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基于GPU的海战场环境研究
Research of Ocean Battlefield Simulation System Based on GPU
 [PDF]

邵刚, 姜华
Computer Science and Application (CSA) , 2012, DOI: 10.12677/CSA.2012.24032
Abstract: 海战场环境仿真是海军作战模拟的重要内容,逼真的战场环境实时仿真是作战模拟的基础,它为保障、分析、作战评估等试验提供了仿真平台。本文采用GPU的编程技术,研制开发高度逼真的海洋战场视景仿真系统。
The Simulation of naval battlefield environment is very important in fighting simulation system. The vivid and real-time simulation of ocean battlefield environment is the base of fighting simulation system, which offers a very nice simulation platform for fighting evaluating. This paper that used GPU program technique, researches how to develop more realistic simulation system of ocean battlefield.
State of the Art for String Analysis and Pattern Search Using CPU and GPU Based Programming  [PDF]
Mario Góngora-Blandón, Miguel Vargas-Lombardo
Journal of Information Security (JIS) , 2012, DOI: 10.4236/jis.2012.34038
Abstract: String matching algorithms are an important piece in the network intrusion detection systems. In these systems, the chain coincidence algorithms occupy more than half the CPU process time. The GPU technology has showed in the past years to have a superior performance on these types of applications than the CPU. In this article we perform a review of the state of the art of the different string matching algorithms used in network intrusion detection systems; and also some research done about CPU and GPU on this area.
Efficient Simulation of Nonlinear Heat Transfer during Thermal Spraying of Complex Workpieces  [PDF]
Rolf Berthelsen, Thomas Wiederkehr, Ralf Denzer, Andreas Menzel, Heinrich Müller
World Journal of Mechanics (WJM) , 2014, DOI: 10.4236/wjm.2014.49029
Abstract: The quality of coatings, produced by thermal spraying processes, considerably decreases with the occurrence of higher residual stresses, which are especially pronounced for complex workpiece geometries. To understand the occurring effects and to aid in the planning of coating processes, simulations of the highly transient energy flux of the HVOF spray gun into the substrate are of great value. In this article, a software framework for the simulation of nonlinear heat transfer during (HVOF) thermal spraying is presented. One part of this framework employs an efficient GPU-based simulation algorithm to compute the time-dependent input boundary conditions for a spray gun that moves along a complex workpiece of arbitrary shape. The other part employs a finite-element model for a rigid heat conductor adhering to the computed boundary conditions. The model is derived from the fundamental equations of continuum thermodynamics where nonlinear temperature-depending heat conduction is assumed.<
Visualization of Pareto Solutions by Spherical Self-Organizing Map and It’s acceleration on a GPU  [PDF]
Masato Yoshimi, Takuya Kuhara, Kaname Nishimoto, Mitsunori Miki, Tomoyuki Hiroyasu
Journal of Software Engineering and Applications (JSEA) , 2012, DOI: 10.4236/jsea.2012.53020
Abstract: In this study, we visualize Pareto-optimum solutions derived from multiple-objective optimization using spherical self-organizing maps (SOMs) that lay out SOM data in three dimensions. There have been a wide range of studies involving plane SOMs where Pareto-optimal solutions are mapped to a plane. However, plane SOMs have an issue that similar data differing in a few specific variables are often placed at far ends of the map, compromising intuitiveness of the visualization. We show in this study that spherical SOMs allow us to find similarities in data otherwise undetectable with plane SOMs. We also implement and evaluate the performance using parallel sphere processing with several GPU environments.
Implementación en GPU del Estadístico t para análisis de expresión genética en microarreglos
Eduardo Romero-Vivas,Fernando Daniel Von Borstel Luna,Isaac Villa-Medina
Acta Universitaria , 2012,
Abstract: Introducción: Los microarreglos de ADN son utilizados para analizar simultáneamente el nivel de expresión de genes bajo múltiples condiciones; sin embargo, la masiva cantidad de datos generados hacen que su análisis sea un candidato ideal para su procesamiento en paralelo. La utilización de Unidades de Procesamiento Gráfico de Propósito General (GPG-PU) es una alternativa eficiente y de bajo costo, comparada contra aplicaciones que utilizan CPUs. Objetivo: Implementación de algoritmos basados en la Arquitectura de Dispositivos de Cómputo Unificado (CUDA) para determinar la significancia estadística en la evalua-ción de los niveles de expresión de genes en microarreglos. Método: Análisis paramétrico t-pareado desarrollado en CUDA. Resultados: La evaluación utilizando la implementación en CUDA es 5 a 30 veces más rápida que la implementación en CPU, dependiendo del nú-mero de genes a ser evaluados. Conclusiones: Los resultados son comparados contra las implementaciones tradicionales en CPU; se proponen mejoras.
Accelerating Network Coding on Many-core GPUs and Multi-core CPUs
Xiaowen Chu,Kaiyong Zhao,Mea Wang
Journal of Communications , 2009, DOI: 10.4304/jcm.4.11.902-909
Abstract: Network coding has recently been widely applied in various distributed systems for throughput improvement and/or resilience to network dynamics. However, the computational overhead introduced by network coding operations is not negligible and has become the obstacle for practical deployment of network coding. In this paper, we exploit the computing power of commodity many-core Graphic Processing Units (GPUs) and multi-core CPUs to accelerate the network coding operations. We propose a set of parallel algorithms that maximize the parallelism of the encoding and decoding processes and fully utilize the power of GPUs. This paper also shares our optimization design choices and our workarounds to the challenges encountered in working with GPUs. With our implementation of the algorithms, we are able to achieve significant speedup over existing solutions on CPUs.
Incoherent Ray tracing on GPU
Xin Yang,Duan-qing Xu,Lei Zhao
Journal of Multimedia , 2010, DOI: 10.4304/jmm.5.3.259-267
Abstract: Tracing secondary rays, such as reflection, refraction and shadow rays, can often be the most costly step in a modern real-time ray tracer. In this paper, we propose a new approach to ray tracing on GPU. Our approach is especially efficient for incoherent rays. Combined with the common packets ray tracing, we propose a different data-parallel approach to ray tracing on GPU, in which individual ray intersect with k different nodes/triangles in the same operation. Besides, we add some additional information in the construction of acceleration structure, and propose a new approach to travel the acceleration structure. Our acceleration structure needn’t collapse, so it could be built very efficiently, which is promising for dynamic scenes. Despite this approach is slower for primary rays, but demonstrate that it performs better than those techniques as soon as incoherent rays are considered.
Multi-prediction particle filter for efficient parallelized implementation
Chu Chun-Yuan,Chao Chih-Hao,Chao Min-An,Wu An-Yeu
EURASIP Journal on Advances in Signal Processing , 2011,
Abstract: Particle filter (PF) is an emerging signal processing methodology, which can effectively deal with nonlinear and non-Gaussian signals by a sample-based approximation of the state probability density function. The particle generation of the PF is a data-independent procedure and can be implemented in parallel. However, the resampling procedure in the PF is a sequential task in natural and difficult to be parallelized. Based on the Amdahl's law, the sequential portion of a task limits the maximum speed-up of the parallelized implementation. Moreover, large particle number is usually required to obtain an accurate estimation, and the complexity of the resampling procedure is highly related to the number of particles. In this article, we propose a multi-prediction (MP) framework with two selection approaches. The proposed MP framework can reduce the required particle number for target estimation accuracy, and the sequential operation of the resampling can be reduced. Besides, the overhead of the MP framework can be easily compensated by parallel implementation. The proposed MP-PF alleviates the global sequential operation by increasing the local parallel computation. In addition, the MP-PF is very suitable for multi-core graphics processing unit (GPU) platform, which is a popular parallel processing architecture. We give prototypical implementations of the MP-PFs on multi-core GPU platform. For the classic bearing-only tracking experiments, the proposed MP-PF can be 25.1 and 15.3 times faster than the sequential importance resampling-PF with 10,000 and 20,000 particles, respectively. Hence, the proposed MP-PF can enhance the efficiency of the parallelization.
Parallel Computing of Discrete Element Method on GPU  [PDF]
Teruyoshi Washizawa, Yasuhiro Nakahara
Applied Mathematics (AM) , 2013, DOI: 10.4236/am.2013.41A037
Abstract:

