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共 292 条记录，以下是141-150 订阅

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Dynamic Data Race Detection for Correlated Variables

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11th international conference on algorithms and architectures for parallel processing (ica3pp)

作者： Jannesari, Ali Westphal-Furuya, Markus Tichy, Walter F. Karlsruhe Inst Technol Inst Program Struct & Data Org D-76131 Karlsruhe Germany

ISBN: (纸本)9783642246494

In parallel programs concurrency bugs are often caused by unsynchronized accesses to shared memory locations, which are called data races. In order to support programmers in writing correct parallel programs, it is therefore highly desired to have tools on hand that automatically detect such data races. Today, most of these tools only consider unsynchronized read and write operations on a single memory location. Concurrency bugs that involve multiple accesses on a set of correlated variables may be completely missed. Tools may overwhelm programmers with data races on various memory locations, without noticing that the locations are correlated. In this paper, we propose a novel approach to data race detection that automatically infers sets of correlated variables and logical operations by analyzing data and control dependencies. For data race detection itself, we combine a modified version of the lockset algorithm with happens-before analysis providing the first hybrid, dynamic race detector for correlated variables. We implemented our approach on top of the Valgrind, a framework for dynamic binary instrumentation. Our evaluation confirmed that we can catch data races missed by existing detectors and provide additional information for correct bug fixing.

关键词： data race detection parallel programs dynamic analysis correlated variables

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ParaMoC: A parallel Model Checker for Pushdown Systems 19th

ParaMoC: A Parallel Model Checker for Pushdown Systems

引用

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

作者： Wei, Hansheng Ye, Xin Shi, Jianqi Huang, Yanhong East China Normal Univ Natl Trusted Embedded Software Engn Technol Res C Shanghai Peoples R China Res Ctr Hardware Software Codesign Technol & Applicat Eng Shanghai Peoples R China Shanghai Key Lab Trustworthy Comp Shanghai Peoples R China LIPN Paris France Paris Univ 7 Paris France

ISBN: (纸本)9783030389611;9783030389604

Model checking on Pushdown Systems (PDSs) has been extensively used to deal with numerous practical problems. However, the existing model checkers for pushdown systems are executed on the central processing unit (CPU), the performance is hampered by the computing power of the CPU. Compared with the CPU, the graphics processing unit (GPU) has more processing cores, which are suitable and efficient for parallel computing. therefore, it is very attractive to accelerate model checking of PDSs on the GPU. In this paper, we present a new parallel model checker, named ParaMoC, to speed up the performance of model checking problems for pushdown systems (PDSs). Moreover, we focus on how to use Graphics processing Units (GPUs) to accelerate the reachability verification and the LTL model checking of PDSs. the ParaMoC running on a state-of-the-art GPU can be 100 times faster than the traditional PDS model checker.

关键词： Graphics processing unit

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An Advanced Data Redistribution Approach to Accelerate the Scale-Down Process of RAID-6

An Advanced Data Redistribution Approach to Accelerate the S...

引用

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

作者： Du, Congjin Wu, Chentao Li, Jie Shanghai Jiao Tong Univ Dept Comp Sci & Engn Shanghai Key Lab Scalable Comp & Syst Shanghai 200240 Peoples R China

ISBN: (纸本)9783319111940;9783319111933

Nowadays RAID is widely used with the increasing requirements of the reliability in storage systems and the fast development of cloud computing. Among various levels and implementations of RAID systems, RAID-6 is one of the most significant category with the ability to tolerate concurrent failures of any two disks. However, the scalability of RAID-6 is a big challenge. Although many approaches are proposed to accelerate the scaling process and reduce the overhead, how to efficiently remove disks (refers to scale-down process) from existing array is still an open problem. To address the scalability problem, we propose an Advanced Data Redistribution (ADR) approach. the basic idea of ADR is to reorganize previous stripes in RAID-6 systems to achieve higher scalability. ADR is a stripe-level scheme and can be combined with other approaches as SDM and MDS-Frame. It can minimize the overhead of data migration and parity modification. We have conducted mathematical analysis by comparing ADR to various popular RAID-6 codes. the results show that, compared to typical approach (Round-Robin), ADR decreases more than 52.1% migration I/O operations, saves the migration time by up to 63.5%, and speeds up of the scaling process by up to 1.91.

