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2nd International Symposium on Instrumentation and Measurement, Sensor Network and Automation (IMSNA)

作者： Huang, Bohu Zhang, Haibin Xidian Univ Inst Comp Theory & Technol Xian Peoples R China

ISBN: (纸本)9781479927166

As the sizes of FPGA device grow, the long run-time of the placement is becoming a great challenge for the FPGA design flow. Simulated annealing is the best-known method applied to this problem due to the good quality of result (QoR), but its computation time seems not satisfactory. In this paper, we propose a parallel placement algorithm named MPP-SA (Multi-core parallel Placement algorithm based on Simulated Annealing). Our goal is to provide a fast placement algorithm with high QoR. MPP-SA has the same annealing schedule as the traditional simulated annealing, but it uses the parallel approach to move blocks concurrently by multiple threads that are run on different cores of the same processor. To ensure the correctness of the results, MPP-SA also uses synchronization technology and lock mechanism, which brings some overheads. However, experiment results show that these overheads have not seriously affected the performance of our algorithm, especial for large circuits. Compared with the placement algorithm of T_VPlace in VPR5.0, MPP-SA is able to decrease the run-time of 5 different size benchmark circuits by an average of 32%-42% without losing QoR.

关键词： FPGA multi-core parallel algorithm simulated annealing design AIDS

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parallel coordinate descent for the Adaboost problem

Parallel coordinate descent for the Adaboost problem

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12th International Conference on Machine Learning and Applications (ICMLA)

作者： Fercoq, Olivier Univ Edinburgh Sch Math Edinburgh EH8 9YL Midlothian Scotland

ISBN: (纸本)9780769551449

We design a randomised parallel version of Adaboost based on previous studies on parallel coordinate descent. The algorithm uses the fact that the logarithm of the exponential loss is a function with coordinate-wise Lipschitz continuous gradient, in order to define the step lengths. We provide the proof of convergence for this randomised Adaboost algorithm and a theoretical parallelisation speedup factor. We finally provide numerical examples on learning problems of various sizes that show that the algorithm is competitive with concurrent approaches, especially for large scale problems.

关键词： Adaboost iteration complexity parallel algorithm randomised coordinate descent parallel algorithms ADABOOST descent Coordinates algorithms Learning Problems parallel Lines step size logarithm (log) RANDOMISING speedup factor

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parallel Hand Shape Classification

Parallel Hand Shape Classification

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15th IEEE International Symposium on Multimedia (ISM)

作者： Nalepa, Jakub Kawulok, Michal Future Proc Gliwice Poland Silesian Tech Univ Inst Informat Gliwice Poland

ISBN: (纸本)9780769551401

This paper introduces a new parallel algorithm (PA) for fast hand shape classification. This problem is challenging as a hand is characterized by a high number of degrees of freedom. Our objective is to design and implement a robust algorithm suitable for real-time applications. We show how the analysis time can be decreased, together with the increase of the classification accuracy, by the means of parallelization. Also, we propose to combine the shape contexts approach with the appearance-based techniques to increase the efficacy of the PA. An extensive experimental study confirms the effectiveness of the proposed PA compared with other state-of-the-art methods.

关键词： hand shape classification parallel algorithm gesture recognition

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Hierarchical parallel Matrix Multiplication on Large-Scale Distributed Memory Platforms

Hierarchical Parallel Matrix Multiplication on Large-Scale D...

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42nd Annual International Conference on parallel Processing (ICPP)

作者： Quintin, Jean-Noel Hasanov, Khalid Lastovetsky, Alexey Extrem Computing R and D Bull France University College Dublin Dublin 4 Belfield Ireland

ISBN: (纸本)9780769551173

Matrix multiplication is a very important computation kernel both in its own right as a building block of many scientific applications and as a popular representative for other scientific applications. Cannon's algorithm which dates back to 1969 was the first efficient algorithm for parallel matrix multiplication providing theoretically optimal communication cost. However this algorithm requires a square number of processors. In the mid-1990s, the SUMMA algorithm was introduced. SUMMA overcomes the shortcomings of Cannon's algorithm as it can be used on a non-square number of processors as well. Since then the number of processors in HPC platforms has increased by two orders of magnitude making the contribution of communication in the overall execution time more significant. Therefore, the state of the art parallel matrix multiplication algorithms should be revisited to reduce the communication cost further. This paper introduces a new parallel matrix multiplication algorithm, Hierarchical SUMMA (HSUMMA), which is a redesign of SUMMA. Our algorithm reduces the communication cost of SUMMA by introducing a two-level virtual hierarchy into the two-dimensional arrangement of processors. Experiments on an IBM BlueGene/P demonstrate the reduction of communication cost up to 2.08 times on 2048 cores and up to 5.89 times on 16384 cores.

