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Multi-core Supported High Performance Security Analytics

Multi-core Supported High Performance Security Analytics

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ieee International symposium on Dependable, Autonomic and Secure Computing (DASC)

作者： Feng Cheng Amir Azodi David Jaeger Christoph Meinel Universitat Potsdam Potsdam Brandenburg DE Hasso Plattner Institute (HPI) University of Potsdam Potsdam Germany

Such information as system and application logs as well as the output from the deployed security measures, e.g., IDS alerts, firewall logs, scanning reports, etc., is important for the administrators or security operators to be aware at first time of the running state of the system and take efforts if necessary. In this context, high performance security analytics is proposed to address the challenges to rapidly gather, manage, process, and analyze the large amount of real-time information generated from the large scale of enterprise IT-Infrastructure while it is being operated. As an example of next generation Security Information and Event Management (SIEM) platform, Security Analytics Lab (SAL) has been designed and implemented based on the newly emerged In-Memory data management technique, which makes it possible to efficiently organize and access different types of event information through a consistent central storage and interface. To correlate the information from different sources and identify the meaningful information is another challenging task, which makes great sense for quickly judging the current situation and making the decision. In this paper, the multi-core processing technique is introduced in the SAL platform. Various correlation algorithms, e.g., k-means based algorithms, ROCK and QROCK clustering algorithms, have been implemented and integrated in the multi-core supported SAL architecture. Practical experiments are conducted and analyzed to proof that the performance of analytics can be significantly improved by applying multi-core processing technique in SAL.

关键词： Correlation Clustering algorithms Computer architecture Security parallel processing Algorithm design and analysis graphics processing units

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Performance Study of SIMD Programming Models on Intel Multicore Processors

Performance Study of SIMD Programming Models on Intel Multic...

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26th ieee International parallel and Distributed Processing symposium (IPDPS) / Workshop on High Performance data Intensive Computing

作者： Kristof, Peter Yu, Hongtao Li, Zhiyuan Tian, Xinmin Purdue Univ Dept Comp Sci W Lafayette IN 47906 USA Intel Corp Mobile Comp & Compilers Santa Clara CA USA

ISBN: (纸本)9780769546766

Modern multicore hardware employs a variety of parallel execution units, including multiple CPU cores for executing multiple threads simultaneously, vector units such as the Intel SIMD on the CPU cores, as well as GPU-like processing arrays. Availability of such unprecedented level of parallelism on main-stream computers offers an enormous potential to enable a new generation of computation-intensive nontraditional applications. On the other hand, how to best harness the hardware parallelism presents a new challenge to application programmers, language designers and compiler developers. In this paper, we evaluate the impact of several different parallel execution models, especially the new SIMD vectorization methods, supported by the latest Intel ICC compiler (version 12.1), using three computation-intensive nontraditional parallel applications as the test workload. Unlike traditional numerical programs, these applications use highly irregular data structures and therefore present nontrivial challenges to effective use of SIMD vector units. The first application is a game engine architecture requiring real-time performance. The second application involves a kd-tree traversal, which is typical to the state-of-the-art 3D ray-tracing applications. The last application processes data for large-scale weather visualization system in the order of tens of minutes. We compare the execution time of these codes using different SIMD models supported by ICC in conjunction with parallel threading under TBB and OpenMP.

关键词： Intel ICC compiler parallel programming SIMD optimization computer graphics

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Redirecting research in large-format displays for visualization

Redirecting research in large-format displays for visualizat...

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2nd symposium on large-Scale data Analysis and visualization, LDAV 2012

作者： Moreland, Kenneth

ISBN: (纸本)9781467347334

large-format displays, in particular tiled displays, remain actively used and researched today after almost two decades since their conception. Many government, academic, and commercial entities have invested considerably in the construction and use of large-format displays. During this time we have developed new applications but have also discovered faulty assumptions. This position paper evaluates the most important lessons learned from early and recent research in large-format displays. Each lesson suggests a direction for future research, which generally takes the form of a more user- and application-centric focus. © 2012 ieee.

关键词： large format DISPLAYING visualization redirection

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parallel IMPLEMENTATION OF VERTEX COMPONENT ANALYSIS FOR HYPERSPECTRAL ENDMEMBER EXTRACTION

PARALLEL IMPLEMENTATION OF VERTEX COMPONENT ANALYSIS FOR HYP...

