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2018 SIAM International Conference on Data Mining, SDM 2018

作者： Smith, Shaden Huang, Kejun Sidiropoulos, Nicholas D. Karypis, George Intel Parallel Computing Lab United States University of Minnesota United States University of Virginia United States

Sparse tensor factorization is a popular tool in multi-way data analysis and is used in applications such as cybersecurity, recommender systems, and social network analysis. In many of these applications, the tensor is not known a priori and instead arrives in a streaming fashion for a potentially unbounded amount of time. Existing approaches for streaming sparse tensors are not practical for unbounded streaming because they rely on maintaining the full factorization of the data, which grows linearly with time. In this work, we present CP-stream, an algorithm for streaming factorization in the model of the canonical polyadic decomposition which does not grow linearly in time or space, and is thus practical for long-term streaming. Additionally, CP-stream incorporates user-specified constraints such as non-negativity which aid in the stability and interpretability of the factorization. An evaluation of CP-stream demonstrates that it converges faster than state-of-the-art streaming algorithms while achieving lower reconstruction error by an order of magnitude. We also evaluate it on real-world sparse datasets and demonstrate its usability in both network traffic analysis and discussion tracking. Our evaluation uses exclusively public datasets and our source code is released to the public as part of SPLATT, an open source high-performance tensor factorization toolkit. © 2018 by SIAM.

关键词： Factorization

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Rupeas: Ruby powered event analysis DSL

Rupeas: Ruby powered event analysis DSL

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International Conference on Networked Sensing Systems

作者： Woehrle, Matthias Plessl, Christian Thiele, Lothar Computer Engineering and Networks Lab ETH Zurich Switzerland Paderborn Center for Parallel Computing University of Paderborn Germany

ISBN: (纸本)9781424479108

Wireless Sensor Networks (WSNs) are unique embedded computer systems for distributed sensing of a dispersed phenomenon. As WSNs are deployed in remote locations for longterm unattended operation, assurance of correct functioning of the system is of prime concern. Thus, the design and development of WSNs requires specialized tools to allow for testing. To this end, we present a novel language, Rupeas, for analyzing WSNs based on collected events during system operation. Rupeas is independent from test specifics and thus generally applicable for analyzing event logs of WSN test executions. © 2010 IEEE.

关键词： Wireless sensor networks

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A clustering-based approach for mining dockerfile evolutionary trajectories

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Science China(Information Sciences) 2019年第1期62卷 211-213页

作者： Yang ZHANG Huaimin WANG Vladimir FILKOV Key Laboratory of Parallel and Distributed Computing National University of Defense Technology College of Computer National University of Defense Technology DECAL Lab University of California Computer Science Department University of California

Dear editor,Docker1), as a de-facto industry standard [1], enables the packaging of an application with all its dependencies and execution environment in a light-weight, self-contained unit, i.e., *** launching the container from Docker image, developers can easily share the same operating system, libraries, and binaries [2]. As the configuration file, the dockerfile plays an important role,

关键词： A clustering-based approach for mining dockerfile evolutionary trajectories

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Personalized mobile application discovery 1

Personalized mobile application discovery

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1st International Workshop on Crowd-Based Software Development Methods and Technologies, CrowdSoft 2014

作者： Yang, Cheng Wang, Tao Yin, Gang Wang, Huaimin Wu, Ming Xiao, Ming Key Lab. of Parallel and Distributed Computing Colledge of Computer National University of Defence Technology ChangSha Hunan China

ISBN: (纸本)9781450332248

With the dramatic growing of mobile application markets, users can find apps with any function they desire in these markets. However, the huge amounts of apps make it quite a challenge for users to discover good applications efficiently. Previous studies recommend applications based on the download history, user ratings or app usage records. Most of these studies fail to capture users' personal interests in mobile applications precisely. In this paper, we leverage apps as features for describing user's personal interests and propose a novel approach to do personalized recommendation. We introduce a Small-Crowd model to distinguish apps at reflecting users' personal interests, and design a weighting method to rank the installed apps for users by combining the global download information with fine-grained app usage records. The extensive experiments validate the effectiveness of our approach which outperforms state-of-the-art method. Copyright 2014 ACM.

