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Augmenting trust establishment in dynamic systems with social networks 10

Augmenting trust establishment in dynamic systems with socia...

引用

Proceedings of the Sixth Annual Workshop on Cyber Security and information Intelligence Research

作者： Lagesse, Brent Kumar, Mohan Venkatesh, Svetha Lazarescu, Mihai Cyberspace Science and Information Intelligence Research Group Computational Science and Engineering Division Oak Ridge National Laboratory United States Department of Computer Science Engineering University of Texas Arlington TX United States Department of Computing Curtin University Australia

ISBN: (纸本)9781450300179

Social networking has recently flourished in popularity through the use of social websites. Pervasive computing resources have allowed people stay well-connected to each other through access to social networking resources. We take the position that utilizing information produced by relationships within social networks can assist in the establishment of trust for other pervasive computing applications. Furthermore, we describe how such a system can augment a sensor infrastructure used for event observation with information from mobile sensors (ie, mobile phones with cameras) controlled by potentially untrusted third parties. © 2010 ACM.

关键词： Ubiquitous computing

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Efficient PageRank and SpMV computation on AMD GPUs

Efficient PageRank and SpMV computation on AMD GPUs

引用

International Conference on Parallel Processing

作者： Wu, Tianji Wang, Bo Shan, Yi Yan, Feng Wang, Yu Xu, Ningyi Department of Electronic Engineering Tsinghua National Laboratory for Information Science and Technology Tsinghua University China Department of Computer Science Purdue University United States Hardware Computing Group Microsoft Researc Asia United States

ISBN: (纸本)9780769541563

Google's famous PageRank algorithm is widely used to determine the importance of web pages in search engines. Given the large number of web pages on theWorld Wide web, efficient computation of PageRank becomes a challenging problem. We accelerated the power method for computing PageRank on AMD GPUs. The core component of the power method is the Sparse Matrix-Vector Multiplication (SpMV). Its performance is largely determined by the characteristics of the sparse matrix, such as sparseness and distribution of nonzero values. Based on careful analysis on the web linkage matrices, we design a fast and scalable SpMV routine with three passes, using a modified Compressed Sparse Row format. Our PageRank computation achieves 15x speedup on a Radeon 5870 Graphic Card compared with a PhenomII 965 CPU at 3.4GHz. Our method can easily adapt to large scale data sets. We also compare the performance of the same method on the OpenCL platform with our low-level implementation. ©2010 IEEE.

关键词： Graphics processing unit

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Leukemia cancer classification based on support vector machine

Leukemia cancer classification based on support vector machi...

引用

8th IEEE International Conference on Industrial Informatics, INDIN 2010

作者： Hsieh, Sung-Huai Wang, Zhenyu Cheng, Po-Hsun Lee, I-Shun Hsieh, Sheau-Ling Lai, Feipei Department of Computer Science and Information Engineering Providence University Taiwan Computing Laboratory Oxford University Oxford United Kingdom Department of Software Engineering National Kaohsiung Normal University Taiwan Department of Computer Science and Information Engineering National Taiwan University Taiwan Department of Electrical Engineering National Taiwan University Taipei Taiwan Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taiwan Network and Computer Centre National Chiao Tung University Hsin Chu Taiwan

ISBN: (纸本)9781424473007

In the paper, we classify cancer with the Leukemia cancer of medical diagnostic data. information gain has been adapted for feature selections. A Leukemia cnacer model that utilizes information Gain based on Support Vector Machines (IG-SVM) techniques and enhancements to evaluate, interpret the cacer classification. The experimental results indicate that the SVM model illustrates the highest accuracy of classifications for Leukemia cancer. © 2010 IEEE.

关键词： Support vector machines

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A translation framework for virtual execution environment on CPU/GPU architecture

A translation framework for virtual execution environment on...

