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An Alternative Sensor Cloud Architecture for Vital Signs Monitoring

An Alternative Sensor Cloud Architecture for Vital Signs Mon...

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International Joint Conference on Neural Networks

作者： Sara Ghanavati Jemal Abawajy Davood Izadi Parallel and Distributed Computing Lab School of Information Technology Deakin University Geelong Australia

ISBN: (纸本)9781509006212

Due to recent technological advancements in wireless communications and low-power sensor devices, wireless body area networks (WBANs) has become increasingly popular in pervasive healthcare monitoring. However, continuously collecting patients' physiological signs will result in large amounts of monitored data that require a scalable architecture for storage and analysis. This fact motivates the integration of WBANs with Cloud technology to manage and store humongous data effectively. In this paper, we propose a Cloud-based WBAN framework for real-time health monitoring of patients. The significance of the proposed framework is the use of mobile technology and Cloud computing to provide services for the ill and elderly people in their independent living. This paper describes the general design of the proposed approach as well as a case study and implementation setup for the real-time monitoring and analysis process of Electromyography (EMG) healthcare system.

关键词： Cloud computing Monitoring Medical services Wireless communication Body area networks Biomedical monitoring Real-time systems

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Efficient Detection Of SQL Injection Attack(SQLIA) Using Pattern-based Neural Network Model

Efficient Detection Of SQL Injection Attack(SQLIA) Using Pat...

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International Conference on computing, Communication, and Intelligent Systems (ICCCIS)

作者： Meharaj Begum A Michael Arock Bio-informatics and Parallel Computing Lab National Institute of Technology Trichy Tamilnadu India

ISBN: (数字)9781728185293

ISBN: (纸本)9781728185309

Web application vulnerability is one of the major causes of cyber attacks. Cyber criminals exploit these vulnerabilities to inject malicious commands to the unsanitized user input in order to bypass authentication of the database through some cyber-attack techniques like cross site scripting (XSS), phishing, Structured Query Language Injection Attack (SQLIA), malware etc., Although many research works have been conducted to resolve the above mentioned attacks, only few challenges with respect to SQLIA could be resolved. Ensuring security against complete set of malicious payloads are extremely complicated and demanding. It requires appropriate classification of legitimate and injected SQL commands. The existing approaches dealt with limited set of signatures, keywords and symbols of SQL queries to identify the injected queries. This work focuses on extracting SQL injection patterns with the help of existing parsing and tagging techniques. Pattern-based tags are trained and modeled using Multi-layer Perceptron which significantly performs well in classification of queries with accuracy of 94.4% which is better than the existing approaches.

关键词： Structured Query Language Computational modeling Phishing SQL injection Tagging Security Payloads

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Clique guided community detection

Clique guided community detection

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IEEE International Conference on Big Data

作者： Diana Palsetia Md. Mostofa Ali Patwary William Hendrix Ankit Agrawal Alok Choudhary Northwestern University Evanston IL Parallel Computing Lab Intel Santa Clara CA

Discovering communities to understand and model network structures has been a fundamental problem in several fields including social networks, physics, and biology. Many algorithms have been developed for finding the communities. Modularity based technique is fairly new relative to clustering, though it is very popular currently. Although some fast modularity based algorithms exist for detecting communities, the quality of these solutions is limited. At the other extreme, a clique embodies a basic community as it has the greatest possible edge density. However, the requirement that each pair of vertices be connected is too strict. Therefore, techniques to merge partitioned cliques using a hill-climbing greedy algorithm have been studied to form communities. However, the task of finding cliques is computationally expensive. In this paper, we present a new approach for fast and efficient community detection. We propose a clique guided community detection framework that consists of two phases. In the first phase, the framework finds disjoint cliques. In the second phase, the cliques from the first phase are used to guide the merging of individual vertices until a good quality solution is obtained. For the first phase, we develop an algorithm named MaCH (Maximum Clique Heuristic), which is a new approach to compute disjoint cliques using a heuristic-based branch-and-bound technique. We provide experimental results to demonstrate the efficiency of the new algorithm and compare our approach with other previously proposed algorithms.

关键词： Communities Heuristic algorithms Merging Partitioning algorithms Clustering algorithms Approximation algorithms

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Eliminating Irregularities of Protein Sequence Search on Multicore Architectures

Eliminating Irregularities of Protein Sequence Search on Mul...