关键词： BlueGene Communication Exascale Grid5000 Hierarchical algorithm Matrix multiplication parallel algorithm

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GPU-accelerated parallel 3D Image Thinning

GPU-accelerated Parallel 3D Image Thinning

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15th IEEE International Conference on High Performance Computing and Communications (HPCC) /11th IEEE/IFIP International Conference on Embedded and Ubiquitous Computing (EUC)

作者： Hu, Bingfeng Yang, Xuan Shenzhen Univ Coll Comp Sci & Software Engn Shenzhen Guangdong Peoples R China Natl High Performance Comp Ctr Shenzhen Guangdong Peoples R China

ISBN: (纸本)9780769550886

The skeletons of the objects in 3D images can be extracted by using 3D image thinning. The application of 3D image thinning for image analysis is hampered by its considerable computation time. By employing the graphics processing unit (GPU), which has tremendous powerful computing power at an incomparable performance-to-cost ratio, the calculation of 3D image thinning can be accelerated. In this paper, we proposed a parallel implementation approach on GPU for the 3D 12-subiteration image thinning algorithm, in which object voxels of 3D image are assigned to threads based on the characteristic of sparse 3D image data. The performance of our approach is analyzed with different image sizes, the ratio of object voxels and the number of thread grids on GPU. The performance of the traditional threads assignment strategy and new threads assignment strategy are compared to show that the proposed approach is more efficient.

关键词： 3D image thinning GPU parallel algorithm

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Implementation of a parallel method for the graph coloring problem using MPI and verification of the number of processors on it

Implementation of a parallel method for the graph coloring p...

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5th Conference on Information and Knowledge Technology (IKT)

作者： Khayami, S. R. Alinezhad, A. Jafari, H. Shiraz Univ Technol Dept Comp Engn & IT Shiraz Iran

ISBN: (纸本)9781467364904;9781467364898

In this paper, a parallel version based on a pipeline of innovative methods for graph coloring in a sequential mode is presented. The results of the execution time for parallel implementation in the C++ language using the Message Passing Interface (MPI) on a multi-processor machine is presented and discussed. This problem also has been implemented in a fully sequential and recursive mode, in the same environment, and the results of comparing them to parallel implementation have been reported.

关键词： graph coloring parallel algorithm message passing interface sequential first fit algorithm

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Performance Analysis of parallel Data Distribution Management in Large-scale Battlefield Simulation 3

Performance Analysis of Parallel Data Distribution Managemen...

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3rd International Conference on Computer Science and Network Technology (ICCSNT)

作者： Rao, Dehu Hu, Xiaofeng Wu, Lin Natl Def Univ Beijing 100091 Peoples R China Navy Univ Engineer Wuhan 430033 Hubei Peoples R China

ISBN: (纸本)9781479905614

There are so many operational entities in large-scale battlefield simulation. Entities may interact with each other in a real-time and frequent manner, which may restrain the performance of the simulation system. From researches in recent decades, it can be concluded that the Data Distribution Management (DDM) is an effective solution for this issue. Although the main focus for realizing DDM is Pub/Sub paradigm, recent literatures has implied that the serial realization of various DDM algorithms has encountered the performance bottleneck. The development of computer microprocessors is making progress from multi-core to many-core, so developing the parallel processing capabilities for DDM in multi-processors platform is the most effective approach to promote runtime performance. Based on the analysis and comparison of region-based, fixed grid-based, dynamic grid based and hierarchical grid-based algorithm for region matching, the parallel algorithms for these methods are realized according to the matching task decomposing. The experiments results manifest that parallel algorithms can gain about 40% similar to 60% performance improvements and support the research of parallel simulation engine of wargame.

关键词： Large-scale Battlefield Simulation Data Distribution Management Publish /Subscribe Region Matching parallel algorithm

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Efficient Transmitting Antenna Selection for MIMO Systems via parallel Approach

Efficient Transmitting Antenna Selection for MIMO Systems vi...

