or Even Faster) Computation Speedup". In Fields of Logic and Computation III, 179–89. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-48006-6_13.

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Frid, Yelena, e Dan Gusfield. "Speedup of RNA Pseudoknotted Secondary Structure Recurrence Computation with the Four-Russians Method". In Combinatorial Optimization and Applications, 176–87. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31770-5_16.

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Chinazzo, André, Christian De Schryver, Katharina Zweig e Norbert Wehn. "Increasing the Sampling Efficiency for the Link Assessment Problem". In Lecture Notes in Computer Science, 39–56. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-21534-6_3.

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AbstractComplex graphs are at the heart of today’s big data challenges like recommendation systems, customer behavior modeling, or incident detection systems. One reoccurring task in these fields is the extraction of network motifs, which are subgraphs that are reoccurring and statistically significant. To assess the statistical significance of their occurrence, the observed values in the real network need to be compared to their expected value in a random graph model.In this chapter, we focus on the so-called Link Assessment (LA) problem, in particular for bipartite networks. Lacking closed-form solutions, we require stochastic Monte Carlo approaches that raise the challenge of finding appropriate metrics for quantifying the quality of results (QoR) together with suitable heuristics that stop the computation process if no further increase in quality is expected. We provide investigation results for three quality metrics and show that observing the right metrics reveals so-called phase transitions that can be used as a reliable basis for such heuristics. Finally, we propose a heuristic that has been evaluated with real-word datasets, providing a speedup of $$15.4\times $$ 15.4 × over previous approaches.

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Schwarz, Reinhard. "Speedup limits for tightly-coupled parallel computations". In Lecture Notes in Computer Science, 242–59. Berlin, Heidelberg: Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/3-540-60042-6_17.

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Rossow, C. C. "Flow Computation at All Speeds". In Notes on Numerical Fluid Mechanics and Multidisciplinary Design, 358–65. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-39604-8_45.

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Jiang, Bo-nan. "High-Speed Compressible Flows". In Scientific Computation, 303–28. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-662-03740-9_13.

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Akl, Selim G. "Unconventional Wisdom: Superlinear Speedup and Inherently Parallel Computations". In From Parallel to Emergent Computing, 347–66. Boca Raton, Florida : CRC Press, [2019] | Produced in celebration of the 25th anniversary of the International Journal of Parallel, Emergent, and Distributed Systems.: CRC Press, 2019. http://dx.doi.org/10.1201/9781315167084-16.

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Jiang, Bo-nan. "Low-Speed Compressible Viscous Flows". In Scientific Computation, 259–84. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-662-03740-9_11.

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Atti di convegni sul tema "Computation speedup"

Lawrens, Fernando, M. Rachmat Sule e Afnimar. "Parallel computation for speedup the computation time of direct determination of common-reflection-surface (CRS) attribute". In Proceedings of the 12th SEGJ International Symposium, Tokyo, Japan, 18-20 November 2015. Society of Exploration Geophysicists and Society of Exploration Geophysicists of Japan, 2015. http://dx.doi.org/10.1190/segj122015-069.

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Liu, Xiao, e Lei Xu. "CUDA Based Parallel Computation for Gauss Elimination Method". In ASME 2018 37th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/omae2018-78479.

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The Central Processing Unit (CPU) parallel algorithm based on Computing Unified Device Architecture (CUDA) has shown great power of computing speedup ability. What performance will the new technique show in the field of structural computation? We choose the Gauss elimination method as the research object. In this study, the parallel Gauss elimination is realized in CUDA on GPU. Furthermore, we carry out two groups of numerical experiments. The first group investigates the effect of Matrix Bandwidths (MBs) and Node Numbers (NNs) on speedup ratio. The second one compares our method with the commercial software by analyzing two actual structural problems in ocean engineering.

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Shen, Shuheng, Linli Xu, Jingchang Liu, Xianfeng Liang e Yifei Cheng. "Faster Distributed Deep Net Training: Computation and Communication Decoupled Stochastic Gradient Descent". In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/637.