关键词： Mobile computing

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Translation validation of loop and arithmetic transformations in the presence of recurrences 2016

Translation validation of loop and arithmetic transformation...

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17th ACM SIGPLAN/SIGBED Conference on Languages, Compilers, Tools and Theory for Embedded Systems, LCTES 2016

作者： Banerjee, Kunal Mandal, Chittaranjan Sarkar, Dipankar Department of Computer Science and Engineering Indian Institute of Technology Kharagpur India Intel Parallel Computing Lab Bangalore India

ISBN: (纸本)9781450343169

Compiler optimization of array-intensive programs involves extensive application of loop transformations and arithmetic transformations. Hence, translation validation of array-intensive programs requires manipulation of intervals of integers (representing domains of array indices) and relations over such intervals to account for loop transformations and simplification of arithmetic expressions to handle arithmetic transformations. A major obstacle for verification of such programs is posed by the presence of recurrences, whereby an element of an array gets defined in a statement S inside a loop in terms of some other element(s) of the same array which have been previously defined through the same statement S. Recurrences lead to cycles in the data-dependence graph of a program which make dependence analyses and simplifications (through closed-form representations) of the data transformations difficult. Another technique which works better for recurrences does not handle arithmetic transformations. In this work, array data-dependence graphs (ADDGs) are used to represent both the original and the optimized versions of the program and a validation scheme is proposed where the cycles due to recurrences in the ADDGs are suitably abstracted as acyclic subgraphs. Thus, this work provides a unified equivalence checking framework to handle loop and arithmetic transformations along with most of the recurrences - this combination of features had not been achieved by a single verification technique earlier. ©2016 ACM.

关键词： Application programs

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A supervised approach for tag hierarchy construction in open source communities 15

A supervised approach for tag hierarchy construction in open...

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7th Asia-Pacific Symposium on Internetware, Internetware 2015

作者： Gu, Chongming Yin, Gang Wang, Tao Yang, Cheng Wang, Huaimin Key Lab. of Parallel and Distributed Computing Colledge of Computer National University of Defence Technology ChangSha Hunan China

ISBN: (纸本)9781450336413

The massive amounts of open source software provide sufficient reusable resources for software development. Most of the OSS communities adopt a kind of categorization or tagging mechanism to organize the software. However, the categorization often too coarse, while the tags are flat and fail to capture the inter-relation among them. In this paper, we propose a novel approach to reveal the latent relations between tags and build a tag hierarchy to help locate resources. We firstly build a co-occurrence network, based on which we compare the connotations of tags and construct a preliminary hierarchy. Then we leverage the domain knowledge of category in SourceForge to optimize and improve the relations between tags. At the end, we demonstrate the effectiveness of the constructed tag hierarchy with quantitative evaluation, which suggest the validation of our approach. © 2015 ACM.

关键词： Open source software

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Evaluating bug severity using crowd-based knowledge: An exploratory study 15

Evaluating bug severity using crowd-based knowledge: An expl...

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7th Asia-Pacific Symposium on Internetware, Internetware 2015

作者： Zhang, Yang Yin, Gang Wang, Tao Yu, Yue Wang, Huaimin Key Lab. of Parallel and Distributed Computing College of Computer National University of Defense Technology Changsha410073 China

ISBN: (纸本)9781450336413

In bug tracking system, the high volume of incoming bug reports poses a serious challenge to project managers. Triaging these bug reports manually consumes time and resources which leads to delaying the resolution of important bugs. StackOverow is the most popular crowdsourcing Q&A community with plenty of bug-related posts. In this paper, we explore the correlation between bug severity and the crowd attributes of linked posts. Two typical types of projects' bug repositories are studied here, e.g. Mozilla (user-centric project) and Eclipse (developer-centric project). Our results show that the bug severity is consistent with the crowd- based knowledge both in Mozilla and Eclipse, i.e. the linked posts of severe bugs have higher score etc. in StackOverow than non-severe bugs. This interesting phenomenon inspires us that we can optimize the existing evaluation methods of bug severity by incorporating the crowd-based knowledge from a third-party in future. © 2015 ACM.

