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SYNC or ASYNC: Time to fuse for distributed graph-parallel computation 2015

SYNC or ASYNC: Time to fuse for distributed graph-parallel c...

引用

20th ACM SIGPLAN Symposium on Principles and Practice of parallel Programming, PPoPP 2015

作者： Xie, Chenning Chen, Rong Guan, Haibing Zang, Binyu Chen, Haibo Shanghai Key Laboratory of Scalable Computing and Systems Institute of Parallel and Distributed Systems Shanghai Jiao Tong University China Shanghai Key Laboratory of Scalable Computing and Systems Department of Computer Science Shanghai Jiao Tong University China

ISBN: (纸本)9781450332057

Large-scale graph-structured computation usually exhibits iterative and convergence-oriented computing nature, where input data is computed iteratively until a convergence condition is reached. Such features have led to the development of two different computation modes for graph-structured programs, namely synchronous (Sync) and asynchronous (Async) modes. Unfortunately, there is currently no in-depth study on their execution properties and thus programmers have to manually choose a mode, either requiring a deep understanding of underlying graph engines, or suffering from suboptimal performance. This paper makes the first comprehensive characterization on the performance of the two modes on a set of typical graph-parallel applications. Our study shows that the performance of the two modes varies significantly with different graph algorithms, partitioning methods, execution stages, input graphs and cluster scales, and no single mode consistently outperforms the other. To this end, this paper proposes Hsync, a hybrid graph computation mode that adaptively switches a graph-parallel program between the two modes for optimal performance. Hsync constantly collects execution statistics on-the-fly and leverages a set of heuristics to predict future performance and determine when a mode switch could be profitable. We have built online sampling and offline profiling approaches combined with a set of heuristics to accurately predicting future performance in the two modes. A prototype called PowerSwitch has been built based on PowerGraph, a state-of-the-art distributed graph-parallel system, to support adaptive execution of graph algorithms. On a 48-node EC2-like cluster, PowerSwitch consistently outperforms the best of both modes, with a speedup ranging from 9% to 73% due to timely switch between two modes. Copyright 2015 ACM.

关键词： Graphic methods

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Tinman: Eliminating confidential mobile data exposure with security oriented offloading 15

Tinman: Eliminating confidential mobile data exposure with s...

引用

10th European Conference on Computer Systems, EuroSys 2015

作者： Xia, Yubin Liu, Yutao Tan, Cheng Ma, Mingyang Guan, Haibing Zang, Binyu Chen, Haibo Shanghai Key Laboratory of Scalable Computing and Systems China Institute of Parallel and Distributed Systems Shanghai Jiao Tong University China Department of Computer Science Shanghai Jiao Tong University China

ISBN: (纸本)9781450332385

The wide adoption of smart devices has stimulated a fast shift of security-critical data from desktop to mobile devices. However, recurrent device theft and loss expose mobile devices to various security threats and even physical attacks. This paper presents TinMan, a system that protects confidential data such as web site password and credit card number (we use the term cor to represent these data, which is short for Confidential Record) from being leaked or abused even under device theft. TinMan separates accesses of cor from the rest of the functionalities of an app, by introducing a trusted node to store cor and offloading any code from a mobile device to the trusted node to access cor. This completely eliminates the exposure of cor on the mobile devices. The key challenges to TinMan include deciding when and how to efficiently and transparently offload execution;Tin-Man addresses these challenges with security-oriented offloading with a low-overhead tainting scheme called asymmetric tainting to track accesses to cor to trigger offloading, as well as transparent SSL session injection and TCP payload replacement to offload accesses to cor. We have implemented a prototype of TinMan based on Android and demonstrated how TinMan protects the information of user's bank account and credit card number without modifying the apps. Evaluation results also show that TinMan incurs only a small amount of performance and power overhead. Copyright © 2015 ACM.

关键词： Crime

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Ranking Open Source Software Based on Crowd Wisdom

Ranking Open Source Software Based on Crowd Wisdom

引用

2015 6th IEEE International Conference on Software Engineering and Service Science(ICSESS 2015)

作者： Qiang Fan Huaimin Wang Gang Yin Tao Wang National Laboratory of Parallel and Distributed Computing School of Computer National University of Defense Technology

Software reuse is critical in open source based software development, but it is very difficult to find a excellent reusable from large amount of similar candidate software in communities. Currently, lots of research works evaluate software by analyzing artifacts created by software developers, few of them reveals the power of feedbacks generated by software users, which we believe very valuable for software ranking. In this paper, we connect open source software from different communities with user feedbacks in Stack Overflow, and explore the correlation between the popularity of posts and time. Finally we rank open source software through using information of connected posts in Stack Overflow and compare our ranking result with several influential ranking results like DB-Engines and personal blogs. The comparison results show that our approach can amazingly give similar ranking results to that given by experienced professionals or commercial ranking systems.

