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A Framework for Real-Time Information Derivation from Big Sensor Data

A Framework for Real-Time Information Derivation from Big Se...

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IEEE international symposium on Cyberspace Safety and Security

作者： Liehuo Chen Kyoung-Don Kang Dept. of Comput. Sci. State Univ. of New York at Binghamton Binghamton NY USA

ISBN: (纸本)9781479989386

In data-intensive real-time applications, e.g., transportation management and location-based services, the amount of sensor data is exploding. In these applications, it is desirable to extract value-added information, e.g., fast driving routes, from sensor data streams in real-time rather than overloading users with massive raw data. However, achieving the objective is challenging due to the data volume and complex data analysis tasks with stringent timing constraints. Most existing big data management systems, e.g., Hadoop, are not directly applicable to real-time sensor data analytics, since they are timing agnostic and focus on batch processing of previously stored data that are potentially outdated and subject to I/O overheads. To address the problem, we design a new real-time big data management framework, which supports a non-preemptive periodic task model for continuous in-memory sensor data analysis and a schedulability test based on the EDF (Earliest Deadline First) algorithm to derive information from current sensor data in real-time by extending the map-reduce model originated in functional programming. As a proof-of-concept case study, a prototype system is implemented. In the performance evaluation, it is empirically shown that all deadlines can be met for the tested sensor data analysis benchmarks.

关键词： Big Data batch processing (computers) data analysis functional programming parallel processing performance evaluation EDF algorithm I/O overheads batch processing complex data analysis tasks continuous in-memory sensor data analysis data volume data-intensive real-time applications earliest deadline first algorithm nonpreemptive periodic task model real-time big data management framework real-time information derivation real-time sensor big data analytics schedulability test stringent timing constraints timing agnostic value-added information extraction Analytical models Big data Data analysis Data models Mobile radio mobility management Real-time systems Timing Big Sensor Data Real-Time Information

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Join sequence optimization in parallel query plans

Join sequence optimization in parallel query plans

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international Workshop on Database and Expert Systems Applications

作者： U.J. Langer H.F. Meyer CS Department University of Rostock Rostock Germany

We show an alternative way to optimize join sequences in a shared nothing architecture of the distributed relational DBMS HEAD. the hardware resources are also used for database independent applications in concurrency, for database access. To achieve a better hardware utilization we span a complete search space involving all intermediate shapes between left deep, right deep and bushy trees, but without join sequences including cartesian products. the approach is based on any combinatorial search engine and a complex cost function. the cost function involves the actual load of the processors, the network load, and the memory capacities. the new technique has free access to any join sequence in the whole search space. the approach is not restricted to acyclic join conditions.

关键词： Shape Hardware Relational databases Cost function Tree graphs parallel processing Workstations Concurrent computing Search engines Optimization methods

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Constructing a Mobility and Acceleration computing Platform with NVIDIA Jetson TK1

Constructing a Mobility and Acceleration Computing Platform ...

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IEEE international symposium on Cyberspace Safety and Security

作者： Min Su Jianjun Tan Chun-Yuan Lin Jin Ye Chung-Hung Wang Che-Lun Hung College of Life Science and Bioengineering Beijing University of Technology Department of Computer Science and Information Engineering Chang Gung University Department of Computer Science and Communication Engineering Providence University

ISBN: (纸本)9781479989386

Current high-end graphics processing units (GPUs), which contain up to thousand cores per-chip, are widely used in the high performance computing community. However, in the past, the cost and power consumption of constructing a high performance platform with graphics cards, such as Tesla and Fermi series, are high. Moreover, these graphics cards all installed in personal computers or servers, and then the immediate and mobility requirements can not be provided by this platform. NVIDIA Jetson TK1 (Tegra K1) is a full-featured platform for embedded applications and it contains 192 CUDA Cores (Kepler CPU). Due to its low cost, low power consumption and high applicability, NVIDIA Jetson TK1 has become a new research direction. In this paper, we construct a mobility and acceleration computing platform with NVIDIA Jetson TK1. Besides, two tools, ClustalWtk and MCCtk are designed based on NVIDIA Jetson TK1. these tools both can achieve 3 and 4 times speedup ratios on single NVIDIA Jetson TK1 by comparing with their CPU versions on Intel XEON E5-2650 CPU and ARM Cortex-A15 CPU, respectively. Moreover, the cost-performance ratio by NVIDIA Jetson TK1 is higher than that by NVIDIA Tesla K20m. In addition, the user friendly interfaces are also provided by these two tools, respectively.

关键词： NVIDIA Jetson TK1 CUDA Mutliple Sequence Alginment Compound Comparison parallel Processing

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Adaptive Phase Synchronisation Algorithm for Collaborative Beamforming in Wireless Sensor Networks

Adaptive Phase Synchronisation Algorithm for Collaborative B...