引用

ieee International Geoscience and Remote Sensing symposium (IGARSS)

作者： Rodriguez Alves, Jose M. Nascimento, Jose M. P. Bioucas-Dias, Jose M. Silva, Vitor Plaza, Antonio Inst Telecomunicacoes Lisbon Portugal

ISBN: (纸本)9781467311595

Vertex component analysis (VCA) has become a very popular and useful tool to linear unmix large hyperspectral datasets without the use of any a priori knowledge of the constituent spectra. Although VCA is fast method, many hyperspectral imagery applications require a response in real time or near-real time. This paper proposes two different optimizations for accelerating the computational performance of VCA: the first one focus a parallel implementation based on graphics computing units (GPUs) to alleviate the VCA computational burden;The second one is focused on the development of a strategy to remove a large proportion of mixed pixels that play no effect on the VCA functioning. Experiments are conducted using simulated and real hyperspectral datasets. These results reveal considerable acceleration factors, which satisfies the real-time constraints given by the data acquisition rate.

关键词： Hyperspectral Unmixing Endmember Extraction Vertex Component Analysis graphics Processing Unit parallel Methods

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Integrated parallelization of Computations and visualization for large-scale Applications

Integrated Parallelization of Computations and Visualization...

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26th ieee International parallel and Distributed Processing symposium (IPDPS) / Workshop on High Performance data Intensive Computing

作者： Malakar, Preeti Natarajan, Vijay Vadhiyar, Sathish S. Indian Inst Sci Dept Comp Sci & Automat Bangalore 560012 Karnataka India Supercomp Educ & Res Ctr Bangalore Karnataka India

ISBN: (纸本)9780769546766

Critical applications like cyclone tracking and earthquake modeling require simultaneous high-performance simulations and online visualization for timely analysis. Faster simulations and simultaneous visualization enable scientists provide real-time guidance to decision makers. In this work, we have developed an integrated user-driven and automated steering framework that simultaneously performs numerical simulations and efficient online remote visualization of critical weather applications in resource-constrained environments. It considers application dynamics like the criticality of the application and resource dynamics like the storage space, network bandwidth and available number of processors to adapt various application and resource parameters like simulation resolution, simulation rate and the frequency of visualization. We formulate the problem of finding an optimal set of simulation parameters as a linear programming problem. This leads to 30% higher simulation rate and 25-50% lesser storage consumption than a naive greedy approach. The framework also provides the user control over various application parameters like region of interest and simulation resolution. We have also devised an adaptive algorithm to reduce the lag between the simulation and visualization times. Using experiments with different network bandwidths, we find that our adaptive algorithm is able to reduce lag as well as visualize the most representative frames.

关键词： visualization simulating Simulation parameter Adaptive algorithms Criticality Affection parallelization

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MaTSE: The microarray time-series explorer

MaTSE: The microarray time-series explorer

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2nd ieee symposium on Biological data visualization, BioVis 2012

作者： Craig, Paul Cannon, Alan Kukla, Robert Kennedy, Jessie Universidad Technológica de la Mixteca Mexico Edinburgh Napier University United Kingdom

ISBN: (纸本)9781467347303

This paper describes the design, development and evaluation of the Microarray Time-Series Explorer (MaTSE), a novel information visualization application for the exploratory analysis of large scale microarray timeseries data. The software combines a variety of visualization and interaction techniques, which work together to allow biologists to explore their data and reveal patterns that would otherwise be impossible to find. These include a scatter-plot that can be animated to view different temporal intervals of the data, a multiple coordinated view framework to support the cross reference of multiple experimental conditions, a novel method for highlighting overlapping groups in the scatter-plot, and a pattern browser component that can be used with scatterplot box queries to support cooperative visualization. © 2012 ieee.

关键词： visualization

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ieee symposium on Biological data visualization 2012, BioVis 2012 - Proceedings

IEEE Symposium on Biological Data Visualization 2012, BioVis...

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2nd ieee symposium on Biological data visualization, BioVis 2012

ISBN: (纸本)9781467347303

The proceedings contain 16 papers. The topics discussed include: interactive extraction of neural structures with user-guided morphological diffusion;volume visualization in serial electron microscopy using local variance;INCIDE the brain of a bee: visualising honeybee brain activity in real time by semantic segmentation;towards real-time visualization of detailed neural tissue models: view frustum culling for parallel rendering;heterogeneity-based guidance for exploring multiscale data in systems biology;MaTSE: the microarray time-series explorer;ADVISe: visualizing the dynamics of enzyme annotations in UniProt/SwissProt;gene-RiViT: a visualization tool for comparative analysis of gene neighborhoods in prokaryote;mzRepeat: visual analysis of lipids in mass spectrometry;similarity analysis of cell movements in video microscopy;and epithelial cell reconstruction and visualization of the developing drosophila wing imaginal disc.