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With the increase in the amount of data and the expansion of model scale, distributed parallel training becomes an important and successful technique to address the optimization challenges. Nevertheless, although distributed stochastic gradient descent (SGD) algorithms can achieve a linear iteration speedup, they are limited significantly in practice by the communication cost, making it difficult to achieve a linear time speedup. In this paper, we propose a computation and communication decoupled stochastic gradient descent (CoCoD-SGD) algorithm to run computation and communication in parallel to reduce the communication cost. We prove that CoCoD-SGD has a linear iteration speedup with respect to the total computation capability of the hardware resources. In addition, it has a lower communication complexity and better time speedup comparing with traditional distributed SGD algorithms. Experiments on deep neural network training demonstrate the significant improvements of CoCoD-SGD: when training ResNet18 and VGG16 with 16 Geforce GTX 1080Ti GPUs, CoCoD-SGD is up to 2-3 x faster than traditional synchronous SGD.

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von Bremen, Hubertus F., e Michael J. Bonilla. "Computation of Lyapunov Characteristic Exponents Using Parallel Computing". In ASME 2017 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/imece2017-71757.

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In [1] a method to accurately compute the Lyapunov Characteristic Exponents of continuous dynamical systems of arbitrary dimensions was presented. However, it can be computationally expensive, because it requires the computation of the time derivatives of the entries of the exponential of a skew-symmetric matrix. In this paper, we present an implementation of the method in [1] that takes advantage of the fact that some of the computations can be done in parallel. The speedup in the computations depends on the number of CPU cores used and the computer memory. Numerical simulations show improvements in efficiency when using the parallel implementation. Our implementation retains the accuracy of the method in [1] with the added advantage of a speedup in computations. Numerical simulation results are presented for a dynamical system of dimension seven and one of dimension forty-nine.

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Harvey, Nicholas, Robert Luke, James M. Keller e Derek Anderson. "Speedup of fuzzy logic through stream processing on Graphics Processing Units". In 2008 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2008. http://dx.doi.org/10.1109/cec.2008.4631314.

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Rathish Kumar, B. V., T. Yamaguchi, H. Liu e R. Himeno. "Parallel Computation of LV Hemodynamics". In ASME 2001 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2001. http://dx.doi.org/10.1115/imece2001/fed-24965.

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Abstract Computer Visualization of hemodynamics in Left Ventricle (LV) is of great significance in treating patients with dilated cardiomyopathy. Numerical simulations that enable such graphical visualization are computationally very intensive. So in the current study we propose to discuss details of the parallel computation of LV flow dynamics on distributed memory based vector parallel processing system (VPP700) under UXP/VPPF90. Speedup and efficiency factors obtained by the present parallel computational strategy will be presented. Results pertaining to the parallel solution to steady flow dynamics in LV model will also be presented.

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Fraigniaud, Pierre, Ami Paz e Sergio Rajsbaum. "A Speedup Theorem for Asynchronous Computation with Applications to Consensus and Approximate Agreement". In PODC '22: ACM Symposium on Principles of Distributed Computing. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3519270.3538422.

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Sumi, Kazuki, Yoshifumi Okamoto, Koji Fujiwara e Hidenori Sasaki. "Speedup of Flux Waveforms Control Using Deep Neural Network for Single Sheet Tester". In 2022 IEEE 20th Biennial Conference on Electromagnetic Field Computation (CEFC). IEEE, 2022. http://dx.doi.org/10.1109/cefc55061.2022.9940766.

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Zhao, Yong, e Chin Hoe Tai. "Parallel Computation of Unsteady Incompressible Viscous Flows Using an Unstructured Multigrid Method". In ASME 2002 International Mechanical Engineering Congress and Exposition. ASMEDC, 2002. http://dx.doi.org/10.1115/imece2002-39388.