关键词： StackOverflow crowd-based knowledge Bugzilla Bug severity

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GPP-grep: High-speed regular expression processing engine on general purpose processors

GPP-grep: High-speed regular expression processing engine on...

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15th International Symposium on Research in Attacks, Intrusions, and Defenses, RAID 2012

作者： Valgenti, Victor C. Chhugani, Jatin Sun, Yan Satish, Nadathur Kim, Min Sik Kim, Changkyu Dubey, Pradeep School of EECS Washington State University United States Parallel Computing Lab. Intel Corporation United States

ISBN: (纸本)9783642333378

Deep Packet Inspection (DPI) serves as a major tool for Network Intrusion Detection Systems (NIDS) for matching datagram payloads to a set of known patterns that indicate suspicious or malicious behavior. Regular expressions offer rich context for describing these patterns. Unfortunately, large rule sets containing thousands of patterns coupled with high link-speeds leave most regular expression matching methods incapable of matching at real-time without specialized hardware. We present GPP-grep, an NFA-based regular expression processing engine designed for maximum performance on General Purpose Processors. The primary contribution of GPP-grep is the utilization of the data-level parallelism available in modern CPUs to reduce the overhead incurred when tracking multiple states in NFA. In essence, we build and store the NFA in an architecture-friendly manner that exploits locality and then traverse the NFA maximizing the parallelism available and minimizing cache-misses and long-latency memory lookups. GPPgrep demonstrates 24-57x improvement in throughput over standard finite automata techniques on a set of up to 1200 regular-expressions culled from the NIDS Snort, and is within 1.3x of FPGA hardware-based techniques. GPP-grep achieves 2Gbps throughput on a dual-socket commodity CPU system allowing for line-speed evaluation on commodity hardware. © 2012 Springer-Verlag.

关键词： Program processors

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Exploring the use of @-mention to assist software development in GitHub 15

Exploring the use of @-mention to assist software developmen...

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7th Asia-Pacific Symposium on Internetware, Internetware 2015

作者： Zhang, Yang Wang, Huaimin Yin, Gang Wang, Tao Yu, Yue Key Lab. of Parallel and Distributed Computing College of Computer National University of Defense Technology Changsha410073 China

ISBN: (纸本)9781450336413

Recently, many researches propose that social media tools can promote the collaboration among developers, which are beneficial to the software development. Nevertheless, there is little empirical evidence to confirm that using @-mention has indeed a beneficial impact on the issues in GitHub. In this paper, we analyze the data from GitHub and give some insights on how @-mention is used in the issues (general- issues and pull-requests). Our statistical results indicate that, @-mention attracts more participants and tends to be used in the difficult issues. @-mention favors the solving process of issues by enlarging the visibility of issues and facilitating the developers' collaboration. In addition to this global study, our study also build a @-network based on the @-mention database we extract. Through the @-network, we can mine the relationships and characteristics of developers in GitHub's issues. © 2015 ACM.

关键词： Social networking (online)

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Evaluating data parallelism in C++ using the parallel Research Kernels 19

Evaluating data parallelism in C++ using the Parallel Resear...

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2019 International Workshop on OpenCL, IWOCL 2019

作者： Hammond, Jeff R. Mattson, Timothy G. Data Center Group Intel Corporation HillsboroOR United States Parallel Computing Lab Intel Corporation HillsboroOR United States

The parallel Research Kernels are a set of simple algorithms that correspond to popular classes of high-performance computing applications. We report on their use to evaluate parallel programming models based upon mod... 详细信息

ISBN: (纸本)9781450362306

关键词： C++ (programming language)

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