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检索条件"任意字段=10th International Conference on Algorithms and Architectures for Parallel Processing"

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Data parallel application adaptivity and system-wide resource management in many-core architectures

Data parallel application adaptivity and system-wide resourc...

引用

10th international Symposium on Reconfigurable Computing: architectures, Tools, and Applications, ARC 2014

作者： Massari, Giuseppe Paone, Edoardo Scandale, Michele Bellasi, Patrick Palermo, Gianluca Zaccaria, Vittorio Agosta, Giovanni Fornaciari, William Silvano, Cristina Politecnico di Milano Piazza Leonardo da Vinci 32 I-20133 Milan Italy

ISBN: (纸本)9783319059594

Since the silicon technology entered the many-core era, new computing platforms are exploiting higher and higher levels of parallelism. thanks to scalable, clustered architectures, embedded systems and high-performance computing (HPC) are rapidly *** are also experiencing a rapid overlapping of the challenges related to efficient exploitation of processing resources. Platform-specific optimization and application boosting cannot be considered independently anymore. thus the increased interest towards broader and versatile methodologies, which could easily scale from the embedded up to the general-purpose domain. © 2014 Springer international Publishing Switzerland.

关键词： Embedded systems

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parallel Preconditioner for the Finite Volume Element Discretization of Elliptic Problems 1

引用

10th international conference on parallel processing and Applied Mathematics (PPAM)

作者： Marcinkowski, Leszek Rahman, Talal Univ Warsaw Fac Math PL-02097 Warsaw Poland

ISBN: (数字)9783642551956

ISBN: (纸本)9783642551956

In this paper we present a parallel preconditioner for the standard Finite Volume (FV) discretization of elliptic problems, using the standard continuous piecewise linear Finite Element (FE) function space. the proposed preconditioner is constructed using an abstract framework of the Additive Schwarz Method, and is fully parallel. the convergence rate of the Generalized Minimal Residual (GMRES) method with this preconditioner is shown to be almost optimal, i.e., it depends poly-logarithmically on the mesh sizes.

关键词： Finite Volume Element parallel Preconditioner Domain Decomposition Method Additive Schwarz Method

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Resolution of Linear Algebra for the Discrete Logarithm Problem Using GPU and Multi-core architectures 1

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20th international Euro-Par conference on parallel processing (Euro-Par)

作者： Jeljeli, Hamza Univ Lorraine CARAMEL Project Team LORIA INRIACNRS Campus SciBP 239 F-54506 Vandoeuvre Les Nancy France

ISBN: (数字)9783319098739

ISBN: (纸本)9783319098739;9783319098722

In cryptanalysis, solving the discrete logarithm problem (DLP) is key to assessing the security of many public-key cryptosystems. the index-calculus methods, that attack the DLP in multiplicative subgroups of finite fields, require solving large sparse systems of linear equations modulo large primes. this article deals with how we can run this computation on GPU- and multi-core-based clusters, featuring InfiniBand networking. More specifically, we present the sparse linear algebra algorithms that are proposed in the literature, in particular the block Wiedemann algorithm. We discuss the parallelization of the central matrix-vector product operation from both algorithmic and practical points of view, and illustrate how our approach has contributed to the recent record-sized DLP computation in GF(2(809)).

关键词： Discrete logarithm problem sparse linear algebra parallel computing GPU acceleration multi-core processors InfiniBand

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parallel Approach to Monte Carlo Simulation for Option Price Sensitivities Using the Adjoint and Interval Analysis 1

引用

10th international conference on parallel processing and Applied Mathematics (PPAM)

作者： Kozikowski, Grzegorz Kubica, Bartlomiej Jacek Univ Manchester Sch Comp Sci Manchester Lancs England

ISBN: (数字)9783642551956

ISBN: (纸本)9783642551956

this paper concerns a new approach to evaluation of Option Price sensitivities using the Monte Carlo simulation, based on the parallel GPU architecture and Automatic Differentiation methods. In order to study rounding errors, the interval arithmetic is used. Considerations are based on two implementations of the algorithm - the sequential and parallel ones. For efficient differentiation, the Adjoint method is employed. Computational experiments include analysis of performance, uncertainty error and rounding error and consider Black-Scholes and Heston models.