关键词： RAID-6 MDS Code Performance Evaluation Scalability Scale-Down Reliability

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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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Asynchronous parallel Dijkstra's Algorithm on Intel Xeon Phi Processor How to Accelerate Irregular Memory Access Algorithm 18th

Asynchronous Parallel Dijkstra's Algorithm on Intel Xeon Phi...

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18th international conference on algorithms and architectures for parallel processing (ica3pp)

作者： Zhang, Weidong Zhang, Lei Chen, Yifeng Peking Univ EECS Beijing 100871 Peoples R China HuaWei Inc Shenzhen Peoples R China

ISBN: (纸本)9783030050511;9783030050504

As the instruction-level parallelism (ILP) on CPU develops to a rather advanced level, the exploration that whether many-core architecture is applicable for graph algorithms is generating more interests in researchers. However, due to the irregular memory access and the low ratio of computation to memory access, the performance of graph algorithms on many-core architectures has never worked good enough. To obtain outstanding speedup on many-core architecture, first of all, we need to figure out three questions: (i) how to optimize the memory access, (ii) how to minimize the overhead of synchronization, (iii) how to exploit the parallelism in algorithm. Prior works hardly reach the goal if such questions are treated in separated way. throughout this paper, we aim to settle these questions systematically, and try to provide a set of methods of optimizing graph algorithms on many-core architecture. this paper mainly discusses how to accelerate the Single Source Shortest Path (SSSP) problem on Intel Many Integrated Core (MIC) architecture, on which we propose an asynchronous parallel Dijkstra's algorithm. It aims at maximizing parallelism and minimizing overhead of synchronization. Experimental result shows that the MIC architecture could efficiently solve the SSSP problem, and its performance could be sped up by 9.2x compared to the benchmark of DIMACS.

关键词： Single source shortest path parallel algorithm Intel MIC Road network

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Generic parallel Genetic Algorithm Framework for Protein Optimisation

Generic Parallel Genetic Algorithm Framework for Protein Opt...

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11th international conference on algorithms and architectures for parallel processing (ica3pp)

作者： Folkman, Lukas Pullan, Wayne Stantic, Bela Griffith Univ Inst Integrated & Intelligent Syst Nathan Qld 4111 Australia

ISBN: (纸本)9783642246685

Proteins are one of the most vital macromolecules on the cellular level. In order to understand the function of a protein, its structure needs to be determined. For this purpose, different computational approaches have been introduced. Genetic algorithms can be used to search the vast space of all possible conformations of a protein in order to find its native structure. A framework for design of such algorithms that is both generic, easy to use and performs fast on distributed systems may help further development of genetic algorithm based approaches. We propose such a framework based on a parallel master-slave model which is implemented in C++ and Message Passing interface. We evaluated its performance on distributed systems with a different number of processors and achieved a linear acceleration in proportion to the number of processing units.

关键词： parallel Genetic Algorithm Protein Optimisation Protein Structure Prediction

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GPU-Based Heterogeneous Coding Architecture for HEVC 16th

GPU-Based Heterogeneous Coding Architecture for HEVC

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16th international conference on algorithms and architectures for parallel processing (ica3pp)

作者： Cebrian-Marquez, Gabriel Migallon, Hector Luis Martinez, Jose Lopez-Granado, Otoniel Pinol, Pablo Cuenca, Pedro Univ Castilla La Mancha Albacete Res Inst Informat I3A Plz Univ 2 Albacete 02071 Spain Miguel Hernandez Univ Dept Phys & Comp Architecture Elche 03202 Spain

ISBN: (纸本)9783319495835;9783319495828

the High Efficiency Video Coding (HEVC) standard has nearly doubled the compression efficiency of prior standards. Nonetheless, this increase in coding efficiency involves a notably higher computing complexity that should be overcome in order to achieve real-time encoding. For this reason, this paper focuses on applying parallel processing techniques to the HEVC encoder with the aim of reducing significantly its computational cost without affecting the compression performance. Firstly, we propose a coarse-grained slice-based parallelization technique that is executed in a multi-core CPU, and then, with finer level of parallelism, a GPU-based motion estimation algorithm. Both techniques define a heterogeneous parallel coding architecture for HEVC. Results show that speed-ups of up to 4.06x can be obtained on a quad-core platform with low impact in coding performance.

关键词： H.265 HEVC Heterogeneous parallel encoding GPU

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On the Use of Binary Trees for DNA Hydroxymethylation Analysis 17th

On the Use of Binary Trees for DNA Hydroxymethylation Analys...

