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An integrated visualization system for interactive analysis of large, heterogeneous cosmology data 9

An integrated visualization system for interactive analysis ...

引用

9th ieee Pacific visualization symposium, PacificVis 2016

作者： Preston, Annie Ghods, Ramyar Xie, Jinrong Sauer, Franz Leaf, Nick Ma, Kwan-Liu Rangel, Esteban Kovacs, Eve Heitmann, Katrin Habib, Salman University of California at Davis United States Northwestern University United States Argonne National Laboratory United States

ISBN: (纸本)9781509014514

Cosmological simulations produce a multitude of data types whose large scale makes them difficult to thoroughly explore in an interactive setting. One aspect of particular interest to scientists is the evolution of groups of dark matter particles, or "halos," described by merger trees. However, in order to fully understand subtleties in the merger trees, other data types derived from the simulation must be incorporated as well. In this work, we develop a novel interactive linked-view visualization system that focuses on simultaneously exploring dark matter halos, their hierarchical evolution, corresponding particle data, and other quantitative information. We employ a parallel remote renderer and a local merger tree selection tool so that users can analyze large data sets interactively. This allows scientists to assess their simulation code, understand inconsistencies in extracted data, and intuitively understand simulation behavior on all scales. We demonstrate the effectiveness of our system through a set of case studies on large-scale cosmological data from the HACC (Hardware/Hybrid Accelerated Cosmology Code) simulation framework. © 2016 ieee.

关键词： Cosmology

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Eurographics Workshop on parallel graphics and visualization

Eurographics Workshop on Parallel Graphics and Visualization

引用

2016 Eurographics symposium on parallel graphics and visualization, EGPGV 2016

ISBN: (纸本)9783038680062

The proceedings contain 10 papers. The topics discussed include: adaptive collision culling for large-scale simulations by a parallel sweep and prune algorithm;external face-list calculation with data-parallel primitives;parallel spatial splits in bounding volume hierarchies;interacting with large distributed datasets using sketch;high-performance mesh partitioning and ghost cell generation for visualization software;web-enabled server-based and distributed real-time ray-tracing;a scalable streamline generation algorithm via flux-based isocontour extraction;dynamically scheduled region-based image compositing;dynamic work packages in parallel rendering;and data mining tornado-genesis precursors.

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SW-AES: Accelerating AES Algorithm on the Sunway TaihuLight

SW-AES: Accelerating AES Algorithm on the Sunway TaihuLight

引用

ieee International symposium on parallel and Distributed Processing with Applications and ieee International Conference on Ubiquitous Computing and Communications (ISPA/IUCC)

作者： Liandeng Li Jiarui Fang Jinlei Jiang Lin Gan Weijie Zheng Haohuan Fu Guangwen Yang Department of Computer Science & Technology Tsinghua National Laboratory for Information Science and Technology Tsinghua University Beijing China Ministry of Education Key Laboratory for Earth System Modeling Center for Earth System Science Tsinghua University Beijing China National Supercomputing Center in Wuxi Jiangsu China

ISBN: (纸本)9781538637913

The Advanced Encryption Standard (AES) is a widely-used efficient cryptographic algorithm. Although AES is fast both in software and hardware, it is time-consuming to do data encryption especially for large amount of data. Therefore, it is a lasting effort to accelerate AES algorithms. This paper presents SW-AES, a parallel AES implementation on the Sunway TaihuLight, the fastest supercomputer in the world that takes the SW26010 many-core processor as the basic building block. According to the architectural features of SW26010, SW-AES exploits parallelism from different levels, including 1) inter-CPE (Compute-Processing Element) paral- lelism that distributes tasks among the 256 on-chip CPEs, 2) intra-CPE data parallelism enabled by the Single-Instruction Multiple-data (SIMD) instructions inside each CPE, and 3) instruction-level parallelism that pipelines memory access and the computation. As a result, SW-AES can gain a maximum throughput of 13.49 GB/s on a single SW26010 node, which is 210.78 × higher than the latest parallel AES implementation on the Sunway TaihuLight, and about 37.3% higher than the latest AES implementation on the GTX 480 GPU.