关键词： Option pricing the greeks Automatic Differentiation the Adjoint Calibration Interval analysis CUDA

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GPU Acceleration of Finding Maximum Eigenvalue of Positive Matrices 1

引用

14th international conference on algorithms and architectures for parallel processing (ICA3PP)

作者： Tian, Ning Guo, Longjiang Ai, Chunyu Ren, Meirui Li, Jinbao Heilongjiang Univ Sch Comp Sci & Technol Harbin Peoples R China Key Lab Database & Parallel Comp Heilongjiang Peoples R China Univ S Carolina Upstate Div Math & Comp Sci Upstate Peoples R China

ISBN: (数字)9783319111940

ISBN: (纸本)9783319111940;9783319111933

Matrix eigenvalue theory has become an important analysis tool in scientific computing. Sometimes, people do not need to find all eigenvalues but only the maximum eigenvalue. Existing algorithms of finding the maximum eigenvalue of matrices are implemented sequentially. With the increasing of the orders of matrices, the workload of calculation is getting heavier. therefore, traditional sequential methods are unable to meet the need of fast calculation for large matrices. this paper proposes a parallel algorithm named PA-ST to find the maximum eigenvalue of positive matrices by using similarity transformation which is implemented by CUDA (Computer Unified Device Architecture) on GPU (Graphic Process Unit). To the best of our knowledge, this is the first CUDA based parallel algorithm of calculating maximum eigenvalue of matrices. In order to improve the performance, optimization techniques are applied in this paper such as using the shared memory rather than the global memory to improve the speed of computation, avoiding bank conflicts by setting the span index, satisfying the principle of coalesced memory access, and by using single-precision floating-point arithmetic and the pinned memory to reduce the copy operation and obtain higher data transfer bandwidth between the host and the GPU device. the experimental results show that the similarity transformation technique can significantly shorten the running time compared to the sequential algorithm and the speedup ratio is nearly stable when the number of iterations increases. As the matrix order increases, the running time of the sequential algorithm and PA-ST increases correspondingly. Experiments also show that the speedup ratio of the PA-ST is between 2.85 and 35.028.

关键词： Maximum Eigenvalue Positive Matrix Similarity Transformation GPU CUDA

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A parallel and Scalable Iterative Solver for Sequences of Dense Eigenproblems Arising in FLAPW 1

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10th international conference on parallel processing and Applied Mathematics (PPAM)

作者： Berljafa, Mario Di Napoli, Edoardo Univ Manchester Sch Math Manchester M13 9PL Lancs England

ISBN: (数字)9783642551956

ISBN: (纸本)9783642551956

In one of the most important methods in Density Functional theory - the Full-Potential Linearized Augmented Plane Wave (FLAPW) method - dense generalized eigenproblems are organized in long sequences. Moreover each eigenproblem is strongly correlated to the next one in the sequence. We propose a novel approach which exploits such correlation through the use of an eigensolver based on subspace iteration and accelerated with Chebyshev polynomials. the resulting solver, parallelized using the Elemental library framework, achieves excellent scalability and is competitive with current dense parallel eigensolvers.

关键词： Chebyshev polynomials Subspace iteration Eigenproblem sequence Density functional theory Elemental

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parallel Efficiency of an Adaptive, Dynamically Balanced Flow Solver 1

引用

10th international conference on parallel processing and Applied Mathematics (PPAM)

作者： Gepner, Stanislaw Majewski, Jerzy Rokicki, Jacek Warsaw Univ Technol Inst Aeronaut & Appl Mech PL-00665 Warsaw Poland

ISBN: (数字)9783642551956

ISBN: (纸本)9783642551956

Computations in Fluid Dynamics require minimisation of time in which the result could be obtained. While parallel techniques allow for handling of large problems, it is the adaptivity that ensures that computational effort is focused on interesting regions in time and space. parallel efflciency, in a domain decomposition based approach, strongly depends on partitioning quality. For adaptive simulation partitioning quality is lost due to the dynamic modification of the computational mesh. Maintaining high efflciency of parallelization requires rebalancing of the numerical load. this paper presents performance results of an adaptive and dynamically balanced in-house flow solver. the results indicate that the rebalancing technique might be used to remedy to the adverse effects of adaptivity on overall parallel performance.

