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parallel Kirchhoff pre-stack depth migration on large high performance clusters 15th

Parallel Kirchhoff pre-stack depth migration on large high p...

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15th international conference on algorithms and architectures for parallel processing, ICA3PP 2015

作者： Li, Chao Wang, Yida Zhao, Changhai Yan, Haihua Zhang, Jianlei School of Computer Science and Engineering Beihang University Beijing100191 China Research and Development Center BGP Inc. CNPC ZhuozhouHebei072751 China

ISBN: (纸本)9783319271361

Kirchhoff Pre-Stack Depth Migration (KPSDM) is a widely used algorithm for seismic imaging in petroleum industry. To provide higher FLOPS, modern high performance clusters are equipped with more computing nodes and more cores for each node. the evolution style of clusters leads to two problems for upper layer applications such as KPSDM: (1) the increasing disparity of the I/O capacity and computing performance is becoming a bottleneck for higher scalability;(2) the decreasing Mean Time Between Failures (MTBF) limits the availability of the applications. In this paper, we present an optimized parallel implementation of KPSDM to adapt to modern clusters. First, we convert the KPSDM into a clear and simple task-based parallel application by decomposing the computation along two dimensions: the imaging space and seismic data. then, those tasks are mapped to computing nodes that are organized using a two-level master/worker architecture to reduce the I/O workloads. And each task is further parallelized using multi-cores to fully utilize the computing resources. Finally, fault tolerance and checkpoint are implemented to meet the availability requirement in production environments. Experimental results with practical seismic data show that our parallel implementation of KPSDM can scale smoothly from 51 nodes (816 cores) to 211 nodes (3376 cores) with low I/O workloads on the I/O sub-system and multiple process failures can be tolerated efficiently. © Springer international Publishing Switzerland 2015.

关键词： Fault tolerance

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A personalized recommendation algorithm based on Hadoop

A personalized recommendation algorithm based on Hadoop

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international conference on Electronics Information and Emergency Communication

作者： Hao Huang Jianqing Huang Sotirios G. Ziavras Yaojie Lu School of Information Technology University of International Business and Economics Beijing PR China Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark U.S.A.

BDM-NBI algorithm is proposed at this paper. It focuses on the analysis of a personalized recommendation algorithm that utilizes a weighted bipartite graph suitable for processing big data. Our algorithm adopts bipartite graph partitioning using a vertex separator method that partitions a high-dimensional sparse matrix into a pseudo-block based diagonal matrix. then, the recommendation algorithm analyzes all weighted sub-matrices in parallel. We produce the global recommendation weighted matrix by merging all of the sub-matrices in parallel. Experiments with Hadoop show that our algorithm has good approximation for small matrices and excellent scalability.

关键词： Partitioning algorithms Sparse matrices Couplings Algorithm design and analysis Approximation algorithms Filtering Motion pictures

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Fast data-dependence profiling by skipping repeatedly executed memory operations 15th

Fast data-dependence profiling by skipping repeatedly execut...

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15th international conference on algorithms and architectures for parallel processing, ICA3PP 2015

作者： Li, Zhen Beaumont, Michael Jannesari, Ali Wolf, Felix Technische Universität Darmstadt Darmstadt64289 Germany RWTH Aachen University Aachen52062 Germany

ISBN: (纸本)9783319271392

Nowadays, more and more program analysis tools adopt pro- filing approaches in order to obtain data dependences because of their ability of tracking dynamically allocated memory, pointers, and array indices. However, dependence profiling suffers from high time overhead. To lower the overhead, former dependence profiling techniques either exploit features of the specific program analyses they are designed for, or let the profiling process run in parallel. Although they successfully lowered the time overhead of dependence profiling by a certain amount, none of them have tried to solve the fundamental problem that causes the high time overhead: the memory operations that are repeatedly executed in loops. In most of the time, these memory operations lead to exactly the same data dependences. However, a profiling method has to profile all these memory operations over and over again in order to not miss a single dependence that may occur just once. In this paper, we present a method that allow a dependence profiling technique to skip memory operations that are repeatedly executed in loops without missing any sin- gle data dependence. Our method works with all types of loops and does not require any prepossessing like source annotation of the input code. Experiment results show that our method can lower the time overhead of data-dependence profiling by up to 52%. © Springer international Publishing Switzerland 2015.

关键词： parallel programming

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Is there a Free Lunch for Image Feature Extraction in Web Applications 8th

Is There a Free Lunch for Image Feature Extraction in Web Ap...