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International Symposium on parallel and Distributed Processing (IPDPS)

作者： Jing Zhang Sanchit Misra Hao Wang Wu-chun Feng Dept. of Computer Science Virginia Tech Parallel Computing Lab Intel Corporation

Finding regions of local similarity between biological sequences is a fundamental task in computational biology. BLAST is the most widely-used tool for this purpose, but it suffers from irregularities due to its heuristic nature. To achieve fast search, recent approaches construct the index from the database instead of the input query. However, database indexing introduces more challenges in the design of index structure and algorithm, especially for data access through the memory hierarchy on modern multicore processors. In this paper, based on existing heuristic algorithms, we design and develop a database indexed BLAST with the identical sensitivity as query indexed BLAST (i.e., NCBI-BLAST). Then, we identify that existing heuristic algorithms of BLAST can result in serious irregularities in database indexed search. To eliminate irregularities in BLAST algorithm, we propose muBLASTP, that uses multiple optimizations to improve data locality and parallel efficiency for multicore architectures and multi-node systems. Experiments on a single node demonstrate up to a 5.1-fold speedup over the multi-threaded NCBI BLAST. For the inter-node parallelism, we achieve nearly linear scaling on up to 128 nodes and gain up to 8.9-fold speedup over mpiBLAST.

关键词： Indexes Multicore processing Heuristic algorithms Protein sequence Tools

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Sparse Tensor Factorization on Many-Core Processors with High-Bandwidth Memory

Sparse Tensor Factorization on Many-Core Processors with Hig...

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International Symposium on parallel and Distributed Processing (IPDPS)

作者： Shaden Smith Jongsoo Park George Karypis Department of Computer Science and Engineering University of Minnesota Parallel Computing Lab Intel Corporation

HPC systems are increasingly used for data intensive computations which exhibit irregular memory accesses, non-uniform work distributions, large memory footprints, and high memory bandwidth demands. To address these challenging demands, HPC systems are turning to many-core architectures that feature a large number of energy-efficient cores backed by high-bandwidth memory. These features are exemplified in Intel's recent Knights Landing many-core processor (KNL), which typically has 68 cores and 16GB of on-package multi-channel DRAM (MCDRAM). This work investigates how the novel architectural features offered by KNL can be used in the context of decomposing sparse, unstructured tensors using the canonical polyadic decomposition (CPD). The CPD is used extensively to analyze large multi-way datasets arising in various areas including precision healthcare, cybersecurity, and e-commerce. Towards this end, we (i) develop problem decompositions for the CPD which are amenable to hundreds of concurrent threads while maintaining load balance and low synchronization costs; and (ii) explore the utilization of architectural features such as MCDRAM. Using one KNL processor, our algorithm achieves up to 1.8x speedup over a dual socket Intel Xeon system with 44 cores.

关键词： Tensile stress Instruction sets Synchronization Sparse matrices parallel processing Bandwidth

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Grid and Cooperative computing - GCC 2004 1

引用

丛书名： Lecture Notes in Computer Science

1000年

作者： Hai Jin Yi Pan Nong Xiao Jianhua Sun

ISBN: (数字)9783540302087

ISBN: (纸本)9783540235644

Welcome to the proceedings of GCC2004 and the city of Wuhan. Grid computing has become a mainstream research area in computer science and the GCC conference has become one of the premier forums for presentation of new and exciting research in all aspectsofgridandcooperativecomputing. Theprogramcommitteeispleasedtopresent the proceedings of the 3rd International Conference on Grid and Cooperative Comp- ing (GCC2004), which comprises a collection of excellent technical papers, posters, workshops, and keynote speeches. The papers accepted cover a wide range of exciting topics, including resource grid and service grid, information grid and knowledge grid, grid monitoring,managementand organizationtools, grid portal, grid service, Web s- vices and their QoS, service orchestration, grid middleware and toolkits, software glue technologies, grid security, innovative grid applications, advanced resource reservation andscheduling,performanceevaluationandmodeling,computer-supportedcooperative work, P2P computing, automatic computing, and meta-information management. The conference continues to grow and this year a record total of 581 manuscripts (including workshop submissions) were submitted for consideration. Expecting this growth, the size of the program committee was increased from 50 members for GCC 2003 for 70 in GCC 2004. Relevant differences from previous editions of the conf- ence: it is worth mentioning a signi?cant increase in the number of papers submitted by authors from outside China; and the acceptance rate was much lower than for p- vious GCC conferences. From the 427 papers submitted to the main conference, the program committee selected only 96 regular papers for oral presentation and 62 short papers for poster presentation in the program.

关键词： Theory of Computation Computer Communication Networks Operating Systems Software Engineering Information Systems Applications (incl. Internet) Information Storage and Retrieval

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Exploring Shared-Memory Optimizations for an Unstructured Mesh CFD Application on Modern parallel Systems

Exploring Shared-Memory Optimizations for an Unstructured Me...