关键词： Encryption parallel processing Throughput Registers Pipelines graphics processing units Computer architecture

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Understanding the Context of Network Traffic Alerts

Understanding the Context of Network Traffic Alerts

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ieee symposium on visualization for Cyber Security (VizSec)

作者： Cappers, Bram C. M. van Wijk, Jarke J. Eindhoven Univ Technol Dept Math & Comp Sci NL-5600 MB Eindhoven Netherlands

ISBN: (纸本)9781509016051

For the protection of critical infrastructures against complex virus attacks, automated network traffic analysis and deep packet inspection are unavoidable. However, even with the use of network intrusion detection systems, the number of alerts is still too large to analyze manually. In addition, the discovery of domain-specific multi stage viruses (e.g., Advanced Persistent Threats) are typically not captured by a single alert. The result is that security experts are overloaded with low-level technical alerts where they must look for the presence of an APT. In this paper we propose an alert-oriented visual analytics approach for the exploration of network traffic content in multiple contexts. In our approach CoNTA (Contextual analysis of Network Traffic Alerts), experts are supported to discover threats in large alert collections through interactive exploration using selections and attributes of interest. Tight integration between machine learning and visualization enables experts to quickly drill down into the alert collection and report false alerts back to the intrusion detection system. Finally, we show the effectiveness of the approach by applying it on real world and artificial data sets.

关键词： Anomaly detection network traffic analysis multivariate analysis streaming data interaction parse data analysis C.2.0 [Computer Communication Networks]: General-Security and Protection H.5.2 [Information Interfaces and Presentation]: User Interfaces I.3.8 [Computer graphics]: Applications

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In situ generated probability distribution functions for interactive post hoc visualization and analysis 6

In situ generated probability distribution functions for int...

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6th ieee symposium on large-Scale data Analysis and visualization, LDAV 2016

作者： Ye, Yucong Chris Neuroth, Tyson Sauer, Franz Ma, Kwan-Liu Borghesi, Giulio Konduri, Aditya Kolla, Hemanth Chen, Jacqueline University of California DavisCA United States Sandia National Laboratory LivermoreCA United States

ISBN: (纸本)9781509056590

The growing power and capacity of supercomputers enable scientific simulations at extreme scale, leading to not only more accurate modeling and greater predictive ability but also massive quantities of data to analyze. New approaches to data analysis and visualization are this needed to support interactive exploration through selective data access for gaining insights into terabytes and petabytes of data. In this paper, we present an in situ data processing method for both generating probability distribution functions (PDFs) from field data and reorganizing particle data using a single spatial organization scheme. This coupling between PDFs and particles allows for the interactive post hoc exploration of both data types simultaneously. Scientists can explore trends in large-scale data through the PDFs and subsequently extract desired particle subsets for further analysis. We evaluate the usability of our in situ method using a petascale combustion simulation and demonstrate the increases in task efficiency and accuracy that the resulting workflow provides to scientists. © 2016 ieee.

关键词： Distribution functions

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SeekAView: An Intelligent Dimensionality Reduction Strategy for Navigating High-Dimensional data Spaces 6

<i>SeekAView</i>: An Intelligent Dimensionality Reduction St...

引用

6th ieee symposium on large data Analysis and visualization (LDAV)

作者： Krause, Josua Dasgupta, Aritra Fekete, Jean-Daniel Bertini, Enrico NYU New York NY 10003 USA Pacific Northwest Natl Lab Richland WA 99352 USA INRIA Le Chesnay France

ISBN: (纸本)9781509056590

Dealing with the curse of dimensionality is a key challenge in high-dimensional data visualization. We present SeekAView to address three main gaps in the existing research literature. First, automated methods like dimensionality reduction or clustering suffer from a lack of transparency in letting analysts interact with their outputs in real-time to suit their exploration strategies. The results often suffer from a lack of interpretability, especially for domain experts not trained in statistics and machine learning. Second, exploratory visualization techniques like scatter plots or parallel coordinates suffer from a lack of visual scalability: it is difficult to present a coherent overview of interesting combinations of dimensions. Third, the existing techniques do not provide a flexible workflow that allows for multiple perspectives into the analysis process by automatically detecting and suggesting potentially interesting subspaces. In SeekAView we address these issues using suggestion based visual exploration of interesting patterns for building and refining multidimensional subspaces. Compared to the state-of-the-art in subspace search and visualization methods, we achieve higher transparency in showing not only the results of the algorithms, but also interesting dimensions calibrated against different metrics. We integrate a visually scalable design space with an iterative workflow guiding the analysts by choosing the starting points and letting them slice and dice through the data to find interesting subspaces and detect correlations, clusters, and outliers. We present two usage scenarios for demonstrating how SeekAView can be applied in real-world data analysis scenarios.

关键词： High-Dimensional data Subspace Exploration Guided visualization

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VIS Keynote Address: Analytics Inspired visualization: a Holistic In-situ Scientific Workflow at Extreme Scale

VIS Keynote Address: Analytics Inspired Visualization: a Hol...

