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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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FooPar: A Functional Object Oriented parallel Framework in Scala 1

引用

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

作者： Hargreaves, Felix Palludan Merkle, Daniel Univ Southern Denmark Dept Math & Comp Sci Odense Denmark

ISBN: (数字)9783642551956

ISBN: (纸本)9783642551956

We present FooPar, an extension for highly efficient parallel Computing in the multi-paradigm programming language Scala. Scala offers concise and clean syntax and integrates functional programming features. Our framework FooPar combines these features with parallel computing techniques. FooPar is designed to be modular and supports easy access to different communication backends for distributed memory architectures as well as high performance math libraries. In this article we use it to parallelize matrix-matrix multiplication and show its scalability by a isoefficiency analysis. In addition, results based on a empirical analysis on two supercomputers are given. We achieve close-to-optimal performance wrt. theoretical peak performance. Based on this result we conclude that FooPar allows programmers to fully access Scalas design features without suffering from performance drops when compared to implementations purely based on C and MPI.

关键词： Functional programming Isoefficiency Matrix multiplication

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Runtime prediction on new architectures 14

Runtime prediction on new architectures

引用

10th Central and Eastern European Software Engineering conference in Russia, CEE-SECR 2014

作者： Sidnev, Aleksey A. Lobachevsky State University of Nizhni Novgorod Russia

ISBN: (纸本)9781450328890

this paper formulates the program runtime prediction problem subject to algorithm parameters and characteristics of a computational system to be used to run the algorithm. It is suggested to build a model representing runtime as a function of algorithm parameters and computational system characteristics. this is followed by determination of features to be used for functional dependence recovery. A two-step method of problem solution using linear and non-linear machine learning algorithms is proposed. the paper examines peculiarities of software algorithms and suggests a method for processing experimental data provided by computational systems. It also features a comparative analysis of runtime prediction results for solution of several linear algebra problems on 84 personal computers and servers using a number of machine learning algorithms. Use of a random forest combined with the linear least square method shows an error of less than 15% for most computational systems of similar architecture. Copyright 2014 ACM.

关键词： Regression analysis

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An Algorithm to Embed a Family of Node-Disjoint 3D Meshes into Locally Twisted Cubes 1

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

作者： You, Lantao Han, Yuejuan Soochow Univ Suzhou Ind Pk Inst Serv Outsourcing Suzhou 215000 Peoples R China Soochow Univ Ctr Informat Dev & Management Suzhou 215000 Peoples R China

ISBN: (数字)9783319111940

ISBN: (纸本)9783319111940;9783319111933

In this paper, embeddings of a family of 3D meshes in locally twisted cubes are studied. Let LTQ(n)(V, E) denotes the n-dimensional locally twisted cube. We find two major results in this paper:(1) For any integer n >= 4, two node-disjoint 3D meshes of size 2 x 2 x 2(n-3) can be embedded into LTQ(n) with dilation 1 and expansion 2. (2) For any integer n = 6, four node-disjoint 4x2x2(n-5) meshes can be embedded into LTQ(n) with dilation 1 and expansion 4. Further, an embedding algorithm can be constructed based on our embedding method. the obtained results are optimal in the sense that the dilations of the embeddings are 1.

关键词： Interconnection networks locally twisted cube 3D mesh embedding parallel computing

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Co-operation Schemes for the parallel Memetic Algorithm

Co-operation Schemes for the Parallel Memetic Algorithm

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

作者： Nalepa, Jakub Blocho, Miroslaw Czech, Zbigniew J. Silesian Tech Univ Gliwice Poland

ISBN: (纸本)9783642552243

this paper presents a study of co-operation schemes for the parallel memetic algorithm to solve the vehicle routing problem with time windows. In the parallel co-operative search algorithms the processes communicate to exchange the up-to-date solutions, which may guide the search and improve the results. the interactions between processes are defined by the content of the exchanged data, timing, connectivity and mode. We show how co-operation schemes influence the search convergence and solutions quality. the quality of a solution is defined as its proximity to the best, currently-known one. We present the experimental study for the well-known Gehring and Homberger's benchmark. the new world's best solutions obtained in the study confirm that the cooperation scheme has a strong impact on the quality of final solutions.

