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The Mapping Framework and Optimizing Strategy for Block Cryptography algorithms on Cell Broadband Engine

The Mapping Framework and Optimizing Strategy for Block Cryp...

引用

IEEE International conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)

作者： Mu Xu Hong An Gu Liu Yaobin Wang Guang Xu Ping Yao Xiurui Hao Wenting Han School of Computer Science and Technology University of Science and Technology Hefei China Key Laboratory of Computer System and Architecture Chinese Academy and Sciences Beijing China

The Cell Broadband Engine is a typical heterogeneous chip multiprocessor which provides potential high performance for computing-intensive applications. Our researches focus on how to use Cell to speed up block cryptography applications. In this paper, we propose a mapping framework for block cryptography working in ECB mode and corresponding optimizing strategy. We take four algorithms(RC5, 3DES, AES, and Twofish) as benchmark and implement these four algorithms using Cell programming language. In order to enhance the performance, we present an optimizing strategy and evaluate the effects of the optimizing methods including compiler optimization, dual buffering, vectorization, and loop unrolling. The experiments indicate that all these four algorithms can obtain 5-20 times speedup compared with traditional processors, which shows that our mapping framework and optimizing strategy are effective for the block cryptography algorithms.

关键词： Engines Elliptic curve cryptography Computer architecture Optimizing compilers optimization methods Distributed computing Application software high performance computing Computer applications Clocks

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high-performance Tsunami Wave Propagation Modeling

High-Performance Tsunami Wave Propagation Modeling

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10th International conference on Parallel Computing Technologies

作者： Lavrentiev-jr, Mikhail Romanenko, Alexey Titov, Vasily Vazhenin, Alexander Russian Acad Sci Sobolev Inst Math Novosibirsk Russia Novosibirsk State Univ Novosibirsk Russia NOAA Pacific Marine Environm Lab Seattle WA USA Univ Aizu Fukushima Japan

ISBN: (纸本)9783642032745

Strongest earthquake of December 26, 2004 generated catastrophic tsunami in Indian Ocean. This shows that, in spite of recent technology progress, population at coastal zone is not protected against tsunami hazard. Here, we address the problem of tsunami risks mitigation. Note that prediction of tsunami wave parameters at certain locations should be made as early as possible to provide enough time for evacuation. Modern computational technologies can accurately calculate tsunami wave propagation over the deep ocean provided that initial displacement (perturbation of the sea bed at tsunami source) is known. Modern deep ocean tsunameters provide direct measurement of the passing tsunami wave in real time, which help to estimate initial displacement parameters right after the tsunami wave is recorded at one of the deep ocean buoys. Therefore, fast tsunami propagation code that can calculate tsunami evolution from estimated model source becomes critical for timely evacuation decision for many coastal communities in case of a strong tsunami. Numerical simulation of tsunami wave is very important task for risk evaluation, assessment and mitigation. Here we discuss a part of MOST (Method of Splitting Tsunami) software package, which has been accepted by the USA National Ocean and Atmosphere Administration as the basic tool to calculate tsunami wave propagation and evaluation of inundation parameters. Our main objectives are speed up the sequential program, and adaptation of this program for shared memory systems (OpenMP) and CELL architecture. optimization of the existing parallel and sequential code for the task of tsunami wave propagation modeling as well as an adaptation of this code for systems based on CELL BE processors (e.g. SONY PlayStation3) is discussed. The paper also covers approaches and techniques for programs optimization and adaptations, and obtained results.

关键词： Tsunami Wave Propagation Modeling Method of Splitting Tsunami Fine-grain Parallel algorithms OpenMP Paradigm Cell BE Architecture

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optimization of neural network with fixed-point weights and touch-screen calibration

Optimization of neural network with fixed-point weights and ...

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IEEE conference on Industrial Electronics and Applications (ICIEA)

作者： Bao Jian Zhou Bin School of Information Science and Engineering East China University of Science and Technology Shanghai China Institute of Intelligent and Software Technology Hangzhou Dianzi University Hangzhou China

ISBN: (纸本)9781424427994

In order to resolve the contradiction between computing performance and precision of the traditional neural network, and accord with the characteristic of double-quick computing and tidy memory capacitance in embedded systems, a NN optimization method is proposed. Firstly, we represented a type of NNs with fixed-point weights (FPNN) and its training method. Secondly, the continuous nonlinear activation function of the neuron was transformed into discrete and linear function using the least-squares arithmetic. Then, the optimal method was applied to a touch-screen-LCD adjusting model for verifying its feasibility. Experiments show that the touch-screen-LCD calibration method using the optimal NN has higher precision comparing with the traditional touch-screen-LCD calibration method.