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Asia international Conference on Modeling & Simulation

作者： Chen How Wong Zhan Wei Siew Renee Ka Yin Chin Aroland Kiring Kenneth Tze Kin Teo Modelling Simulation & Computing Laboratory Universiti Malaysia Sabah Kota Kinabalu Malaysia Universiti Malaysia Sabah Kota Kinabalu Sabah MY

Collaborative beam forming (CB) is a cooperative technique that utilizes a group of distributed wireless nodes to collectively transmit a common message with proper phase weights to an intended direction. As a result, CB significantly extends the communication range of the sensor node in wireless sensor networks (WSNs). Each sensor node in CB has an independent local oscillator. It becomes a vital problem to achieve CB as the distributed nodes are unaware of their phase relationship. therefore, an efficient phase synchronisation algorithm is needed as the distributed nodes are unaware of their phase relationship. In this paper, an iterative phase synchronisation algorithm using (1+1)-evolution strategy (ES) is proposed to achieve CB in WSNs. Evaluations have been carried out through simulation and the results show that the proposed algorithm is more energy efficient in comparison to the existing phase synchronisation algorithm.

关键词： Synchronization Array signal processing Receivers Wireless sensor networks Simulation Algorithm design and analysis Radiation detectors

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Local parallelization of pleasingly parallel stream processing on multiple CPU cores

Local parallelization of pleasingly parallel stream processi...

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international Conference and Workshop on computing and Communication (IEMCON)

作者： Ruediger Gad Martin Kappes Inmaculada Medina-Bulo Terma GmbH Space Darmstadt Germany Frankfurt University of Applied Sciences Frankfurt am Main Germany Universidad de Cádiz Cádiz Spain

ISBN: (纸本)9781509009978

Data stream processing addresses the need for high-throughput near real-time data processing, which can be considered as one part of Big Data or Fast Data. In this paper, we study the local parallelization of stream processing on a single multi-core Central Processing Unit (CPU) computer system, which, in our opinion, was not sufficiently addressed yet. In distributed systems, optimizing the local throughput can help to improve the overall system. In less resource demanding scenarios, it may be beneficial to use more lightweight local parallelization instead of more complex distributed approaches. We present our work-in-progress on locally parallelizing stream processing on multiple CPU cores and on ways for further improving the local data processing. In order to study the fundamental mechanisms and effects, we focused on pleasingly parallel workloads. While pleasingly parallel tasks, by definition, can be easily parallelized, our results show that stream processing adds important aspects and that the outcomes strongly vary depending on use case and parallelization approach. Furthermore, we present early stages of a stream transformation Domain Specific Language and of a self-adaptive mechanism for easing and optimizing the processing. We published our implementations as Open Source Software.

关键词： Pipelines Data processing throughput Central Processing Unit DSL parallel processing Concurrent computing

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Real-time parallel Computation of Core thermal Hydraulic based on Sub-channel Model for a Pressurized Water Reactor

Real-time Parallel Computation of Core Thermal Hydraulic bas...

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the second international symposium on Socially and Technically Symbiotic Systems (STSS2015);the 7th international symposium on Symbiotic Nuclear Power Systems (ISSNP2015)

作者： WANG Ya-feng TIAN Zhao-fei LI Lei CHENG Guang-liang Fundamental Science on Nuclear Safety and Simulation Technology Laboratory College of Nuclear Science and TechnologyHarbin Engineering University

Using the reactor core as the simulation object,considering coolant mass and energy exchange effect between adjacent sub-channels,a real time sub-channel thermal hydraulic evaluation and analysis program at a Chinese PWR( Qinshan phase two) core is *** aim of thermal hydraulic characteristics research about reactor core is ***,due to the complexity flow characteristics of core coolant,and heavy task of the numerical calculation,so that the requirements in high precision and real-time simulation can't be ***,using parallel computing is one of the most effective methods at *** aim of the paper is to solve the problem of computation resource constraints in the traditional numerical calculation and low calculation efficiency with the stable,efficient parallel environment through parallel programming language,so that the high efficiency of parallel computing code and environment were actualized.

关键词： thermal hydraulic sub-channel real-time simulation parallel computation MPI

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Using Artificial Neural Network for Predicting thread Partitioning in Speculative Multithreading

Using Artificial Neural Network for Predicting Thread Partit...

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IEEE international Conference on High Performance computing and Communications (HPCC)

作者： Yuxiang Li Yinliang Zhao Huan Gao Engineering Xi'an Jiaotong University Xi'an China

ISBN: (纸本)9781479989386

Speculative multithreading (SpMT) is a thread-level automatic parallelization technique to accelerate sequential programs on multi-core, and it partitions programs into multiple threads to be speculatively executed in the presence of ambiguous data and control dependences while the correctness of the programs is guaranteed by hardware support. thread granularity, number of parallel threads as well as partition postions are crucial to the performance improvement in SpMT, for they determine the amount of resources (CPU, memory, cache, or waiting cycles, etc), and affect the efficiency of every PE (Processing Element). In conventional way, these three parameters are determined by heuristic rules. Although it is simple to partition threads with them, they are a type of one-size-fits-all strategy and can not guarantee to get the optimal solution of thread partitioning. this paper proposes an Artificial Neural Network (ANN) based approach to learn and determine the thread partition strategy. Using the ANN-based thread partition approach, an unseen irregular program can obtain a stable, much higher speedup than the Heuristic Rules (HR) based approach. On Prophet, which is a generic SpMT processor to evaluate the performance of multithreaded programs, the novel thread partitioning policy is evaluated and reaches an average speedup of 1.80 on 4-core processor. Experiments show that our proposed approach can obtain a significant increase in speedup and Olden benchmarks deliver a better performance improvement of 2.36% than the traditional heuristic rules based approach. the results indicate that our approach finds the best partitioning scheme for each program and is more stable across programs.

