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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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Bipartite-oriented distributed graph partitioning for big learning 14

Bipartite-oriented distributed graph partitioning for big le...

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5th ACM Asia-Pacific Workshop on systems, APSYS 2014

作者： Chen, Rong Shi, Jiaxin 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)9781450330244

Many machine learning and data mining (MLDM) problems like recommendation, topic modeling and medical diagnosis can be modeled as computing on bipartite graphs. However, most distributed graph-parallel systems are oblivious to the unique characteristics in such graphs and existing online graph partitioning algorithms usually causes excessive replication of vertices as well as significant pressure on network communication. This article identifies the challenges and opportunities of partitioning bipartite graphs for distributed MLDM processing and proposes BiGraph, a set of bipartite-oriented graph partitioning algorithms. BiGraph leverages observations such as the skewed distribution of vertices, discriminated computation load and imbalanced data sizes between the two subsets of vertices to derive a set of optimal graph partition algorithms that result in minimal vertex replication and network communication. BiGraph has been implemented on PowerGraph and is shown to have a performance boost up to 17.75X (from 1.38X) for four typical MLDM algorithms, due to reducing up to 62% vertex replication, and up to 96% network traffic. © 2014 ACM.

关键词： Data mining

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Concurrent and consistent virtual machine introspection with hardware transactional memory

Concurrent and consistent virtual machine introspection with...

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20th IEEE International Symposium on High Performance computer Architecture, HPCA 2014

作者： Liu, Yutao Xia, Yubin 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)9781479930975

Virtual machine introspection, which provides tamperresistant, high-fidelity 'out of the box' monitoring of virtual machines, has many prominent security applications including VM-based intrusion detection, malware analysis and memory forensic analysis. However, prior approaches are either intrusive in stopping the world to avoid race conditions between introspection tools and the guest VM, or providing no guarantee of getting a consistent state of the guest VM. Further, there is currently no effective means for timely examining the VM states in question. In this paper, we propose a novel approach, called TxIntro, which retrofits hardware transactional memory (HTM) for concurrent, timely and consistent introspection of guest VMs. Specifically, TxIntro leverages the strong atomicity of HTM to actively monitor updates to critical kernel data structures. Then TxIntro can mount introspection to timely detect malicious tampering. To avoid fetching inconsistent kernel states for introspection, TxIntro uses HTM to add related synchronization states into the read set of the monitoring core and thus can easily detect potential inflight concurrent kernel updates. We have implemented and evaluated TxIntro based on Xen VMM on a commodity Intel Haswell machine that provides restricted transactional memory (RTM) support. To demonstrate the effectiveness of TxIntro, we implemented a set of kernel rootkit detectors using TxIntro. Evaluation results show that TxIntro is effective in detecting these rootkits, and is efficient in adding negligible performance overhead. © 2014 IEEE.

关键词： Malware

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Inside risks: Keys under doormats

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Communications of the ACM 2015年第10期58卷 24-26页

作者： Abelson, Harold Anderson, Ross Bellovin, Steven M. Benaloh, Josh Blaze, Matt Diffie, Whitfield Gilmore, John Green, Matthew Landau, Susan Neumann, Peter G. Rivest, Ronald L. Schiller, Jeffrey I. Schneier, Bruce Specter, Michael A. Weitzner, Daniel J. MIT Creative Commons Free Software Foundation United States University of Cambridge United Kingdom Computer Science Columbia University United States Microsoft Research United States University of Pennsylvania Distributed Systems Lab. United States Internet-Scale Communications United States Sun Microsystems Cygnus Solutions Electronic Frontier Foundation Cypherpunks Internet's alt newsgroups United States Johns Hopkins University Information Security Institute United States Worcester Polytechnic Institute United States Computer Science Lab SRI International ACM Risks Forum United States MIT Institute RSA Security and Verisign United States Internet Engineering Steering Group United States Berkman Center for Internet and Society Harvard Law School Resilient Systems Inc United States MIT Computer Science and Artificial Intelligence Lab MIT Cybersecurity and Internet Policy Research Initiative United States

The complexity of today's Internet environment means new law enforcement requirements are likely to introduce unanticipated security flaws. Political and law enforcement leaders in the U.S. and the U.K. have called for Internet systems to be redesigned to ensure government access to information even encrypted information. There are three general problems. First, providing exceptional access to communications would force a U-turn from the best practices now being deployed to make the Internet more secure. These practices include forward secrecy, where decryption keys are deleted immediately after use, so that stealing the encryption key used by a communications server would not compromise earlier or later communications. Second, building in exceptional access would substantially increase system complexity. Third, exceptional access would create concentrated targets that could attract bad actors. Moreover, law enforcement's stated need for rapid access to data would make it impractical to store keys offline or split keys among multiple key holders, as security engineers would normally do with extremely high-value credentials.

关键词： Law enforcement

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Density estimation with adaptive sparse grids for large data sets 14

Density estimation with adaptive sparse grids for large data...