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

作者： Gonzalez, Cesar Perez, Mariano Orduna, Juan M. Chaves, Javier Garcia, Ana-Barbara Univ Valencia Dept Informat Avda Univ S-N Valencia 46100 Spain CIBERDEM Carlos III Hlth Inst INCLIVA Hlth Res Inst Avda Menendez Pelayo 4 Accesorio Valencia 46010 Spain

ISBN: (纸本)9783319654829;9783319654812

DNA methylation (mC) and hydroxymethylation (hmC) can have a significant effect on normal human development, health and disease status. Hydroxymethylation studies require specific treatment of DNA, as well as software tools for their analysis. In this paper, we propose a parallel software tool for analyzing the DNA hydroxymethylation data obtained by TAB-seq. the software is based on the use of binary trees for searching the different occurrences of methylation and hydroxymethylation in DNA samples. the binary trees allow to efficiently store and access the information about the methylation of each methylated/hydroxymethylated cytosines in the samples. Evaluation results shows that the performance of the application is only limited by the computer input/output bandwidth, even for the case of very long samples.

关键词： High performance computing DNA hydroxymethylation parallel pipeline

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parallel Belief Propagation Optimized by Coloring on GPUs 20th

Parallel Belief Propagation Optimized by Coloring on GPUs

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

作者： Hou, Junteng Si, Chengxiang Wang, Shupeng Wu, Guangjun Zhang, Lei Chinese Acad Sci Inst Informat Engn Beijing Peoples R China Univ Chinese Acad Sci Sch Cyber Secur Beijing Peoples R China Coordinat Ctr China Natl Comp Network Emergency Response Tech Team Beijing Peoples R China

ISBN: (纸本)9783030602451;9783030602444

Belief propagation (BP) is a message passing algorithm that infers over probabilistic graphical models. Its main computational workload, messages update, is suitable for GPU's massively parallel architecture. However, the efficiency of fully parallel BP is low, and traditional algorithms implemented on GPUs occupy amount of computing and memory resources. In this paper, we propose several GPU-friendly BP algorithms optimized by coloring. Color Wave (CW) algorithm performs multi-step coloring on residuals of non-convergent vertices to quickly obtain multiple disjoint partitions and vertices with the largest residuals in each partition, and then updates batches of messages in a fixed order. these operations are all suitable for parallelization and require little additional memory. To save time in each iteration, the Color Extract (CE) algorithm only update messages on edges with the largest residuals among all adjacent edges. the Random Drop (RD) algorithm steadily increases the convergence degree by progressively reducing the messages update ratio of non-convergent edges. the experiments on different GPUs show that our algorithms perform well throughout the calculation process. Compared with state-of-the-art algorithms, CW algorithm converged most of the messages in previous iterations. the convergence degree of CE is higher than all other algorithms in most calculation processes. RD converges fast and always has a high degree of convergence.

关键词： Belief propagation GPUs parallel optimization Coloring operations Progressively reducing update ratio

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RTEF-pp: A Robust Trust Evaluation Framework with Privacy Protection for Cloud Services Providers 19th

RTEF-PP: A Robust Trust Evaluation Framework with Privacy Pr...

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

作者： Zhong, Hong Zou, JianZhong Cui, Jie Xu, Yan Anhui Univ Sch Comp Sci & Technol Hefei 230039 Peoples R China Anhui Engn Lab IoT Secur Technol Hefei 230039 Peoples R China

ISBN: (纸本)9783030389918;9783030389901

the trust problem of Cloud Services Providers (CSPs) has become one of the most challenging issues for cloud computing. To build trust between Cloud Clients (CCs) and CSPs, a large number of trust evaluation frameworks have been proposed. Most of these trust evaluation frameworks collect and process evidence data such as the feedback and the preferences from CCs. However, evidence data may reveal the CCs' privacy. So far there are very few trust frameworks study on the privacy protection of CCs. In addition, when the number of malicious CCs' feedback increases, the accuracy of existing frameworks is greatly reduced. this paper proposes a robust trust evaluation framework RTEF-pp, which uses differential privacy to protect CCs' privacy. Furthermore, RTEF-pp uses the Euclidean distances between the monitored QoS values and CCs' feedback to detect malicious CCs' feedback ratings, and is not affected by the number of malicious CCs' feedback rating. Experimental results show that RTEF-pp is reliable and will not be affected by the number of malicious CCs' feedback rating.

关键词： Cloud computing Trust evaluation Robust Differential privacy

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