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检索条件"任意字段=10th International Conference Algorithms and Architectures for Parallel Processing, ICA3PP 2010"

共 21 条记录，以下是1-10 订阅

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algorithms and architectures for parallel processing - 10th international conference, ica3pp 2010, Workshops

Algorithms and Architectures for Parallel Processing - 10th ...

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10th international conference algorithms and architectures for parallel processing, ica3pp 2010

ISBN: (纸本)3642131352

the proceedings contain 95 papers. the topics discussed include: scalable co-clustering algorithms;parallel prefix computation in the recursive dual-net;a two-phase differential synchronization algorithm for remote files;query optimization over parallel relational data warehouses in distributed environments by simultaneous fragmentation and allocation;a high efficient on-chip interconnection network in SIMD CMPs;design of a slot assignment scheme for link error distribution on wireless grid networks;dynamic resource tuning for flexible core chip multiprocessors;a grid based system for closure computation and online service;parallel domain decomposition methods for high-order finite element solutions of the Helmholtz problem;frequencies;quick forwarding of queries to relevant peers in a hierarchical P2P file search system;cluster-fault-tolerant routing in burnt pancake graphs;and edge-bipancyclicity of all conditionally faulty hypercubes.

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algorithms and architectures for parallel processing - 10th international conference, ica3pp 2010, Proceedings

Algorithms and Architectures for Parallel Processing - 10th ...

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10th international conference algorithms and architectures for parallel processing, ica3pp 2010

ISBN: (纸本)3642131182

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algorithms and architectures for parallel processing 1

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丛书名： Lecture Notes in Computer Science

1000年

作者： Ching-Hsien Hsu Laurence T. Yang Jong Hyuk Park Sang-Soo Yeo

ISBN: (数字)9783642131196

ISBN: (纸本)9783642131189

It is our great pleasure to welcome you to the proceedings of the 10th annual event of the international conference on algorithms and architectures for parallel processing (ica3pp). ica3pp is recognized as the main regular event covering the many dimensions of parallel algorithms and architectures, encompassing fundamental theoretical - proaches, practical experimental projects, and commercial components and systems. As applications of computing systems have permeated every aspect of daily life, the power of computing systems has become increasingly critical. therefore, ica3pp 2010 aimed to permit researchers and practitioners from industry to exchange inf- mation regarding advancements in the state of the art and practice of IT-driven s- vices and applications, as well as to identify emerging research topics and define the future directions of parallel processing. We received a total of 157 submissions this year, showing by both quantity and quality that ica3pp is a premier conference on parallel processing. In the first stage, all papers submitted were screened for their relevance and general submission - quirements. these manuscripts then underwent a rigorous peer-review process with at least three reviewers per paper. In the end, 47 papers were accepted for presentation and included in the main proceedings, comprising a 30% acceptance rate.

关键词： Algorithm Analysis and Problem Complexity Computer System Implementation Programming Techniques Artificial Intelligence Software Engineering Information Storage and Retrieval

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GPU-Accelerated Verification of the Collatz Conjecture

GPU-Accelerated Verification of the Collatz Conjecture

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14th international conference on algorithms and architectures for parallel processing (ica3pp)

作者： Honda, Takumi Ito, Yasuaki Nakano, Koji Hiroshima Univ Dept Informat Engn Higashihiroshima 7398527 Japan

ISBN: (纸本)9783319111971;9783319111964

the main contribution of this paper is to present an implementation that performs the exhaustive search to verify the Collatz conjecture using a GPU. Consider the following operation on an arbitrary positive number: if the number is even, divide it by two, and if the number is odd, triple it and add one. the Collatz conjecture asserts that, starting from any positive number m, repeated iteration of the operations eventually produces the value 1. We have implemented it on NVIDIA GeForce GTX TITAN and evaluated the performance. the experimental results show that, our GPU implementation can verify 5.01x10(11) 64-bit numbers per second, while the CPU implementation on Intel Xeon X7460 can verify 1.80 x 10(9) 64-bit numbers per second. thus, our implementation on the GPU attains a speed-up factor of 278 over the single CPU implementation.