General purpose computing on GPU for scientific computing has been rapidly growing in recent years. We investigate the applicability of GPU to discrete element method (DEM) often used in particle motion simulation. NVIDIA provides a sample code for this type of simulation, which obtained superior performance than CPU in computational time. A computational model of the contact force in NVIDIA’s sample code is, however, too simple to use in practice. This paper modifies the NVIDIA’s simple model by replacing it with the practical model. The computing speed of the practical model on GPU is compared with the simple one on GPU and with the practical one on CPU in numerical experiments. The result shows that the practical model on GPU obtains the computing speed 6 times faster than the practical one on CPU while 7 times slower than that of the simple one on GPU. The effects of the GPU architectures on the computing speed are analyzed.

Evaluation of CDK6 and p16/INK4a-Derived Peptides Interaction  [PDF]
Andrey Kazennov, Andrey Alekseenko, Vladimir Bozhenko, Tatiana Kulinich, Nikolay Shuvalov, Yaroslav Kholodov
Computational Molecular Bioscience (CMB) , 2013, DOI: 10.4236/cmb.2013.33007
Abstract:  The goal of this work is the development of novel peptides with high efficacy of inhibiting activity of CDK6/CyclinD complex. The peptides were derived from primary sequence of P16 protein and its homologues. The interactions between CDK6 and P16/INK4a-derived peptides are studied with molecular dynamics simulation employing umbrella sampling method. The SASA implicit solvent model was used for simulation, which was accelerated using NVIDIA GPUs.
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