关键词： Software ranking Open Source Crowd Wisdom Open Source Community

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Ranking open source software based on crowd wisdom

Ranking open source software based on crowd wisdom

引用

IEEE International Conference on Software Engineering and Service Sciences (ICSESS)

作者： Qiang Fan Huaimin Wang Gang Yin Tao Wang National Laboratory of Parallel and Distributed Computing National University of Defense Technology ChangSha Hunan China

ISBN: (纸本)9781479983544

Software reuse is critical in open source based software development, but it is very difficult to find a excellent reusable from large amount of similar candidate software in communities. Currently, lots of research works evaluate software by analyzing artifacts created by software developers, few of them reveals the power of feedbacks generated by software users, which we believe very valuable for software ranking. In this paper, we connect open source software from different communities with user feedbacks in StackOverflow, and explore the correlation between the popularity of posts and time. Finally we rank open source software through using information of connected posts in StackOverflow and compare our ranking result with several influential ranking results like DB-Engines and personal blogs. The comparison results show that our approach can amazingly give similar ranking results to that given by experienced professionals or commercial ranking systems.

关键词： Open source software Data models Joining processes Software reusability Internet

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OSSEAN: Mining Crowd Wisdom in Open Source Communities

OSSEAN: Mining Crowd Wisdom in Open Source Communities

引用

2015 IEEE Symposium on Service-Oriented System Engineering

作者： Gang Yin Tao Wang Huaimin Wang Qiang Fan Yang Zhang Yue Yu Cheng Yang National Laboratory of Parallel and Distributed Computing National University of Defense Technology ChangSha Hunan China

Nowadays open source software represents a successful crowd-based software production model and is becoming an ecosystem combining huge amounts of software producers (such as software developers) and consumers (such as software users and customers). Lots of research work has been conducted on analyzing software artifacts created by producers, but few of them reveal the power of feedback from consumers which we believe is very important for the evaluation and evolution of open source software. This paper introduces OSSEAN, a platform for Open Source Software Evaluating, Analyzing and Networking. OSSEAN divides the open source communities into two groups: software production communities and software consumption communities. The former contain structured software artifacts such as projects, source code and issues, while the latter are full of textual documents with rich semantics of user feedback. We show the power of OSSEAN with some interesting demos by analyzing more than 200 thousands of open source projects and 10 million documents.

关键词： Communities Production Data mining Crawlers Open source software Ecosystems

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MatrixMap: Programming Abstraction and Implementation of Matrix Computation for Big Data Applications

MatrixMap: Programming Abstraction and Implementation of Mat...

引用

International Conference on parallel and distributed Systems (ICPADS)

作者： Yaguang Huangfu Jiannong Cao Hongliang Lu Guanqing Liang Department of Computing The Hong Kong Polytechnic University Parallel and Distributed Processing Laboratory National University of Defense Technology

The computation core of many big data applications can be expressed as general matrix computations, including linear algebra operations and irregular matrix operations. However, existing parallel programming systems such as Spark do not have programming abstraction and efficient implementation for general matrix computations. In this paper, we present MatrixMap, a unified and efficient data-parallel system for general matrix computations. MatrixMap provides powerful yet simple abstraction, consisting of a distributed data structure called bulk key matrix and a computation interface defined by matrix patterns. Users can easily load data into bulk key matrices and program algorithms into parallel matrix patterns. MatrixMap outperforms current state-of-the-art systems by employing three key techniques: matrix patterns with lambda functions for irregular and linear algebra matrix operations, asynchronous computation pipeline with optimized data shuffling strategies for specific matrix patterns and in-memory data structure reusing data in iterations. Moreover, it can automatically handle the parallelization and distribute execution of programs on a large cluster. The experiment results show that MatrixMap is 12 times faster than Spark.

关键词： Data structures Programming Linear algebra Machine learning algorithms Sparks Sparse matrices Computational modeling

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parallel image sharpness measure for supercomputing environment

Parallel image sharpness measure for supercomputing environm...

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International Symposium on Applied Machine Intelligence and Informatics (SAMI)

作者： Gergely Windisch Miklós Kozlovszky Óbuda University/John von Neumann Faculty of Informatics Budapest Hungary MTA SZT AKI/Laboratory of Parallel and Distributed Computing Budapest Hungary

Image sharpness is an important part of the overall quality of an image. There are multiple metrics to evaluate image sharpness, the algorithms are mainly created for regular desktop computers. This article describes the sharpness metrics devised and implemented at Obuda University parallelized and ported to an HPC infrastructure. Along with the native ported application a workflow has been created on the gUSE/WS-PGRADE portal system and an ASM portlet has been developed to make the service readily available to.

关键词： Measurement Supercomputers Portals Logic gates Program processors Bioinformatics Biomedical imaging

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Constrained Projective Non-negative Matrix Factorization for Semi-supervised Multi-label Learning

Constrained Projective Non-negative Matrix Factorization for...