引用

International Symposium on Parallel Architectures, Algorithms, and Programming

作者： Dong, Guoxing Chen, Kai Zhu, Erzhou Zhang, Yichao Qi, Zhengwei Guan, Haibing School of Software Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Jiaotong University Shanghai 200240 China School of Information Security Engineering Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Jiaotong University Shanghai 200240 China Department of Computer Science and Engineering Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Jiaotong University Shanghai 200240 China

ISBN: (纸本)9780769543123

GPUs are many-core processors with tremendous computational power. However, as automatic parallelization has not been realized yet, developing high-performance parallel code for GPUs is still very challenging. The paper presents a novel translation framework designed for virtual execution environment based on CPU/GPU architecture. It addresses two major challenges of taking advantage of general purpose computation on graphics processing units (GPGPU) to improve performance: no rewriting the existing source code and resolving binary compatibility issues between different GPUs. The translation framework uses semi-automatic parallelization technology to port existing code to explicitly parallel programming models. It not only offers a mapping strategy from X86 platform to CUDA programming model, but also synchronizes the execution between the CPU and the GPUs. The input to our translation framework is parallelizable part of the program within binary code. With an additional information related to the parallelizable part, the translation framework transforms the sequential code into PTX code and execute it on GPUs. Experimental results on several programs from CUDA SDK Code Samples and Parboil Benchmark Suite show that our translation framework could achieve very high performance, even up to several tens of times speedup over the X86 native version. © 2010 IEEE.

关键词： Graphics processing unit

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引用

2010 IEEE 5th International Conference on Bio-Inspired computing: Theories and Applications, BIC-TA 2010

作者： Zhang, Zhujin Wang, Shuo Zhang, Xingyi Zhang, Zheng Department of Control Science and Engineering Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China School of Computer and Information Science University of South Australia Adelaide SA 5095 Australia Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei 230039 China

ISBN: (纸本)9781424464388

Randí et al. proposed a significant graphical representation for DNA sequences, which is very compact and avoids loss of information. In this paper, we build a fast algorithm for this graphical representation with time complexity O(n2), and find another important advantage in the representation: no degeneracy. Moreover, we propose a new method to do similarity analysis of DNA sequences based on the representation. The approach adopts four elements of covariance matrix as a descriptor, and is illustrated on the first exon of beta-globin genes from 11 different species. © 2010 IEEE.

关键词： DNA sequences

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Efficient online trace building using code replication

Efficient online trace building using code replication

引用

International Conference on Grid and Cloud computing

作者： Deng, Haipeng Chen, Kai Liu, Bo He, Yunchao Zhou, Kan Yang, Yindong Liang, Alei Guan, Haibing School of Software Shanghai Jiao Tong University China Department of Computer Science and Engineering Shanghai Jiao Tong University China School of Information Security Engineering Shanghai Jiao Tong University China Shanghai Key Laboratory of Scalable Computing and Systems China

ISBN: (纸本)9780769543130

Hot trace building plays an important role in enhancing the performance of dynamic binary translators, since in most cases 10% of code takes 90% of execution time of the whole program. Hot traces can promote the code position to make better the locality of the code;therefore programs can achieve a better performance. Thus how to build qualified and long hot traces is the key point. Considering the situation when one single basic block is needed by more than two hot traces, code replication can help build hot traces with cost of expansion of code size. In this paper, a code replication method to help with building hot traces as well as code positioning is presented, and experiments have been done to evaluate the details of changes that code replication brings to the system, like trace fragment length, memory size expansion, etc. With this method, a performance promotion by 0.5%-3.5% against the original trace building method has been achieved. © 2010 IEEE.

关键词： Virtual machine

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Reactive Programming Optimizations in Pervasive computing

Reactive Programming Optimizations in Pervasive Computing

引用

Symposium on Applications and the Internet (SAINT)

作者： Chao Chen Yi Xu Kun Li Sumi Helal Mobile and Pervasive Computing Laboratory Computer & Information Science & Engineering Department University of Florida Gainesville FL USA

Pervasive computing systems are begging for programming models and methodologies specifically suited to the particular cyber-physical nature of these systems. Reactive (rule-based) programming is an attractive model to use due to its built-in safety features and intuitive application development style. Without careful optimization however, reactive programming engines could turn into monstrous power drains of the pervasive system and its sensor network. In this paper we propose two optimizations for reactivity engines. The first, which we prove to be optimal, assumes all sensors in the space are equally important to the application. The other, which is adaptive, employs and estimates a probability for each sensor based on application usage. Both optimizations use a mixed push/pull approach to achieve optimal or near optimal energy efficiency. We present an experimental evaluation of the two algorithms to quantify their performance over a range of parameters.

