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Japan-China Joint workshop on Frontier of Computer Science and Technology (FCST)

作者： Gu Liu Hong An Wenting Han Guang Xu Ping Yao Mu Xu Xiurui Hao Yaobin Wang Department 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

Recently many studies have been made to map cryptography algorithms onto graphics processors (GPU), and gained great performances. This paper does not focus on the performance of a specific program exploited by using all kinds of optimization methods algorithmically, but the intrinsic reason which lies in GPU architectural features for this performance improvement. Thus we present a study of several block encryption algorithms(AES, TRI-DES, RC5, TWOFISH and the chained block cipher formed by their combinations) processing on GPU using CUDA. We introduce our CUDA implementations, and investigate the program behavioral characteristics and their impacts on the performance in four aspects. We find that the number of threads used by a CUDA program can affect the overall performance fundamentally. Many block encryption algorithms can benefit from the shared memory if the capacity is large enough to hold the lookup tables. The data stored in device memory should be organized purposely to avoid performance degradation. Besides, the communication between host and device may turn out to be the bottleneck of a program. Through these analyses we hope to find out an effective way to optimize a CUDA program, as well as to reveal some desirable architectural features to support block encryption applications better.

关键词： Cryptography Computer architecture Acceleration Runtime Computer science Parallel processing Hardware Laboratories Computer graphics optimization methods

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A Systemic Strategy for Tuning Intra-node Collective Communication on Multicore Systems

A Systemic Strategy for Tuning Intra-node Collective Communi...

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Japan-China Joint workshop on Frontier of Computer Science and Technology (FCST)

作者： Zhiqiang Liu Junqiang Song Kaijun Ren Fen Xu Xiaoling Qu College of Computer National University of Defense Technology Changsha Hunan China China Aerodynamics Research and Development Center Mianyang Sichuan China

In HPC domain, a majority of applications build on MPI and employ collective operations in their communication kernels. Improving the performance of collectives has been long term focused by a lot of work. Recently, in the optimization work of collectives on multi-core clusters, hierarchical algorithm designs are remark-able. This kind of algorithms can greatly reduce the inter-node traffic but increase the intra-node traffic load at the same time. Meanwhile, in hierarchical collectives, the part of intra-node collectives take more and more time while the number of cores in each node keeps growing. Improving the performance of intra-node collectives is critical to the holistic performance. However, on multi-cores, the factor of process affinity greatly impacts the performance of an intra-node collective. This peculiarity challenges us how to improve the overall performance of intra-node collectives. Towards this problem, in this paper, we propose a novel and systemic strategy for tuning the performance of intra-node collectives. As illustrative examples, we have implemented our strategy on a dual-socket Intel Clovertown platform and successfully tuned the performance of Broadcast and Allgather up to 14% and 52% improvement together.

关键词： Multicore processing Broadcasting Algorithm design and analysis Telecommunication traffic Kernel Clustering algorithms Computer science Educational institutions Application software Design optimization

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Workload characterization and optimization of high-performance text indexing on the Cell Broadband Engine™ (Cell/B.E.)

Workload characterization and optimization of high-performan...

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IEEE international workshop/Symposium on Workload Characterization

作者： Daniele Paolo Scarpazza Gordon W. Braudaway Multicore Computing Department IBM Thomas J. Watson Research Center Yorktown Heights NY USA

In this paper we examine text indexing on the Cell Broadband Enginetrade (Cell/B.E.), an emerging workload on an emerging multicore architecture. The Cell Broadband Engine is a microprocessor jointly developed by Sony Computer Entertainment, Toshiba, and IBM (herein, we refer to it simply as the "Cell"). The importance of text indexing is growing not only because it is the core task of commercial and enterprise-level search engines, but also because it appears more and more frequently in desktop and mobile applications, and on network appliances. Text indexing is a computationally intensive task. Multi-core processors promise a multiplicative increase in compute power, but this power is fully available only if workloads exhibit the right amount and kind of parallelism. We present the challenges and the results of mapping text indexing tasks to the Cell processor. The Cell has become known as a platform capable of impressive performance, but only when algorithms have been parallelized with attention paid to its hardware peculiarities (expensive branching, wide SIMD units, small local memories). We propose a parallel software design that provides essential text indexing features at a high throughput (161 Mbyte/s per chip on Wikipedia inputs) and we present a performance analysis that details the resources absorbed by each subtask. Not only does this result affect traditional applications, but it also enables new ones such as live network traffic indexing for security forensics, until now believed to be too computationally demanding to be performed in real time. We conclude that, at the cost of a radical algorithmic redesign, our Cell-based solution delivers a 4x performance advantage over recent commodity machine like the Intel Q6600. In a per-chip comparison, ours is the fastest text indexer that we are aware of.