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IEEE International Conference on Communications (ICC)

作者： Chang, Shih Yu Wu, Hsiao-Chun Natl Tsing Hua Univ Dept Comp Sci Hsinchu Taiwan Louisiana State Univ Sch Elect Engn & Comp Sci Baton Rouge LA 70803 USA

ISBN: (纸本)9781467331227

In this paper, we propose a new low-complexity optimal transmitting antenna selection algorithm for multiple-input multiple-output (MIMO) systems. Different from the conventional optimal antenna selection methods, our proposed algorithm can approximate the inverse matrix subject to an error tolerance. However, the antenna selection optimality can often be obtained as the same outcome from the exact matrix inverse. Furthermore, our proposed matrix inverse approximation algorithm can be greatly expedited by using parallel computing. With significantly reduced complexity using many microprocessors, our proposed method is very appealing to the future MIMO technologies.

关键词： MIMO antenna subset selection matrix inverse approximation parallel algorithm

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Fast parallel algorithms for the x-ray transform and its adjoint

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MEDICAL PHYSICS 2012年第11期39卷 7110-7120页

作者： Gao, Hao Emory Univ Dept Math & Comp Sci Atlanta GA 30322 USA Emory Univ Dept Radiol & Imaging Sci Atlanta GA 30322 USA

Purpose: Iterative reconstruction methods often offer better imaging quality and allow for reconstructions with lower imaging dose than classical methods in computed tomography. However, the computational speed is a major concern for these iterative methods, for which the x-ray transform and its adjoint are two most time-consuming components. The speed issue becomes even notable for the 3D imaging such as cone beam scans or helical scans, since the x-ray transform and its adjoint are frequently computed as there is usually not enough computer memory to save the corresponding system matrix. The purpose of this paper is to optimize the algorithm for computing the x-ray transform and its adjoint, and their parallel computation. Methods: The fast and highly parallelizable algorithms for the x-ray transform and its adjoint are proposed for the infinitely narrow beam in both 2D and 3D. The extension of these fast algorithms to the finite-size beam is proposed in 2D and discussed in 3D. Results: The CPU and GPU codes are available at https://***/site/fastxraytransform. The proposed algorithm is faster than Siddon's algorithm for computing the x-ray transform. In particular, the improvement for the parallel computation can be an order of magnitude. Conclusions: The authors have proposed fast and highly parallelizable algorithms for the x-ray transform and its adjoint, which are extendable for the finite-size beam. The proposed algorithms are suitable for parallel computing in the sense that the computational cost per parallel thread is O(1). (C) 2012 American Association of Physicists in Medicine. [http://***/10.1118/1.4761867]

关键词： x-ray transform discrete Radon transform parallel algorithm CT GPU

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A novel algorithm and its parallelization for solving nearly penta-diagonal linear systems

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INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS 2013年第2期90卷 435-444页

作者： Jia, Ji-Teng Sogabe, Tomohiro Xi An Jiao Tong Univ Dept Math Sci Xian 710049 Shaanxi Peoples R China Aichi Prefectural Univ Grad Sch Informat Sci & Technol Nagakute Aichi 4801198 Japan

In the current paper, a new serial algorithm for solving nearly penta-diagonal linear systems is presented. The computational cost of the algorithm is less than or almost equal to those of recent successful algorithms [J. Jia, Q. Kong, and T. Sogabe, A fast numerical algorithm for solving nearly penta-diagonal linear systems, Int. J. Comput. Math. 89 (2012), pp. 851860;X.G. Lv and J. Le, A note on solving nearly penta-diagonal linear systems, Appl. Math. Comput. 204 (2008), pp. 707712;S.N. Neossi Nguetchue and S. Abelman, A computational algorithm for solving nearly penta-diagonal linear systems, Appl. Math. Comput. 203 (2008), pp. 629634]. Moreover, it is suitable for developing its parallel algorithms. One of the parallel algorithms is given and is shown to be promising. The implementation of the algorithms using Computer Algebra Systems such as MATLAB and MAPLE is straightforward. Two numerical examples are given in order to illustrate the validity and efficiency of our algorithms.

关键词： nearly penta-diagonal matrices parallel algorithm linear systems Crout LU decomposition computer algebra systems 15A09 15A23 65F30 33F10

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