关键词： Engines Programming Optimization Computational modeling Middleware computer architecture Energy consumption

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Toward a Programming Model for Safer Pervasive Spaces

Toward a Programming Model for Safer Pervasive Spaces

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Symposia and Workshops on Ubiquitous, Autonomic and Trusted computing, UIC-ATC

作者： Chao Chen Sumi Helal Mobile and Pervasive Computing Laboratory Computer & Information Science & Engineering Department University of Florida Gainesville FL USA

This paper addresses issues of safety in pervasive spaces. We show how pervasive systems are different from traditional computer systems, and how their cyber-physical nature ties intimately with the users. Errors and conflicts in such space could have detrimental, dangerous or undesired effects on the user, the space, or the devices. There are no support systems or programming models conscious of the issue of safety. Unrestrained programming is the model de jour, which is inadequate. We need a programming model that encourages and obligates various roles engaged in the development of pervasive spaces to contribute to increasing safety. We propose a model that utilizes role-specific safety knowledge, and that takes advantage of the rich sensing and actuations capabilities of pervasive systems to detect and handle “conflicting contexts” and prevent or detect/avert“impermissible contexts”. We present our model and discus show it mitigates overall safety risks in presence of uncertainty due to multiple independent roles.

关键词： Safety Context Programming Ontologies Sensors Software Computational modeling

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Performance tuning towards a KVM-based low latency virtualization system

Performance tuning towards a KVM-based low latency virtualiz...

引用

2nd International Conference on information engineering and computer science, ICIECS 2010

作者： Zuo, Baojing Chen, Kai Liang, Alei Guan, Haibing Zhang, Jun Ma, Ruhui Yang, Hongbo School of Software Shanghai Jiao Tong University Shanghai 200240 China School of Information Security Engineering Shanghai Jiao Tong University Shanghai 200240 China Department of Computer Science and Engineering Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Jiao Tong University Shanghai 200240 China

ISBN: (纸本)9781424479412

Utilizing virtualization technology to combine real-time operating system (RTOS) and off-the-shelf time-sharing general purpose operating system (GPOS) is attracting much more interest recently. Such combination has the potential to provide a large application base, and to guarantee timely deterministic response to real-time applications, yet there is no convincible experimental result about its real-time property. In this paper, we analyze the interrupt latency of RTOS running on Linux KVM based on some preliminary tunings, and find out System Management Interrupt (SMI) is the main factor which makes the maximum latency unideal, so we propose a method to limit the worst-case interrupt latency in an acceptable interval. Furthermore, we also find out that boosting priority may result in wastes of CPU resources when RTOS is not executing real-time tasks, so we design a co-scheduling mechanism to improve the CPU throughput of the GPOS system. ©2010 IEEE.

关键词： Virtualization

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Efficient PageRank and SpMV Computation on AMD GPUs

Efficient PageRank and SpMV Computation on AMD GPUs

引用

International Conference on Parallel Processing (ICPP)

作者： Tianji Wu Bo Wang Yi Shan Feng Yan Yu Wang Ningyi Xu Department of Electronic Engineering Tsinghua National Laboratory of Information Science and Technology Tsinghua University China Department of Computer Science Purdue University USA Hardware Computing Group Microsoft Research Asia China

Google's famous PageRank algorithm is widely used to determine the importance of web pages in search engines. Given the large number of web pages on the World Wide web, efficient computation of PageRank becomes a challenging problem. We accelerated the power method for computing PageRank on AMD GPUs. The core component of the power method is the Sparse Matrix-Vector Multiplication (SpMV). Its performance is largely determined by the characteristics of the sparse matrix, such as sparseness and distribution of non-zero values. Based on careful analysis on the web linkage matrices, we design a fast and scalable SpMV routine with three passes, using a modified Compressed Sparse Row format. Our PageRank computation achieves 15x speedup on a Radeon 5870 Graphic Card compared with a PhenomII 965 CPU at 3.4GHz. Our method can easily adapt to large scale data sets. We also compare the performance of the same method on the OpenCL platform with our low-level implementation.

关键词： Instruction sets Sparse matrices Couplings Graphics processing unit Hardware web pages

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