关键词： Collatz conjecture GPGPU parallel processing Exhaustive verification

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An Efficient Pre-filter to Accelerate Regular Expression Matching 15th

An Efficient Pre-filter to Accelerate Regular Expression Mat...

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15th international conference on algorithms and architectures for parallel processing (ica3pp)

作者： Xu, Chengcheng Chen, Shuhui Wang, Xiaofeng Su, Jinshu Natl Univ Def Technol Coll Comp Changsha 410073 Hunan Peoples R China Natl Univ Def Technol Natl Key Lab Parallel & Distributed Proc Changsha 410073 Hunan Peoples R China

ISBN: (纸本)9783319271613;9783319271606

Regular expression matching is widely used in content-aware applications, such as NIDS and protocol identification. However, wire-speed processing for large scale patterns still remains a great challenge in practice. Considering low hit rates in NIDS, a compact and efficient pre-filter is firstly proposed to filter most normal traffics and leave few suspicious traffics for further pattern matching. Experiment results show that, the pre-filter achieves a big improvement in both space and time consumption with its compact and efficient structure.

关键词： Regular expression matching Pattern matching Deep packet inspection DPI Pre-filter

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A parallel Approach to Advantage Actor Critic in Deep Reinforcement Learning 19th

A Parallel Approach to Advantage Actor Critic in Deep Reinfo...

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19th international conference on algorithms and architectures for parallel processing (ica3pp)

作者： Zhu, Xing Du, Yunfei Sun Yat Sen Univ Sch Data & Comp Sci Guangzhou Peoples R China

ISBN: (纸本)9783030389611;9783030389604

Deep Reinforcement learning (DRL) algorithms recently still take a long time to train models in many applications. parallelization has the potential to improve the efficiency of DRL algorithms. In this paper, we propose an parallel approach (ParaA2C) for the popular Actor-Critic (AC) algorithms in DRL, to accelerate the training process. Our work considers the parallelization of the basic advantage actor critic (Serial-A2C) in AC algorithms. Specifically, we use multiple actor-learners to mitigate the strong correlation of data and the instability of updating, and finally reduce the training time. Note that we assign each actor-learner MPI process to a CPU core, in order to prevent resource contention between MPI processes, and make our ParaA2C approach more scalable. We demonstrate the effectiveness of ParaA2C by performing on Arcade Learning Environment (ALE) platform. Notably, our ParaA2C approach takes less than 10 min to train in some commonly used Atari games when using 512 CPU cores.

关键词： Deep reinforcement learning Advantage actor critic parallelization MPI Scalable

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Configuring Concurrent Computation of Phylogenetic Partial Likelihoods: Accelerating Analyses Using the BEAGLE Library 17th

Configuring Concurrent Computation of Phylogenetic Partial L...

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17th international conference on algorithms and architectures for parallel processing (ica3pp)

作者： Ayres, Daniel L. Cummings, Michael P. Univ Maryland Ctr Bioinformat & Computat Biol College Pk MD 20742 USA

ISBN: (纸本)9783319654829;9783319654812

We describe our approach in augmenting the BEAGLE library for high-performance statistical phylogenetic inference to support concurrent computation of independent partial likelihoods arrays. Our solution involves identifying independent likelihood estimates in analyses of partitioned datasets and in proposed tree topologies, and configuring concurrent computation of these likelihoods via CUDA and opencL frameworks. We evaluate the effect of each increase in concurrency on throughput performance for our partial likelihoods kernel for a four-state nucleotide substitution model on a variety of parallel computing hardware, such as NVIDIA and AMD GPU5, and Intel multicore cPus, observing up to 16-fold speedups over our previous implementation. Finally, we evaluate the effect of these gains on an domain application program, MrBayes. For a partitioned nucleotide-model analysis we observe an average speedup for the overall run time of 2.1-fold over our previous parallel implementation, and 10-fold over the native MrBayes with SSE.