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A study of ray tracing large-scale scientific data in parallel visualization applications

A study of ray tracing large-scale scientific data in parall...

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12th Eurographics symposium on parallel graphics and visualization, EG PGV 2012

作者： Brownlee, Carson Patchett, John Lo, Li-Ta DeMarle, David Mitchell, Christopher Ahrens, James Hansen, Charles D. School of Computing University of Utah United States SCI Institute University of Utah United States Los Alamos National Labs United States Kitware Inc. United States

ISBN: (纸本)9783905674354

large-scale analysis and visualization is becoming increasingly important as supercomputers and their simulations produce larger and larger data. These large data sizes are pushing the limits of traditional rendering algorithms and tools thus motivating a study exploring these limits and their possible resolutions through alternative rendering algorithms . In order to better understand real-world performance with large data, this paper presents a detailed timing study on a large cluster with the widely used visualization tools ParaView and VisIt. The software ray tracer Manta was integrated into these programs in order to show that improved performance could be attained with software ray tracing on a distributed memory, GPU enabled, parallel visualization resource. Using the Texas Advanced Computing Center's Longhorn cluster which has multi-core CPUs and GPUs with large-scale polygonal data, we find multi-core CPU ray tracing to be significantly faster than both software rasterization and hardware-accelerated rasterization in existing scientific visualization tools with large data. © The Eurographics Association 2012.

关键词： Rasterization

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Gaussian mixture model based volume visualization

Gaussian mixture model based volume visualization

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2nd symposium on large-Scale data Analysis and visualization, LDAV 2012

作者： Liu, Shusen Levine, Joshua A. Bremer, Peer-Timo Pascucci, Valerio

ISBN: (纸本)9781467347334

Representing uncertainty when creating visualizations is becoming more indispensable to understand and analyze scientific data. Uncertainty may come from different sources, such as, ensembles of experiments or unavoidable information loss when performing data reduction. One natural model to represent uncertainty is to assume that each position in space instead of a single value may take on a distribution of values. In this paper we present a new volume rendering method using per voxel Gaussian mixture models (GMMs) as the input data representation. GMMs are an elegant and compact way to drastically reduce the amount of data stored while still enabling realtime data access and rendering on the GPU. Our renderer offers efficient sampling of the data distribution, generating renderings of the data that flicker at each frame to indicate high variance. We can accumulate samples as well to generate still frames of the data, which preserve additional details in the data as compared to either traditional scalar indicators (such as a mean or a single nearest neighbor down sample) or to fitting the data with only a single Gaussian per voxel. We demonstrate the effectiveness of our method using ensembles of climate simulations and MRI scans as well as the down sampling of large scalar fields as examples. © 2012 ieee.

关键词： visualization

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TiledRenderer - an Object Oriented Framework for MPI Based parallel Rendering

TiledRenderer - an Object Oriented Framework for MPI Based P...

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2nd ieee International Conference on parallel, Distributed and Grid Computing (PDGC)

作者： Shete, Pritam Prakash Kondapi, Venkata Pinaka Pani Sarode, Dinesh M. Laghate, Mohini A. Bose, Surojit Kumar Bhabha Atom Res Ctr Comp Div Bombay 400085 Maharashtra India

ISBN: (纸本)9781467329255

A visualization of large datasets requires ultra high resolution. data wall systems provide large number of pixels by combining a power of multiple graphics cards. In this paper, we propose and realize an object oriented framework for the Message Passing Interface based parallel rendering. We introduce a GUI based viewer called the TiledRenderer, which is used for viewing pre- recorded high resolution animations as well as images on data walls. We identify a set of design patterns in a development of the TiledRenderer. We talk about benefits of using design patterns for extending our framework for adding the Real Time Streaming Protocol based IP camera support. We demonstrate that use of design patterns facilitates reusing the existing functionality and adding new functionality by providing new classes, rather than modifying the existing classes or functionality. We also discuss about a visualization of tsunami simulation data by using 6x6 data wall and the TiledRenderer.

关键词： data wall design patterns Message Passing Interface object oriented programming Real Time Streaming Protocol parallel rendering computer simulations.

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