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8th international conference on Similarity Search and Applications (SISAP)

作者： Krulis, Martin Charles Univ Prague Fac Math & Phys Parallel Architectures Algorithms Applicat Res Gr Malostranske Nam 25 Prague Czech Republic

ISBN: (纸本)9783319250878;9783319250861

Feature extraction is one of the essential parts of multimedia indexing in similarity search and content-based retrieval methods. Most applications that employ these methods also implement their client side interface using web technologies. the world wide web has become a well-established platform for distributed software and virtually all personal computers, tablets, and smartphones are equipped with a web browser. In the past, most applications employed a strict client-server approach, where the client part (running in the browser) handles only the user interface and the server side handles data storage and business logic. However, the client-side technologies leaped forward with the new HTML5 standard and the web browser has become capable of handling much more complex tasks. In this paper, we propose a model where the multimedia indexing is handled at the client side, which reduces necessary computational power of the server to run a web application that manages large multimedia database. We have implemented an in-browser image feature extractor and compared its performance with a server implementation.

关键词： HTML5 Image Feature extraction Multimedia indexing

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Joint redundancy and inspection-based maintenance optimization for series-parallel system 15th

Joint redundancy and inspection-based maintenance optimizati...

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15th international conference on algorithms and architectures for parallel processing, ICA3PP 2015

作者： Yao, Yuan He, Pan Zheng, Zhihao Tan, Chun Yuan, Yue Chongqing Institute of Green and Intelligent Technology Chinese Academy of Sciences Chongqing400714 China

ISBN: (纸本)9783319271361

While researchers have concentrated on the optimization of joint redundancy and maintenance mechanism, maintenance in computing systems is quite different from that in traditional systems. Considering a routine monitoring and inspection mechanisms is conducted to detect component status and trigger repair process, this paper pays attention to the optimization problem of joint redundancy and inspection-based maintenance mechanism. After conducting steady state analysis on subsystems using inspection-based maintenance, shared repair facility and component redundancy, optimization model is built to search appropriate system structure and maintenance policy which maximizes system performance while meeting availability and cost constraints. Due to the complexity of uncertain optimization model, genetic algorithm is used to search optimal solution, using triple-element encoding mechanism and specifically designed operators. Illustrative examples are conducted to show that the optimization model and corresponding solution technique could be used to search optimal system configuration under given constraints and different cost constraints would lead to different optimization result while meeting availability constraints. © Springer international Publishing Switzerland 2015.

关键词： Redundancy

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Identifying repeated interleavings to improve the efficiency of concurrency bug detection 15th

Identifying repeated interleavings to improve the efficiency...

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15th international conference on algorithms and architectures for parallel processing, ICA3PP 2015

作者： Wu, Zhendong Lu, Kai Wang, Xiaoping Science and Technology on Parallel and Distributed Processing Laboratory College of Computer National University of Defense Technology Changsha410073 China

ISBN: (纸本)9783319271392

Detecting concurrency bugs is becoming increasingly important. Many pattern-based concurrency bug detectors focus on the specific types of interleavings that are correlated to concurrency bugs. To detect multiple types of concurrency bugs, general detectors focus on multiple types of interleaving patterns, including data race pattern, atomicity violation pattern, and atomic-set violation pattern. Unfortunately, they suffer from redundant analysis due to repeated interleavings, which may affect the efficiency of concurrency bug detection. Hence, we propose an approach to identify the repeated interleavings. To the best of our knowledge, this is the first approach that can prune repeated interleavings to improve the efficiency of concurrency bug detection. We apply our approach to existing general detectors (PECAN and Maple) to avoid analyzing repeated interleavings. We evaluated the general detectors with and without our approach, respectively. the experimental results show that the bug detection results are not affected. With our approach, the bug detection time of PECAN and Maple are reduced by 40.0% and 44.4%, respectively. Additionally, our approach does not affect the overhead of bug detection, and consumes only a little memory. © Springer international Publishing Switzerland 2015.

关键词： Efficiency

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Mimer and Schedeval: Tools for Comparing Static Schedulers for Streaming Applications on Manycore architectures

Mimer and Schedeval: Tools for Comparing Static Schedulers f...