关键词： Indexing Multicore processing Application software Computer architecture Microprocessors Search engines Home appliances Concurrent computing Parallel processing Hardware

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Performance comparison of evolutionary algorithms in the task of optimization of chaos control

Performance comparison of evolutionary algorithms in the tas...

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19th international Conference on Database and Expert Systems applications

作者： Zelinka, Ivan Senkerik, Roman Oplatkova, Zuzana Tomas Bata Univ Zlin Fac Appl Informat Zlin 76272 Czech Republic

ISBN: (纸本)9780769532998

This work deals with optimization of the control of chaos by means of the evolutionary algorithms. The main aim of this work is to show that evolutionary algorithms are capable of optimization of chaos control leading to satisfactory results and mainly to compare their performance in this task. As a model of deterministic chaotic system, the one dimensional Logistic equation was used. The evolutionary algorithms, SOMA (Self-Organizing Migrating Algorithm) and DE (Differential Evolution) were used in several versions. For each version, simulations were repeated 50 times to show and check robustness of the used method and constructed cost function. Within this work the results of optimized chaos control for both evolutionary algorithms are compared in statistical overview.

关键词： Evolutionary algorithms

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Particle Swarm optimization using adaptive mutation

Particle Swarm Optimization using adaptive mutation

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19th international Conference on Database and Expert Systems applications

作者： Pant, Millie Thangaraj, Radha Abraham, Ajith Indian Inst Technol Roorkee Dept Paper Technol Roorkee Uttar Pradesh India Norwegian Univ Sci & Technol Ctr Excellence Quantifiable Qual Serv Trondheim Norway

ISBN: (纸本)9780769532998

Two new variants of Particle Swarm optimization (PSO) called AAPSO1 and AAPSO2 are proposed for global optimization problems. Both the algorithms use adaptive mutation using Beta distribution. AMPSO1 mutates the personal best position of the swarm and AMPSO2, mutates the global best swarm position. The performance of proposed algorithms is evaluated on twelve unconstrained test problems and three real life constrained problems taken from the field of Electrical Engineering. The numerical results show the competence of the proposed algorithms with respect some other contemporary techniques.

关键词： Particle swarm optimization (PSO)

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Evolutionary algorithms in aircraft trim optimization

Evolutionary algorithms in aircraft trim optimization

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19th international Conference on Database and Expert Systems applications

作者： Tupy, Jaroslav Zelinka, Ivan Tomas Bata Univ Zlin Dept Appl Informat Zlin 76005 Czech Republic

ISBN: (纸本)9780769532998

In this paper, the calculation of aircraft trimming process is presented in a sufficiently understandable way using a unique combination of global optimization theory and the direct hand-on computer simulation. The methods of artificial intelligence and heuristic algorithms handling with the equations of airplane motion are presented in this paper. The main aim was to use them for trimming the flying aircraft to the steady state flight upon setting the flight conditions of various kinds. New approach of SOMA (Self Organizing Migrating Algorithm) has been used here to find the vehicle equilibrium state. The method can be practically utilized in construction of airplanes as well as the flight simulators design.

关键词： Heuristic methods

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A distributed multilevel ant colonies approach for graph partitioning

A distributed multilevel ant colonies approach for graph par...