关键词： Neural networks Calibration optimization methods Neurons Neural network hardware Genetic algorithms Computer networks Embedded computing Information science Optical computing

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optimization of test engineering utilizing evolutionary computation

Optimization of test engineering utilizing evolutionary comp...

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International Automatic Testing conference, AUTOTESTCON

作者： Joseph Engler Rockwell Collins Inc. Cedar Rapids IA USA

Test engineering often experiences pressures to produce test stations and software in a short time frame with constrained budgets. Since test is a negative influence towards product costs, it is crucial to optimize the processes of test station software creation as well as the configuration of the test station itself. This paper introduces novel methodologies for optimized station configuration and automated station software generation. These two optimizations utilize evolutionary computation to automatically generate software for the test station and to offer optimal configurations of the station based upon testing requirements. Presented is a modified genetic programming algorithm for the creation of test station software (e.g. COTS software drivers). The genetic algorithm is improved through use of adaptive memory to recall historic schemas of high fitness. From the automated software generation an optimal station configuration is produced based upon the requirements of the testing to be performed. This system has been implemented in industry and an actual industrial case study is presented to illustrate the efficiency of this novel optimization technique. Comparisons with standard genetic programming techniques are offered to further illustrate the efficiency of this methodology.

关键词： Evolutionary computation software testing Automatic testing Genetic programming Time factors Cost function optimization methods software algorithms Genetic algorithms software performance

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Parameters optimization based on evolutionary algorithm for nonlinear hydraulic servo system

Parameters optimization based on evolutionary algorithm for ...

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IEEE International conference on Industrial Informatics (INDIN)

作者： Shaoping Wang Jun Du Zongxia Jiao Beihang University Beijing China Mechatronic Department Beihang University Beijing China

Directing to the nonlinear factors existed in hydraulic servo system, this paper focuses on fuzzy PID controller whose scaling factors and membership functions are optimized by evolutionary algorithm simultaneously to achieve high performance. With the improved genetic algorithm of sub population and dynamic time variant mutation, evolutionary algorithm can search the optimal state effectively. The scaling factors map the variable into universe of discourse while the tuning of scaling factors and fuzzy membership functions. Application of hydraulic servo system illustrates the effectiveness of the proposed technique.

关键词： Evolutionary computation Servomechanisms Fuzzy control Fuzzy systems Three-term control nonlinear control systems Control systems Genetic algorithms nonlinear dynamical systems Genetic mutations

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QoS-Aware GASA: A QoS-Aware Grid Resource Selection optimization Algorithm

QoS-Aware GASA: A QoS-Aware Grid Resource Selection Optimiza...

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International conference on Computational Intelligence and software Engineering (CiSE)

作者： Ning Qi Binqiang Wang Shuai Wei Nat. Digital Switching Syst. Eng. & Technol. Center Zhengzhou China Inf. Eng. Coll. Zhengzhou China

In order to provide high quality of service (QoS), reasonable scheduling and resource allocation are needed when a great deal of tasks request grid resources. By quantifying some important properties of Grid QoS and maximizing cost-performance of the system, a grid resource selection optimization algorithm is provided based on simulated annealing genetic algorithm (SAGA) : QoS-aware SAGA, and the flow of the algorithm is introduced. Finally, this algorithm is proved to be valid through a simulation experiment.

关键词： Quality of service Resource management Simulated annealing Genetic algorithms Scheduling algorithm Processor scheduling Dynamic scheduling Delay effects Costs Q measurement

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An Improved Cache-Based PTSVM Learning Algorithm

An Improved Cache-Based PTSVM Learning Algorithm

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International conference on Computational Intelligence and software Engineering (CiSE)

作者： Yong Piao Peng Wu Xiu-kun Wang Qiang Sun EI / Software School Dalian University of Technology Dalian China Software School Dalian University of Technology Dalian China EI School Dalian University of Technology Dalian China ChengGao Technologies Dalian China

Support vector machine is gaining popularity due to many attractive features and promising empirical performance in the fields of nonlinear and high dimensional pattern recognition. TSVM (transductive support vector machine) takes into account a particular test set and tries to minimize misclassifications of just those particular examples. PTSVM (progressive transductive support vector machine) can automatically adapt to different data distributions and realize a transductive learning of support vectors in a more general sense. However, the process of pairwise labeling of PTSVM in the margin band is unnatural and products errors more easily. Although dynamical adjusting offers some sort of error recovery function, its ability is limited. In allusion to the shortcomings of PTSVM learning algorithm, ICPTSVM (an improved cache-based PTSVM) learning algorithm is presented. The algorithm uses pairwise labeling in the range and error-correcting on cache to replace pairwise labeling in the margin band and dynamical adjusting. Then it greatly reduces the number of mis-labeling and improves the speed and accuracy. Experiments data show the validity of this algorithm.