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14th SIAM International Conference on Data Mining, SDM 2014

作者： Peherstorfer, Benjamin Pflüger, Dirk Bungartz, Hans-Joachim Aerospace Computational Design Laboratory AeroAstro Massachusetts Institute of Technology United States Simulation of Large Systems Group Institute for Parallel and Distributed Systems University of Stuttgart Germany Scientific Computing Group Department of Computer Science Technische Universität München Germany

ISBN: (纸本)9781510811515

Nonparametric density estimation is a fundamental problem of statistics and data mining. Even though kernel density estimation is the most widely used method, its performance highly depends on the choice of the kernel bandwidth, and it can become computationally expensive for large data sets. WTe present an adaptive sparse-grid-based density estimation method which discretizes the estimated density function on basis functions centered at grid points rather than on kernels centered at the data points. Thus, the costs of evaluating the estimated density function are independent from the number of data points. We give details on how to estimate density functions on sparse grids and develop a cross validation technique for the parameter selection. We show numerical results to confirm that our sparse-grid-based method is well-suited for large data sets, and, finally, employ our method for the classification of astronomical objects to demonstrate that it is competitive to current kernel-based density estimation approaches with respect to classification accuracy and runtime. Copyright © SIAM.

关键词： Data mining

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Coupling algorithms for partitioned multi-physics simulations 44

Coupling algorithms for partitioned multi-physics simulation...

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44. Jahrestagung der Gesellschaft fur Informatik INFORMATIK 2014 - Big Data - Komplexitat meistern - Big Data - Mastering Complexity: 44th Annual Meeting of the Society for computer science, INFORMATICS 2014

作者： Uekermann, Benjamin Gatzhammer, Bernhard Mehl, Miriam Department of Computer Science Technische Universität München Boltzmannstraße 3 Garching85748 Germany Institute for Parallel and Distributed Systems Universität Stuttgart Universitätsstraße 38 Stuttgart70569 Germany

ISBN: (纸本)9783885796268

Partitioned coupling approaches are an important tool in order to achieve a decent time-to-solution for multi-physics problems with more than two physical fields or changing combinations of fields. We study different approaches to deduce coupling schemes for partitioned multi-physics scenarios, by means of a simple, but yet challenging fluid-structure-fluid model problem. To our knowledge, this is the first time that a fully implicit black-box coupling scheme for partitioned multi-physics scenarios is described. This allows the simulation of a new range of applications in a partitioned way.

关键词： Fluid structure interaction

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RFA-Cut: Semi-automatic Segmentation of Radiofrequency Ablation Zones with and without Needles via Optimal s-t-Cuts

RFA-Cut: Semi-automatic Segmentation of Radiofrequency Ablat...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society

作者： Jan Egger Harald Busse Philipp Brandmaier Daniel Seider Matthias Gawlitza Steffen Strocka Philip Voglreiter Mark Dokter Michael Hofmann Bernhard Kainz Xiaojun Chen Alexander Hann Pedro Boechat Wei Yu Bernd Freisleben Tuomas Alhonnoro Mika Pollari Michael Moche Dieter Schmalstieg Institute for Computer Graphics and Vision Graz University of Technology Austria Dept. of Diagnostic and Interventional Radiology Leipzig University Hospital Germany Dept. of Computing Imperial College London UK School of Mechanical Engineering Shanghai Jiao Tong University Shanghai China Dept. of Internal Medicine and Gastroenterology Katharinenhospital Stuttgart Germany Distributed Systems Group Philipp University of Marburg Germany School of Science Aalto University Espoo Finland

ISBN: (纸本)9781424492695

In this contribution, we present a semi-automatic segmentation algorithm for radiofrequency ablation (RFA) zones via optimal s-t-cuts. Our interactive graph-based approach builds upon a polyhedron to construct the graph and was specifically designed for computed tomography (CT) acquisitions from patients that had RFA treatments of Hepatocellular Carcinomas (HCC). For evaluation, we used twelve post-interventional CT datasets from the clinical routine and as evaluation metric we utilized the Dice Similarity Coefficient (DSC), which is commonly accepted for judging computer aided medical segmentation tasks. Compared with pure manual slice-by-slice expert segmentations from interventional radiologists, we were able to achieve a DSC of about eighty percent, which is sufficient for our clinical needs. Moreover, our approach was able to handle images containing (DSC=75.9%) and not containing (78.1%) the RFA needles still in place. Additionally, we found no statistically significant difference (p<0.423) between the segmentation results of the subgroups for a Mann-Whitney test. Finally, to the best of our knowledge, this is the first time a segmentation approach for CT scans including the RFA needles is reported and we show why another state-of-the-art segmentation method fails for these cases. Intraoperative scans including an RFA probe are very critical in the clinical practice and need a very careful segmentation and inspection to avoid under-treatment, which may result in tumor recurrence (up to 40%). If the decision can be made during the intervention, an additional ablation can be performed without removing the entire needle. This decreases the patient stress and associated risks and costs of a separate intervention at a later date. Ultimately, the segmented ablation zone containing the RFA needle can be used for a precise ablation simulation as the real needle position is known.