关键词： parallel memetic algorithm Co-operation scheme Hybrid genetic algorithm Vehicle routing problem with time windows

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Hmfs: Efficient Support of Small Files processing over HDFS 1

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

作者： Yan, Cairong Li, Tie Huang, Yongfeng Gan, Yanglan Donghua Univ Sch Comp Sci & Technol Shanghai 201620 Peoples R China

ISBN: (数字)9783319111940

ISBN: (纸本)9783319111940;9783319111933

the storage and access of massive small files are one of the challenges in the design of distributed file system. Hadoop distributed file system (HDFS) is primarily designed for reliable storage and fast access of very big files while it suffers a performance penalty with increasing number of small files. A middleware called Hmfs is proposed in this paper to improve the efficiency of storing and accessing small files on HDFS. It is made up of three layers, file operation interfaces to make it easier for software developers to submit different file requests, file management tasks to merge small files into big ones or extract small files from big ones in the background, and file buffers to improve the I/O performance. Hmfs boosts the file upload speed by using asynchronous write mechanism and the file download speed by adopting prefetching and caching strategy. the experimental results show that Hmfs can help to obtain high speed of storage and access for massive small files on HDFS.

关键词： HDFS small files middleware asynchronous write prefetching

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A Platform for Stock Market Simulation with Distributed Agent-Based Modeling 1

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

作者： Wang, Chunyu Yu, Ce Wu, Hutong Chen, Xiang Li, Yuelei Zhang, Xiaotao Tianjin Univ Sch Comp Sci & Technol Tianjin 300072 Peoples R China Tianjin Univ Sch Econ & Management Tianjin Peoples R China

ISBN: (数字)9783319111940

ISBN: (纸本)9783319111940;9783319111933

Agent-based modeling (ABM) has been widely used in stock market simulation. However, traditional simulations of stock markets with ABM on single computers are limited by the computing capability as breakthroughs in financial research need much larger amount of agents. this paper introduces a platform for stock market simulation with ABM focusing on large scale parallel agents in a distributed computing environment such as Cluster and MPP. With the customized trade strategies inside the agents, the runtime system of the platform can distribute the massive amount of agents to multiple computing nodes automatically during the execution of the simulation. And agents exchange information with each other and the market through a uniform communication system. With this platform financial researchers can design their own financial model without caring about the complexity of parallelization and related problems. the sample simulation on the platform is verified to be compatible with the data from Euronext-NYSE and the platform shows fair scalability and performance under different parallelism configurations.

关键词： stock market simulation agent-based modeling parallel distributed environment

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Optimization of an OpenCL-Based Multi-swarm PSO Algorithm on an APU 1

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

作者： Franz, Wayne thulasiraman, Parimala thulasiram, Ruppa K. Univ Manitoba Winnipeg MB Canada

ISBN: (数字)9783642551956

ISBN: (纸本)9783642551956

the multi-swarm particle swarm optimization (MPSO) algorithm incorporates multiple independent PSO swarms that cooperate by periodically exchanging information. In spite of its embarrassingly parallel nature, MPSO is memory bound, limiting its performance on data-parallel GPUs. Recently, heterogeneous multi-core architectures such as the AMD Accelerated processing Unit (APU) have fused the CPU and GPU together on a single die, eliminating the traditional PCIe bottleneck between them. In this paper, we provide our experiences developing an OpenCL-based MPSO algorithm for the task scheduling problem on the APU architecture. We use the AMD A8-3530MX APU that packs four x86 computing cores and 80 four-way processing elements. We make effective use of hardware features such as the hierarchical memory structure on the APU, the four-way very long instruction word (VLIW) feature for vectorization, and global-to-local memory DMA transfers. We observe a 29% decrease in overall execution time over our baseline implementation.

关键词： PSO parallel evolutionary computing APU OpenCL

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Applying OpenMP-based parallel Implementations of NSGA-II and SPEA2 to Study Phylogenetic Relationships 16

Applying OpenMP-based Parallel Implementations of NSGA-II an...