关键词： parallel cfd Adaptation Dynamic load balancing Mesh refinement parallel efflciency Super linear speed-up

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Finding Enclosures for Linear Systems Using Interval Matrix Multiplication in CUDA 1

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10th international conference on parallel processing and Applied Mathematics (PPAM)

作者： Dallmann, Alexander Beck, Philip-Daniel von Gudenberg, Juergen Wolff Univ Wurzburg Chair Comp Sci 2 D-97074 Wurzburg Germany

ISBN: (数字)9783642551956

ISBN: (纸本)9783642551956

In this paper we present CUDA kernels that compute an interval matrix product. Starting from a naive implementation we investigate possible speedups using commonly known techniques from standard matrix multiplication. We also evaluate the achieved speedup when our kernels are used to accelerate a variant of an existing algorithm that finds an enclosure for the solution of a linear system. Moreover the quality of our enclosure is discussed.

关键词： GPGPU Interval arithmetic Linear algebra parallel computing

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Supporting Smart Electric Vehicle Charging with Information-Centric Networking 10

Supporting Smart Electric Vehicle Charging with Information-...

引用

10th international conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness (QShine)

作者： Katsaros, Konstantinos V. Chai, Wei Koong Vieira, Barbara Pavlou, George UCL London WC1E 6BT England Radboud Univ Nijmegen NL-6525 ED Nijmegen Netherlands

ISBN: (纸本)9781631900259

Inspired by the proliferation of content-centric applications in the Internet, Information-Centric Networking (ICN) has emerged as a promising networking paradigm. Focusing on the delivery of content instead of the pairwise communication between end-hosts, ICN inherently supports location-independent content/information distribution, through the means of in-network caching and multicast;as well as mobile computing. However, so far the vast majority of ICN research efforts have mostly focused on the design of sound and scalable architectures and protocols for the current Internet application landscape. In this paper, we revisit ICN in the context of a radically different application environment of smart grids and in particular, the case of smart charging of electric vehicles. Based on a thorough description of the currently forming application environment in the Netherlands, we highlight the inefficiencies resulting from a host-centric model. We then show how ICN can address these limitations and ultimately support quality and security in such application environment. Besides qualitative benefits, our preliminary analysis also demonstrates that ICN can substantially reduce communication and security complexity, thus fostering the development and widespread adoption of the smart charging application.

关键词： smart grid electric vehicles caching in-network processing congestion management load balancing

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An Identity Parareal Method for Temporal parallel Computations

An Identity Parareal Method for Temporal Parallel Computatio...

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10th international conference on parallel processing and Applied Mathematics (PPAM)

作者： Takami, Toshiya Fukudome, Daiki Kyushu Univ Res Inst Informat Technol Higashi Ku 6-10-1 Hakozaki Fukuoka 8128581 Japan Kyushu Univ Grad Sch Informat Sci & Elect Engn Nishi Ku Fukuoka 8190395 Japan

ISBN: (纸本)9783642552243

A new simplified definition of time-domain parallelism is introduced for explicit time evolution calculations, and is implemented on parallel machines with bucket-brigade type communications. By the use of an identity operator instead of introducing an approximate solver, a recurrence formula for the parareal-in-time algorithm is much simplified. In spite of such a simple definition, it is applicable to many of explicit time-evolution calculations. In addition, this approach overcomes several drawbacks known in the original parareal-in-time method. In order to implement this algorithm on parallel machines, a parallel bucket-brigade interface is introduced, which reduces programming and tuning costs for complicated space-time parallel programs.

关键词： Parareal-in-time Bucket-brigade communication Strong scaling Massively parallel machine Scientific computing

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