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ieee symposium on Visual Analytics Science and Technology (VAST)

作者： Jacqueline H. Chen Sandia National Laboratories

ISBN: (纸本)9781538631645;9781538631638

Combustion and turbulence simulations involve highly intermittent localized phenomena that generate high volumes of spatially and temporally varying field and particle data. The current paradigm of posthoc analysis and visualization will become increasingly infeasible as data volumes continue to increase. In the exascale era this problem will be further exacerbated by the difficulty of moving large volumes of data through deep complex memory hierarchies and across the machine network to hard disks on a heterogeneous supercomputer. I will discuss recent advances in in situ massively parallel volume and particle visualization algorithms coupled with analytics - e.g., topological feature segmentation/tracking, distance field construction, multi-variate statistics and eigensolutions of the reaction rate Jacobian - as an integral part of a scientific discovery from high-fidelity combustion simulations. The role of asynchronous task based programming models and runtimes to facilitate an extensible, performance portable computational science workflow at extreme scale will also be discussed in the context of recent turbulent ignition simulations.

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Research on visualization techniques in large scale virtual battlefield 1

Research on visualization techniques in large scale virtual ...

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1st ieee International Conference on data Science in Cyberspace (DSC)

作者： Wu Lingda Hao Hongxing Yang Chao Yu Ronghuan Hu Huaquan Equipment Acad Sci & Technol Complex Elect Syst Simulat Lab Beijing Peoples R China

ISBN: (纸本)9781509011926

As the development of computer graphics, visualization is widely used in the simulation of war. A bunch of techniques are proposed and employed in virtual battlefield visualization. This paper focuses on the summarization of these visualization techniques that can be applied in virtual battlefield. Firstly, the paper researches on the elements of environment and basic facilities, and classifies the visualization objects in battlefield to points, lines, surfaces and volumes by the character of these elements. We also analyze the methods of visualization for these elements. Then we study on the acceleration technology for the complexity virtual battlefield. Finally, visualization results for the four types of element are given, and from these results we can get that abstract information in battlefield are much more understandable and intuitional by visualization so as to assistant the commander to make decision.

关键词： virtual battlefield visualization techniques GPU acceleration parallel computation

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Immersive Molecular visualization with Omnidirectional Stereoscopic Ray Tracing and Remote Rendering 30

Immersive Molecular Visualization with Omnidirectional Stere...

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30th ieee International parallel and Distributed Processing symposium (IPDPS)

作者： Stone, John E. Sherman, William R. Schulten, Klaus Univ Illinois Beckman Inst Urbana IL 61801 USA Indiana Univ Pervas Technol Inst Bloomington IN USA Univ Illinois Dept Phys Urbana IL USA

ISBN: (纸本)9781509036820

Immersive molecular visualization provides the viewer with intuitive perception of complex structures and spatial relationships that are of critical interest to structural biologists. The recent availability of commodity head mounted displays (HMDs) provides a compelling opportunity for widespread adoption of immersive visualization by molecular scientists, but HMDs pose additional challenges due to the need for low-latency, high-frame-rate rendering. State-of-the-art molecular dynamics simulations produce terabytes of data that can be impractical to transfer from remote supercomputers, necessitating routine use of remote visualization. Hardware-accelerated video encoding has profoundly increased frame rates and image resolution for remote visualization, however round-trip network latencies would cause simulator sickness when using HMDs. We present a novel two-phase rendering approach that overcomes network latencies with the combination of omnidirectional stereoscopic progressive ray tracing and high performance rasterization, and its implementation within VMD, a widely used molecular visualization and analysis tool. The new rendering approach enables immersive molecular visualization with rendering techniques such as shadows, ambient occlusion lighting, depth-of-field, and high quality transparency, that are particularly helpful for the study of large biomolecular complexes. We describe ray tracing algorithms that are used to optimize interactivity and quality, and we report key performance metrics of the system. The new techniques can also benefit many other application domains.

关键词： immersive visualization molecular visualization remote visualization ray tracing head mounted displays

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parallel Randomized KD-tree Forest on GPU Cluster for Image Descriptor Matching

Parallel Randomized KD-tree Forest on GPU Cluster for Image ...

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ieee International symposium on Circuits and Systems (ISCAS)

作者： Hu, Linjia Nooshabadi, Saeid Ahmadi, Majid Michigan Tech Dept Comp Sci Houghton MI 49931 USA Univ Windsor Dept Elect & Comp Engn Windsor ON Canada

ISBN: (纸本)9781479953417

Many high dimensional data mining applications involve the nearest neighbor search (NNS) on a KD-tree. Randomized KD-tree forest enables fast medium and large scale NNS among high dimensional data points. In this paper, we present massively parallel algorithms for the construction of KD-tree forest, and NNS on a cluster equipped with massively parallel architecture (MPA) devices of graphical processing unit (GPU). This design can accelerate the KD-tree forest construction and NNS significantly for the signature of histograms of orientations (SHOT) 3D local descriptors by factors of up to 5.27 and 20.44, respectively. Our implementations will potentially benefit realtime high dimensional descriptors matching.

关键词： Nearest neighbor search

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