引用

16th IEEE international conference on Cluster Computing (CLUSTER)

作者： Santander-Jimenez, Sergio Vega-Rodriguez, Miguel A. Univ Extremadura Dept Technol Comp & Commun Caceres Spain

ISBN: (纸本)9781479955480

throughout the years, biological processing demands have been addressed by relying on the design of algorithmic approaches for parallel architectures. By taking advantage of multicore processor systems, we can deal with the main sources of complexity which explain the NP-hard nature of multiple problems in computational biology. In this work, we address the inference of phylogenetic topologies by using two multiobjective metaheuristics: Fast Non-Dominated Sorting Genetic Algorithm and Strength Pareto Evolutionary Algorithm 2. the additional complexity introduced by the multiobjective formulation of the problem motivates that parallel designs of these algorithms must be undertaken. For this purpose, OpenMP-based implementations of these two metaheuristics are applied. To evaluate the performance of these approaches, a comparative study has been conducted by performing experimentation on four nucleotide data sets. Our experiments suggest the relevance of these parallel algorithmic designs, improving the phylogenetic results reported by other multiobjective tools in reduced execution times.

关键词： Multiobjective optimization evolutionary computation parallel computing phylogeny reconstruction

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parallelized Race Detection Based on GPU Architecture

Parallelized Race Detection Based on GPU Architecture

引用

10th Annual conference of Advanced Computer Architecture, ACA 2014

作者： Dai, Zhuofang Zhang, Zheng Wang, Haojun Li, Yi Zhang, Weihua Software School Fudan University Shanghai China Shanghai Key Laboratory of Data Science Fudan University Shanghai China Parallel Processing Institute Fudan University Shanghai 201203 China State Key Laboratory of Mathematic Engineering and Advanced Computing Zhengzhou 450001 China

ISBN: (纸本)9783662444900

In order to harness abundant hardware resources, parallel programming has become a necessity in multicore era. However, parallel programs are prone to concurrency bugs, especially data races. Even worse, current software tools always suffer from both large runtime overheads and poor scalability, while most of hardware supports for race detection are not available in parallel programming. therefore, it has been a challenge that how to introduce a practical and fast race detection tools. Nowadays, GPUs with massive parallel computation resources have become one of the most popular hardware platforms. Hence, the prevalence of GPU architectures has opened an opportunity of accelerating data race detection. In this paper, we first have a deeply analysis on data race detection algorithms like happens-before and observe that these algorithms have very good computation and data parallelism. Based on the observation, we propose Grace, a software approach that leverages massive parallelism computation units of GPU architectures to accelerate data race detection. Grace deploys detection, the most computation intensive workload, on GPU to fully utilize the computation resource in GPU. Moreover, Grace leverages coarse-grained pipeline parallelism and data parallelism through exploiting the computation resource in multi-core CPUs to further improve performance. Experimental results show that Grace is fast and scalable. It achieves over 80x speedup compared to the sequential version even under a 128-thread configuration. © Springer-Verlag Berlin Heidelberg 2014.

关键词： Graphics processing unit

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Data-driven techniques to overcome workload disparity 4

Data-driven techniques to overcome workload disparity

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4th Workshop on Irregular Applications: architectures and algorithms, IA3 2014

作者： Connors, Dan Saleh, Skyler Joshi, Tejas Bueter, Ryan Department of Electrical Engineering University of Colorado Denver DenverCO80217-3364 United States

ISBN: (纸本)9781479970568

General-purpose computing on graphics processing unit (GPGPU) architectures rely on data locality and regular computation to leverage parallel resources to achieve performance benefits over multi-core systems. Current GPUs often cannot effectively accommodate irregular algorithms and non-uniform memory accesses. Irregular execution corrupts the efficiency of the rigid GPU groups of threads that lead to idle execution execution and workload disparity in the GPU architecture. While hardware aspects of branch divergence, local memory bank conflicts, and non-coalesced memory accesses cause workload disparity, the greater issue is the lost of execution potential from other GPU workgroups. this paper sets out to characterize the workload disparity and toexplore data-driven models for executing irregular computations on GPU architectures. © 2014 IEEE.

关键词： Graphics processing unit

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