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International Symposium on parallel and Distributed Processing (IPDPS)

作者： Dheevatsa Mudigere Srinivas Sridharan Anand Deshpande Jongsoo Park Alexander Heinecke Mikhail Smelyanskiy Bharat Kaul Pradeep Dubey Dinesh Kaushik David Keyes Parallel Computing Lab Intel Corporation Bangalore India Parallel Computing Lab Intel Corporation Santa Clara CA Qatar Foundation Doha Qatar King Abdullah University of Science and Technology Thuwal Saudi Arabia

ISBN: (纸本)9781479986507

In this work, we revisit the 1999 Gordon Bell Prize winning PETSc-FUN3D aerodynamics code, extending it with highly-tuned shared-memory parallelization and detailed performance analysis on modern highly parallel architectures. An unstructured-grid implicit flow solver, which forms the backbone of computational aerodynamics, poses particular challenges due to its large irregular working sets, unstructured memory accesses, and variable/limited amount of parallelism. This code, based on a domain decomposition approach, exposes tradeoffs between the number of threads assigned to each MPI-rank sub domain, and the total number of domains. By applying several algorithm- and architecture-aware optimization techniques for unstructured grids, we show a 6.9X speed-up in performance on a single-node Intel® XeonTM1 E5 2690 v2 processor relative to the out-of-the-box compilation. Our scaling studies on TACC Stampede supercomputer show that our optimizations continue to provide performance benefits over baseline implementation as we scale up to 256 nodes.

关键词： Optimization Kernel parallel processing Jacobian matrices Computational fluid dynamics Instruction sets Sparse matrices

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Study of a Code Comment Decision Method Based on Structural Features

Study of a Code Comment Decision Method Based on Structural ...

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International Conference on Intelligent computing, Automation and Systems (ICICAS)

作者： Renmin Wang Tao Wang Huaimin Wang Key Lab. of Parallel and Distributed Computing National University of Defense Technology Changsha China

ISBN: (数字)9781728161068

ISBN: (纸本)9781728161075

Code comment is one of the most effective ways to help programmers to understand the source code. High-quality comment decisions can not only cover the core code snippets in the software system but also avoid generating redundant code comments. However, in actual development, there is no uniform comment specification, and most of the comment decisions depend on personal experience and domain knowledge. This paper has learned a common comment decision specification from a large number of code comment examples to assist programmers in making appropriate comment decisions during code development. This paper proposes a method to extract the code structure from the context code of the current code line, and use the machine learning algorithm to determine the possibility that the current code needs to add comments. The proposed method was evaluated on 8 well-known open-source Python projects in GitHub and the experimental results show the feasibility and effectiveness of the method in some code types.

关键词： decision making feature extraction knowledge acquisition learning (artificial intelligence) public domain software software engineering system documentation program and system documentation open source software Information Extraction Comment Software engineering Codes Feature extraction Computer personnel Structural properties Software systems Machine learning algorithms decision making

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To INT_MAX... and Beyond! Exploring Large-Count Support in MPI

To INT_MAX... and Beyond! Exploring Large-Count Support in M...

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Workshop on Exascale MPI at Supercomputing Conference (ExaMPI)

作者： Jeff R. Hammond Andreas Schäfer Rob Latham Parallel Computing Lab Intel Corp Friedrich-Alexander-Universität Erlangen-Nürnberg

In order to describe a structured region of memory, the routines in the MPI standard use a (count, datatype) pair. The C specification for this convention uses an int type for the count. Since C int types are nearly always 32 bits large and signed, counting more than 231 elements poses a challenge. Instead of changing the existing MPI routines, and all consumers of those routines, the MPI Forum asserts that users can build up large datatypes from smaller types. To evaluate this hypothesis and to provide a user-friendly solution to the large-count issue, we have developed BigMPI, a library on top of MPI that maps large-count MPI-like functions to MPI-3 standard features. BigMPI demonstrates a way to perform such a construction, reveals shortcomings of the MPI standard, and uncovers bugs in MPI implementations.

关键词： Vectors Standards Libraries Optimization Context Memory management Open area test sites

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High Performance Emulation of Quantum Circuits 16

High Performance Emulation of Quantum Circuits

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Supercomputing Conference

作者： Thomas Häner Damian S. Steiger Mikhail Smelyanskiy Matthias Troyer ETH Zurich Institute for Theoretical Physics Zurich Switzerland Parallel Computing Lab Intel Corporation

ISBN: (纸本)9781467388153

As quantum computers of non-trivial size become available in the near future, it is imperative to develop tools to emulate small quantum computers. This allows for validation and debugging of algorithms as well as exploring hardware-software co-design to guide the development of quantum hardware and architectures. The simulation of quantum computers entails multiplications of sparse matrices with very large dense vectors of dimension 2n, where n denotes the number of qubits, making this a memory-bound and network bandwidth-limited application. We introduce the concept of a quantum computer emulator as a component of a software framework for quantum computing, enabling a significant performance advantage over simulators by emulating quantum algorithms at a high level rather than simulating individual gate operations. We describe various optimization approaches and present benchmarking results, establishing the superiority of quantum computer emulators in terms of performance.

关键词： Quantum computing Logic gates Computers Computational modeling Emulation Sparse matrices Optimization

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