关键词： Bayes methods Biology computing Evolution (biology) Phylogeny Maximum likelihood estimation Multicore processing parallel programming High performance computing

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A proposed asynchronous object load balancing method for parallel 3D image reconstruction applications

A proposed asynchronous object load balancing method for par...

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10th international conference algorithms and architectures for parallel processing, ica3pp 2010

作者： Alvarez-Bermejo, Jose Antonio Roca-Piera, Javier Dept of Computer Architecture and Electronics Universidad de Almería Ctra. Sacramento S/N. 04120 Spain

ISBN: (纸本)3642131182

Scientific applications usually exhibit irregular patterns of execution and high resource usage. parallel architectures are a feasible solution to face these drawbacks, but porting software to parallel platforms means the addition of an extra layer of complexity to scientific software. Abstractions such as Object Orientation and models like the concurrent object model may be of great help to develop scientific parallel applications. the shared nature of parallel architectures and the stochastic condition of parallel schedulers underline the adaptivity as a desired feature for parallel applications. Load Balancers are key for achieving adaptivity, and benefit from object oriented models in issues like load migration. In this paper we present our experiences when porting scientific software using the concurrent object abstraction and a method to asynchronously invoke load balancers. © Springer-Verlag Berlin Heidelberg 2010.

关键词： parallel architectures

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algorithms and architectures for parallel processing 1

引用

丛书名： Lecture Notes in Computer Science

1000年

作者： Yang Xiang Wanlei Zhou Alfredo Cuzzocrea Michael Hobbs

ISBN: (数字)9783642246692

ISBN: (纸本)9783642246685

this two volume set LNCS 7016 and LNCS 7017 constitutes the refereed proceedings of the 11th international conference on algorithms and architectures for parallel processing, ica3pp 2011, held in Melbourne, Australia, in October 2011. the second volume includes 37 papers from one symposium and three workshops held together with ica3pp 2011 main conference. these are 16 papers from the 2011 international Symposium on Advances of Distributed Computing and Networking (ADCN 2011), 10 papers of the 4th IEEE international Workshop on Internet and Distributed Computing Systems (IDCS 2011), 7 papers belonging to the III international Workshop on Multicore and Multithreaded architectures and algorithms (M2A2 2011), as well as 4 papers of the 1st IEEE international Workshop on parallel architectures for Bioinformatics Systems (HardBio 2011).

关键词： Algorithm Analysis and Problem Complexity Artificial Intelligence Software Engineering Information Systems Applications (incl. Internet) Computer Communication Networks Management of Computing and Information Systems

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A Distributed Framework for Online Stream Data Clustering 20th

A Distributed Framework for Online Stream Data Clustering

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20th international conference on algorithms and architectures for parallel processing (ica3pp)

作者： Ding, Jiafeng Fang, Junhua Chao, Pingfu Xu, Jiajie Zhao, PengPeng Zhao, Lei Soochow Univ Dept Comp Sci & Technol Suzhou Peoples R China Univ Queensland Brisbane Qld Australia

ISBN: (纸本)9783030602451;9783030602444

the recent prevalence of positioning sensors and mobile devices generates a massive amount of spatial-temporal data from moving objects in real-time. As one of the fundamental processes in data analysis, the clustering on spatial-temporal data creates various applications, like event detection and travel pattern extraction. However, most of the existing works only focus on the offline scenario, which is not applicable to online time-sensitive applications due to their low efficiency and ignorance of temporal features. In this paper, we propose a distributed streaming framework for spatial-temporal data clustering, which accepts various clustering algorithms while ensuring low resource consumption and result correctness. the framework includes a dynamic partitioning strategy for continuous load-balancing and a cluster-merging algorithm based on convex hulls [10], which guarantees the result correctness. Extensive experiments on real dataset prove the effectiveness of our proposed framework and its advantage over existing solutions.

关键词： Real-time cluster analysis Distributed stream processing Spatial-temporal data mining Top-k query parallel computing

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