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3rd international Conference on Bioinspired optimization Methods and their applications, BIOMA 2008

作者： Taškova, Katerina Korošec, Peter Šilc, Jurij Computer Systems Department Jožef Stefan Institute Ljubljana Slovenia

ISBN: (纸本)9789612640026

The paper presents a distributed implementations of an ant colony optimization metaheuristic for the solution of a mesh partitioning problem. The usefulness and efficiency of the algorithm, in its sequential form, to solve that particular optimization problem has already been shown in previous work. In this paper a straightforward implementations on a distributed architecture is presented and the main algorithmic issues that had to be addressed are discussed. algorithms are evaluated on a set of well known graph-partitioning problems from the Graph Collection Web page.

关键词： Ant colony optimization

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Evolutionary scanning and neural network optimization

Evolutionary scanning and neural network optimization

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19th international Conference on Database and Expert Systems applications

作者： Zelinka, Ivan Senkerik, Roman Oplatkova, Zuzana Tomas Bata Univ Zlin Fac Appl Informat Zlin 76001 Czech Republic

ISBN: (纸本)9780769532998

This paper deals with use of an alternative tool for symbolic regression - analytic programming which is able to solve various problems from the symbolic domain as well as genetic programming and gramatical evolution. The main tasks of analytic programming in this paper, is synthesis of a neural network. In this contribution main principles of analytic programming are described and explained. In the second part of the article is in detail described how analytic programming was used for neural nework synthesis. An ability to create so called programms, as well as genetic programming or grammatical evolution do, is shown in that part. In this contribution three evolutionary algorithms were used - Self Organizing Migrating Algorithm, Differential Evolution and Simulated Annealing. The total number of simulations was 150 and results show that the first two used algorithms were more successful than not so robust Simulated Annealing.

关键词： Artificial neural networks Encoding Evolutionary computation Evolution (biology) Genetics Biological neural networks Computer architecture

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Adaptive optimization of join trees for multi-join queries over sensor streams

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INFORMATION FUSION 2008年第3期9卷 412-424页

作者： Gomes, Joseph Choi, Hyeong-Ah George Washington Univ Dept Comp Sci Washington DC 20052 USA

Data processing applications for sensor streams have to deal with multiple continuous data streams with inputs arriving at highly variable and unpredictable rates from various sources. These applications perform various operations (e.g. filter, aggregate, join, etc.) on incoming data streams in real-time according to predefined queries or rules. Since the data rate and data distribution fluctuate over time, an appropriate join tree for processing join queries must be adaptively maintained in response to dynamic changes to prevent rapid degradation of the system performance. In this paper, we address the problem of finding an optimal join tree that maximizes throughput for sliding window based multi-join queries over continuous data streams and prove its NP-Hardness. We present a dynamic programming algorithm, OptDP, which produces the optimal tree but runs in an exponential time in the number of input streams. We then present a polynomial time greedy algorithm, XGreedyJoin. We tested these algorithms in ARES, an adaptively re-optimizing engine for stream queries, which we developed by extending Jess (Jess is a popular RETE-based, forward chaining rule engine written in java). For almost all instances, trees from XGreedyJoin perform close to the optimal trees from OptDP, and significantly better than common heuristics-based XJoin algorithms. (C) 2007 Elsevier B.V. All rights reserved.

关键词： stream query join query sensor stream sliding windows adaptive optimization dynamic programming

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Bioinspired optimization Methods and their applications - Proceedings of the 3rd international Conference on Bioinspired optimization Methods and their applications, BIOMA 2008

Bioinspired Optimization Methods and their Applications - Pr...

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3rd international Conference on Bioinspired optimization Methods and their applications, BIOMA 2008

ISBN: (纸本)9789612640026

The proceedings contain 14 papers. The topics discussed include: Nash equilibria, collusion in games and the coevolutionary particle swarm algorithm;hybrid optimization based on fast evolution strategies and particle swarm optimization;a distributed multilevel ant colonies approach;statistical multi-comparison of evolutionary algorithms;testing approaches for global optimization of space trajectories;a discrete particle swarm optimizer for clustering short-text corpora;solving engineering optimization problems with the simple constrained particle swarm optimizer;analysis of an immune algorithm for protein structure prediction;evolutionary jazz harmony: a new jazz harmony system;constrained transportation scheduling;and the application of smart control technique in scheduling of electrical power generation.

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