关键词： RFA decreases patient stress

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Concurrent and consistent virtual machine introspection with hardware transactional memory

Concurrent and consistent virtual machine introspection with...

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IEEE Symposium on High-Performance computer Architecture

作者： Yutao Liu Yubin Xia Haibing Guan Binyu Zang Haibo Chen Institute of Parallel and Distributed Systems Shanghai Jiao Tong University Department of Computer Science Shanghai Jiao Tong University

Virtual machine introspection, which provides tamperresistant, high-fidelity “out of the box” monitoring of virtual machines, has many prominent security applications including VM-based intrusion detection, malware analysis and memory forensic analysis. However, prior approaches are either intrusive in stopping the world to avoid race conditions between introspection tools and the guest VM, or providing no guarantee of getting a consistent state of the guest VM. Further, there is currently no effective means for timely examining the VM states in question. In this paper, we propose a novel approach, called TxIntro, which retrofits hardware transactional memory (HTM) for concurrent, timely and consistent introspection of guest VMs. Specifically, TxIntro leverages the strong atomicity of HTM to actively monitor updates to critical kernel data structures. Then TxIntro can mount introspection to timely detect malicious tampering. To avoid fetching inconsistent kernel states for introspection, TxIntro uses HTM to add related synchronization states into the read set of the monitoring core and thus can easily detect potential inflight concurrent kernel updates. We have implemented and evaluated TxIntro based on Xen VMM on a commodity Intel Haswell machine that provides restricted transactional memory (RTM) support. To demonstrate the effectiveness of TxIntro, we implemented a set of kernel rootkit detectors using TxIntro. Evaluation results show that TxIntro is effective in detecting these rootkits, and is efficient in adding negligible performance overhead.

关键词： Kernel Monitoring Educational institutions Abstracts Single photon emission computed tomography Virtual machine monitors Continuous wavelet transforms

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ChaosFIRE: An experiment with chaoster, the context-aware collaboration platform for crisis/chaos management

ChaosFIRE: An experiment with chaoster, the context-aware co...

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IEEE Annual Conference on Pervasive Computing and Communications Workshops (PerCom)

作者： László Kovács Balázs E. Pataki MTA SZTAKI DSD Department of Distributed Systems Institute for Computer Science and Control Hungarian Academy of Sciences Budapest Hungary

Summary form only given. ChaosFIRE is an experiment project to evaluate the performance and usability of peer-to-peer mobile technologies as an alternative mean to central service based solutions to collect and distribute sensor information in an urban area. The Project runs under the 1st Open Call of Fed4FIRE IP under FP7 and is based on the technology developed in the Chaoster project of MTA SZTAKI DSD. Chaoster is a DTN-PSN (Delay Tolerant Networking - Pocket Switched Network) based adaptive, context-aware collaboration platform supporting emergent interoperability for crisis/chaos management. DTN-PSN communication layer of Chaoster is used in this experiment together with the ChaosONE simulator, for the evaluation of DTN communication protocols. This talk will present the Chaoster platform, the target use cases of the solution and the aims and results of the ChaosFIRE experiment.

关键词： Chaotic communication Collaboration computer science Peer-to-peer computing Mobile communication Interoperability

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Computational Offloading or Data Binding? Bridging the Cloud Infrastructure to the Proximity of the Mobile User

Computational Offloading or Data Binding? Bridging the Cloud...

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IEEE International Conference on Mobile Cloud Computing, Services, and Engineering

作者： Huber Flores Satish Narayana Srirama Rajkumar Buyya University of Tartu Institute of Computer Science Mobile Cloud Lab University of Melbourne Department of Computing and Information Systems Cloud Computing and Distributed Systems Laboratory (CLOUDS)

ISBN: (纸本)9781479944248

Mobile and cloud computing are converging as the prominent technologies that are leading the change to the post personal computing (PC) era. Computational offloading and data binding are the core techniques that foster to elastically augment the capabilities of low-power devices, such as smartphones. Mobile applications may be bonded to cloud resources by following a task delegation or code offloading criteria. In a delegation model, a handset can utilize the cloud in a service-oriented manner to delegate asynchronously a resource-intensive mobile task by direct invocation of the service. In contrast, in an offloading model, a mobile application is partitioned and analyzed so that the most computational expensive operations at code level can be identified and offloaded to a remote cloud-based surrogate. We compared in this paper, the mobile cloud computing models for offloading and delegation. We utilized our own frameworks for computational offloading and data binding in the analysis. While in principle, offloading and delegation are viable methods to augment the capabilities of the mobile devices with cloud power, they enrich the mobile applications from different perspectives at diverse computational scales.

关键词： Mobile Cloud Computing Access Models Code Offloading Task Delegation Middleware Mobile Crowdsourcing

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