引用

International Conference on Machine Learning and Applications (ICMLA)

作者： Xiang Zhang Naiyang Guan Zhigang Luo Xuejun Yang College of Computer National University of Defense Technology Changsha China National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China The State key Laboratory of High Performance Computing National University of Defense Technology Changsha China

This paper formulates multi-label learning as a constrained projective non-negative matrix factorization (CPNMF) problem which concentrates on a variant of the original projective NMF (PNMF) and explicitly introduces an auxiliary basis to learn the semantic subspace and boosts its discriminating ability by exploiting labeled and unlabeled examples together. Particularly, it propagates labels of the labeled examples to the unlabeled ones by enforcing coefficients of examples sharing identical semantic contents to be identical based on a hard constraint, i.e., embedding the class indicator of labeled examples into their coefficients. CPNMF preserves the geometrical structure of dataset via manifold regularization meanwhile captures the inherent structure of labels by using label correlations. We developed a multiplicative update rule (MUR) based algorithm to optimize CPNMF and proved its convergence. Experiments of image annotation on Corel dataset, text categorization on Rcv1v2 dataset, and text clustering on two popular text corpuses suggest the effectiveness of CPNMF.

关键词： Conferences

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Situation and location awareness in harsh environment

Situation and location awareness in harsh environment

引用

Proceedings of the International Convention MIPRO

作者： Miklos Kozlovszky Daniela Zavec Pavlinić Andreja Oder Gábor Fehér Pál Bogdanov MTA SZTAKI Laboratory of Parallel and Distributed Computing Budapest Hungary John von Neumann Faculty of Informatics Óbuda University Budapest Hungary Titera Technical Innovative Technologies Ltd. Slovenia Prevent&Deloza Ltd. Celje Slovenia OMT-LAB Budapest University Hungary

Enhanced environment awareness is a key element of life protection in dangerous situations. Thus the Personal Protection Equipment (PPE) clothing industry is forced in the direction to develop highly innovative “intelligent” products, and equip their products with sensors and actuators combined with smart technologies. Besides basic functions of protection, thermal and ergonomic comfort, these new generation protective garments have additional functions such as monitoring and/or alarming for prevention in case of emergency situation. Such systems are costly because even if the clothing and engineering parts of the development are feasible, their combination is far from trivial. The different system parts have different requirements, and these requirements are sometimes not compatible with each other. Parameters such as cost, bulkiness, accuracy, independency, scalability, robustness are key parameters, which can cause high acceptance or usage prevention rapidly by the end-users. Our research is focusing on the seamless integration of the various subsystems to develop effective and user friendly, intelligent situation aware personal protection systems. Our solution helps to receive accurate information about user performance and activity conditions. The main goal of our work is to adapt the already existing monitoring solution and provide it to people working in harsh environment. The paper describes the results of our development with the description of the main functionalities.

关键词： Data acquisition Sensor fusion Monitoring Accuracy Data integration Data visualization

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Computation and communication efficient graph processing with distributed immutable view 14

Computation and communication efficient graph processing wit...

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23rd ACM Symposium on High-Performance parallel and distributed computing, HPDC 2014

作者： Chen, Rong Ding, Xin Wang, Peng Chen, Haibo Zang, Binyu Guan, Haibing Shanghai Key Laboratory of Scalable Computing and Systems Institute of Parallel and Distributed Systems Shanghai Jiao Tong University China Shanghai Key Laboratory of Scalable Computing and Systems Department of Computer Science Shanghai Jiao Tong University China

ISBN: (纸本)9781450327480

Cyclops is a new vertex-oriented graph-parallel framework for writing distributed graph analytics. Unlike existing distributed graph computation models, Cyclops retains simplicity and computation-efficiency by synchronously computing over a distributed immutable view, which grants a vertex with read-only access to all its neighboring vertices. The view is provided via readonly replication of vertices for edges spanning machines during a graph cut. Cyclops follows a centralized computation model by assigning a master vertex to update and propagate the value to its replicas unidirectionally in each iteration, which can significantly reduce messages and avoid contention on replicas. Being aware of the pervasively available multicore-based clusters, Cyclops is further extended with a hierarchical processing model, which aggregates messages and replicas in a single multicore machine and transparently decomposes each worker into multiple threads ondemand for different stages of computation. We have implemented Cyclops based on an open-source Pregel clone called Hama. Our evaluation using a set of graph algorithms on an in-house multicore cluster shows that Cyclops outperforms Hama from 2.06X to 8.69X and 5.95X to 23.04X using hash-based and Metis partition algorithms accordingly, due to the elimination of contention on messages and hierarchical optimization for the multicore-based clusters. Cyclops (written in Java) also has comparable performance with PowerGraph (written in C++) despite the language difference, due to the significantly lower number of messages and avoided contention. Copyright © 2014 ACM.

关键词： Iterative methods

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