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international conference on parallel processing Workshops (ICPPW)

作者： Nicolas Melot Johan Janzén Christoph Kessler Linköpinq University Sweden Uppsala University Sweden

Scheduling algorithms published in the scientific literature are often difficult to evaluate or compare due to differences between the experimental evaluations in any two papers on the topic. Very few researchers share the details about the scheduling problem instances they use in their evaluation section, the code that allows them to transform the numbers they collect into the results and graphs they show, nor the raw data produced in their experiments. Also, many scheduling algorithms published are not tested against a real processor architecture to evaluate their efficiency in a realistic setting. In this paper, we describe Mimer, a modular evaluation tool-chain for static schedulers that enables the sharing of evaluation and analysis tools employed to elaborate scheduling papers. We propose Schedeval that integrates into Mimer to evaluate static schedules of streaming applications under throughput constraints on actual target execution platforms. We evaluate the performance of Schedeval at running streaming applications on the Intel Single-Chip Cloud computer (SCC), and we demonstrate the usefulness of our tool-chain to compare existing scheduling algorithms. We conclude that Mimer and Schedeval are useful tools to study static scheduling and to observe the behavior of streaming applications when running on many core architectures.

关键词： Schedules Processor scheduling Time-frequency analysis Switches Benchmark testing throughput Energy consumption

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parallel data regeneration based on multiple trees with network coding in distributed storage system 15th

Parallel data regeneration based on multiple trees with netw...

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15th international conference on algorithms and architectures for parallel processing, ICA3PP 2015

作者： You, Pengfei Huang, Zhen Wang, Changjian Hu, Minghao Peng, Yuxing College of Computer National University of Defense Technology Changsha410073 China

ISBN: (纸本)9783319271217

Distributed storage systems can provide large-scale data storage and high data reliability by redundant schemes, such as replica and erasure codes. Redundant data may get lost due to frequent node failures in the system. the lost data is needed to be regenerated as soon as possible so as to maintain data availability and reliability. the direct way for reducing regeneration time is to reduce network traffic in regeneration. Compared with that way, tree-structured regeneration achieves shorter regeneration time by constructing better treestructured topology to increase transmission bandwidth. However, some bandwidth of many other edges beyond the tree is not utilized to speed up transmission in tree-structured regeneration. In this paper, we consider to use multiple edge-disjoint trees to parallel regenerate the lost data, and analyze the total regeneration time. We deduce the formula about optimal regeneration time, and propose an approximate construction algorithm with polynomial time complexity for the optimal multiple regeneration trees. Our experiments shows, the regeneration time reduces 62 % compared with common tree–structured scheme, and the file availability reaches almost 99 %. © Springer international Publishing Switzerland 2015.

关键词： Network coding

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Real-time data flow language processing system for handling streams of data 5th

Real-time data flow language processing system for handling ...

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5th international conference on Scalable Information Systems, INFOSCALE 2014

作者： Park, Choon Seo Jeong, Jin-Hwan Lee, Myungcheol Lee, Yong-Ju Lee, Miyoung Hur, Sung Jin 161 Gajeong-Dong Yuseong-Gu Daejeon Korea Republic of

ISBN: (纸本)9783319168678

Apache Pig system generates MapReduce jobs by compiling program scripts written in Pig Latin to process large data sets in parallel on distributed computing nodes. there are inefficient features in Pig due to the limitation of the MapReduce, e.g., the MapReduce is used only for batch processing. As various smart devices are extensively utilized recently, streams of data are generated explosively and the need to process streams of data in real-time is required. In this paper, we propose a data flow language processing system, called LAMA-CEP, by generating DAG-based stream processing services to process unbounded streams of data in real-time continuously. We present a stream processing language, called Pig Latin Stream extended from Pig Latin. Programs written in Pig Latin Stream are translated into distributed stream processing jobs and then the jobs are executed on a highly scalable distributed stream processing system to process large streams of data in real-time. © Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2015.

关键词： MapReduce

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parallel Strategies for Harmony Search on CUDA to Solve Traveling Salesman Problem

Parallel Strategies for Harmony Search on CUDA to Solve Trav...

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international conference on IT Convergence and Security (ICITCS)

作者： Kang Chian Le Rosni Abdullah School of Computer Sciences Universiti Sains Malaysia Penang Malaysia

this paper presents parallel strategies applied to Harmony Search (HS) on CUDA for solving Traveling Salesman Problem (TSP), which is an NP-hard problem in combinatorial optimization. the implementations are tested with data instances of varying problem size from TSPLIB to measure speedup attained over serial implementation. In our experiment, HSGPU parallel implementation can acquire 32 times speedup as compared with CPU-based implementation.

关键词： Cities and towns Graphics processing units Instruction sets parallel processing Sociology Statistics Algorithm design and analysis

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