关键词： Labeling Support vector machines Machine learning Pattern recognition Statistical learning software performance Testing software algorithms Sun Inference algorithms

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A Testbed Development Framework for Cognitive Radio Networks

A Testbed Development Framework for Cognitive Radio Networks

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IEEE International conference on Communications (ICC)

作者： J. Jia Q. Zhang Department of Computer Science and Engineering Hong Kong University of Science and Technology Hong Kong China

Cognitive radio networking is a promising approach to fulfill the future's need for intelligent, high-performance communication and improve the efficiency of overall spectrum utilization. Testbed evaluation of protocols and algorithms is a must for the development of cognitive radio networks. In this paper, we present an integrated testbed framework for cognitive radio networks. The framework includes necessary components for cognitive radio operations: flexible RF front end, software define signal processing, adaptive MAC layer and network layer as well as a cross layer management interface. Such a design eases the cross layer configuration and performance optimization of cognitive protocol stack, while retaining the advantage of modularity. We design a testbed for ad-hoc cognitive radio network.

关键词： Testing Cognitive radio Protocols Signal processing algorithms Cross layer design Intelligent networks Radio frequency Adaptive signal processing Radio spectrum management optimization

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Multi-objective optimization of Graph Partitioning Using Genetic algorithms

Multi-objective Optimization of Graph Partitioning Using Gen...

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International conference on Advanced Engineering Computing and Applications in Sciences (ADVCOMP)

作者： Mehdi Farshbaf Mohammad-Reza Feizi-Derakhshi Department of Computer University of Tabriz Tabriz Iran

Graph partitioning is a NP-hard problem with multiple conflicting objectives. The graph partitioning should minimize the inter-partition relationship while maximizing the intra-partition relationship. Furthermore, the partition load should be evenly distributed over the respective partitions. Therefore this is a multi-objective optimization problem. There are two approaches to multi-objective optimization using genetic algorithms: weighted cost functions and finding the Pareto front. We have used the Pareto front method to find the suitable curve of non-dominated solutions, composed of a high number of solutions. The proposed methods of this paper used to improve the performance are injecting best solutions of previous runs into the first generation of next runs and also storing the non-dominated set of previous generations to combine with later generation's non-dominated set. These improvements prevent the GA from getting stuck in the local optima and make the search more efficient and increase the probability of finding more optimal solutions. Finally, a simulation research is carried out to investigate the effectiveness of the proposed algorithm. The simulation results confirm the effectiveness of the proposed multi-objective GA method.

关键词： Genetic algorithms Pareto optimization Cost function Computational modeling optimization methods Genetic engineering Computer applications Application software NP-hard problem Partitioning algorithms

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Accurate Measurements and Precise Modeling of Power Dissipation of CUDA Kernels toward Power Optimized high performance CPU-GPU Computing

Accurate Measurements and Precise Modeling of Power Dissipat...

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IEEE International conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)

作者： Reiji Suda Da Qi Ren Graduate School of Information Science and Technology CREST University of Tokyo Japan Science and Technology SORST Tokyo Japan

Power dissipation is one of the most imminent limitation factors influencing the development of high performance Computing (HPC). Toward power-efficient HPC on CPU-GPU hybrid platform, we are investigating software methodologies to achieve optimized power utilization by algorithm design and programming technique. In this paper we discuss power measurements of GPU, propose a method of automatic extraction of power data of CUDA kernels from long measurement sequence, and execute an exactitude and effective power analysis on CUDA kernels. By using the proposed method above, we measured a sample kernel that performs single precision floating point additions on GeForce 8800 GTS. Our results suggest that the power consumption by a non-working thread in underoccupied half-warp is 71% of the power consumed by a working thread.

关键词： Power measurement Power dissipation Kernel high performance computing Yarn Design optimization software algorithms Algorithm design and analysis Data mining performance evaluation

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