关键词： Conferences High performance computing Cyberspace Safety Security Cascading style sheets Embedded software

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Design and implementation of parallel JiST to support distributed wireless network simulation

Design and implementation of parallel JiST to support distri...

引用

international symposium on High Capacity Optical Networks and Enabling Technologies, HONET

作者： Michael Slavik Imad Mahgoub Ahmed Badi Mohammad Ilyas Department of Computer Science and Engineering Florida Atlantic University Boca Raton FL USA

JiST/SWANS is a wireless network simulator gaining increasing popularity for ad-hoc wireless, wireless sensor network, and vehicular network evaluations. Typical published results using this tool show node counts on the order of hundreds of nodes. However, realistic sensor and vehicular networks may contain many more nodes than that. One reason for this discrepancy is the computational cost of evaluation via simulation. Currently, cluster computers are becoming preferred over expensive multi-processor supercomputers for improving computational output. We present the design and implementation of a parallelization of JiST, the discrete event simulator core of JiST/SWANS. JiST uses unique dynamic byte-code rewriting to simplify the development of applications and has been shown to perform well running small- or medium-scale wireless network simulations on single processor systems. We propose an optimistic cluster-based architecture and apply it to JiST. Simulation entity memory is distributed evenly across all nodes in the cluster, resulting in linear memory growth. Details of the simulation engine including the complex event execution synchronization are hidden entirely from the application, easing development and debug time. Since JiST is the simulation backend of the SWANS wireless network simulator, this result is the first step in simulating large networks using SWANS in reasonable periods of time. Results presented show the performance of our parallelization of JiST is in line with the performance of other existing parallel discrete event simulators.

关键词： Synchronization Computational modeling Java Wireless networks Kernel Computer architecture Ad hoc networks

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False Discovery Rates in Identifying Functional DNA Motifs

False Discovery Rates in Identifying Functional DNA Motifs

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IEEE symposium on Bioinformatics and Bioengineering (BIBE)

作者： Osman Abul Geir Kjetil Sandve Finn Drablos Department of Computer Engineering TOBB University of Economics and Technology Ankara Turkey Department of Computer and Information Science Norwegian University of Science and Technology Trondheim Norway Department of Cancer Research and Molecular Medicine Norwegian University of Science and Technology Trondheim Norway

there are several methods for scoring a set of upstream DNA sequences against a given motif. Typically, significance of raw scores are based on p-values, measured by statistical hypothesis testing. As an extension, multiple hypothesis testing is adopted in cases where there are multiple motifs to be evaluated in parallel. In this way significant motifs are identified for a given significance level. However, a set of significantly identified motifs can contain false positives. In this work, we introduce a false discovery rate estimation problem for significantly predicted motifs. An explorative method for this problem is presented. We test the method using TRANSFAC and JASPAR motif libraries on several upstream DNA subsets of ***. the results show the effectiveness of the method.

关键词： Testing Libraries Sequences DNA computing Power generation economics Cancer Information science Medical tests In vivo Optimization methods

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the GPU on biomedical image processing for color and phenotype analysis

The GPU on biomedical image processing for color and phenoty...

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IEEE symposium on Bioinformatics and Bioengineering (BIBE)

作者： Antonio Ruiz Manuel Ujaldon Jose Antonio Andrades Jose Becerra Kun Huang Tony Pan Joel Saltz Computer Architecture Department ETSI Informática University of Malaga Malaga Spain Cell Biology Genetics and Phisiology Department Faculty of Sciences University of Malaga Malaga Spain Biomedical Informatics Department Ohio State Uinversity Columbus OH USA

the computational power and memory bandwidth of graphics processing units (GPUs) have turned them into attractive platforms for general-purpose applications. In this paper, we exploit this power in the context of biomedical image processing by establishing a cooperative environment between the CPU and the GPU. We deal with phenotype and color analysis on a wide variety of microscopic images from studies of cartilage and bone tissue regeneration using stem cells and genetics involving cancer pathology. Both processors are used in parallel to map algorithms for computing color histograms, contour detection using the Canny filter and pattern recognition based on the Hough transform. Task, data and instruction parallelism are exploited in the GPU to accomplish performance gains between 4times and 100times more than the typical CPU code.

关键词： Image color analysis Biomedical image processing Image analysis Central Processing Unit Biomedical computing Bandwidth Graphics Microscopy Bone tissue Stem cells

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