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The development and validation of a parallel unstructured non-nested multigrid method for simulation of unsteady incompressible viscous flow is presented. The Navier-Stokes solver is based on the artificial compressibility method (ACM) [10] and a higher-order characteristics-based finite-volume scheme [8] on unstructured multigrids. Unsteady flow is calculated with an implicit dual time stepping scheme. The parallelization of the solver is achieved by a multigrid domain decomposition approach (MG-DD), using the Single Program Multiple Data (SPMD) programming paradigm and Message-Passing Interface (MPI) for communication of data. The parallel codes using single grids and multigrids are used to simulate steady and unsteady incompressible viscous flows over a circular cylinder for validation and performance evaluation purposes. Speedups and parallel efficiencies obtained by both the parallel single-grid and multigrid solvers are reasonably good for both test cases, using up to 32 processors on the SGI Origin 2000. A maximum speedup of 12 could be achieved on 16 processors for the unsteady flow. The parallel results obtained agree well with those of serial solvers and with numerical solutions obtained by other researchers, as well as experimental measurements.

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Hermanns, Miguel. "An order 102 speedup in the computation of the steady-state thermal response of geothermal heat exchangers". In INTERNATIONAL CONFERENCE OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING 2018 (ICCMSE 2018). Author(s), 2018. http://dx.doi.org/10.1063/1.5079205.

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Rapporti di organizzazioni sul tema "Computation speedup"

Duff, C. R. W. Data compression and computation speed. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1986. http://dx.doi.org/10.4095/315270.

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Alberse, John Robert, Adam Edward Biewer, John W. Grove e Roseanne Marie Cheng. Computational Study of High Speed Jets with xRage. Office of Scientific and Technical Information (OSTI), agosto 2019. http://dx.doi.org/10.2172/1557195.

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Biewer, Adam Edward, e John Robert Alberse. Computational Study of High Speed Jets with xRage. Office of Scientific and Technical Information (OSTI), agosto 2019. http://dx.doi.org/10.2172/1558033.

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Jiang, Minyee. Joint High Speed Sealift (JHSS) Appendage Resistance Computation Fluid Dynamics (CFD) Analysis. Fort Belvoir, VA: Defense Technical Information Center, dicembre 2009. http://dx.doi.org/10.21236/ada514547.

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Hafez, Mohamed. Symposium on Computational Fluid Dynamics and High Speed Flows. Fort Belvoir, VA: Defense Technical Information Center, giugno 2001. http://dx.doi.org/10.21236/ada399066.

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Haussling, H. J., R. W. Miller e R. M. Coleman. Computation of High-Speed Turbulent Flow about a Ship Model with a Transom Stern. Fort Belvoir, VA: Defense Technical Information Center, settembre 1997. http://dx.doi.org/10.21236/ada330142.

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Edwards, Jack R. Computational Simulation of High-Speed Projectiles in Air, Water, and Sand. Fort Belvoir, VA: Defense Technical Information Center, dicembre 2007. http://dx.doi.org/10.21236/ada474825.

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Wenren, Yonghu, Luke Allen e Robert Haehnel. SAGE-PEDD user manual. Engineer Research and Development Center (U.S.), agosto 2022. http://dx.doi.org/10.21079/11681/44960.

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SAGE-PEDD is a computational model for estimating snowdrift shapes around buildings. The main inputs to the model are wind speed, wind direction, building geometry and initial ground or snow-surface topography. Though developed mainly for predicting snowdrift shapes, it has the flexibility to accept other soil types, though this manual addresses snow only. This manual provides detailed information for set up, running, and viewing the output of a SAGE-PEDD simulation.

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Perumalla, Kalyan S., Maksudul Alam e Devin A. White. Computational Speed and Matching Quality using an Upper Bound on the Normalized Mutual Information. Test accounts, maggio 2017. http://dx.doi.org/10.2172/1360069.

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Tumin, Anatoli. Theoretical and Computational Studies of Stability, Transition and Flow Control in High-Speed Flows. Fort Belvoir, VA: Defense Technical Information Center, febbraio 2011. http://dx.doi.org/10.21236/ada547191.

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