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ieee symposium on large data Analysis and visualization (LDAV)

作者： Jinrong Xie Hongfeng Yu Kwan-Liu Ma University of California-Davis California USA University of Nebraska-Lincoln Nebraska USA University of California Davis Davis CA US

Geodesic grids become increasingly prevalent in large weather and climate applications. The deluge amount of simulation data demands efficient and scalable visualization capabilities for scientific exploration and understanding. Given the unique characteristics of geodesic grids, no current techniques can scalably visualize scalar fields defined on a geodesic grid. In this paper, we present a new parallel ray-casting algorithm for large geodesic grids using massively distributed GPUs. We construct a spherical quadtree to adaptively partition and distribute the data according to the grid resolution of simulation, and ensure a balanced workload assignment over a large number of processors from different view angles. We have designed and implemented the entire rendering pipeline based on the MPI and CUDA architecture, and demonstrated the effectiveness and scalability of our approach using an example of large application on a supercomputer with thousands of GPUs.

关键词： Rendering (computer graphics) data visualization data models Sea surface Surface treatment graphics processing units

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An Edge-Bundling Layout for Interactive parallel Coordinates

An Edge-Bundling Layout for Interactive Parallel Coordinates

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Pacific (formerly Asia-Pacific APVIS) visualization symposium

作者： Gregorio Palmas Myroslav Bachynskyi Antti Oulasvirta Hans Peter Seidel Tino Weinkauf MPI Informatik MPI Informatik Saarland University

parallel Coordinates is an often used visualization method for multidimensional data sets. Its main challenges for large data sets are visual clutter and over plotting which hamper the recognition of patterns in the data. We present an edge-bundling method using density-based clustering for each dimension. This reduces clutter and provides a faster overview of clusters and trends. Moreover, it allows rendering the clustered lines using polygons, decreasing rendering time remarkably. In addition, we design interactions to support multidimensional clustering with this method. A user study shows improvements over the classic parallel coordinates plot in two user tasks: correlation estimation and subset tracing.

关键词： Strips Layout Image color analysis visualization data visualization Rendering (computer graphics) Clutter

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A Framework for Lattice QCD Calculations on GPUs

A Framework for Lattice QCD Calculations on GPUs

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ieee 28th International parallel & Distributed Processing symposium (IPDPS)

作者： Winter, F. T. Clark, M. A. Edwards, R. G. Joo, B. Thomas Jefferson Natl Accelerator Facil Newport News VA 23606 USA NVIDIA Corp Santa Clara CA 95050 USA

ISBN: (纸本)9780769552071

Computing platforms equipped with accelerators like GPUs have proven to provide great computational power. However, exploiting such platforms for existing scientific applications is not a trivial task. Current GPU programming frameworks such as CUDA C/C++ require low-level programming from the developer in order to achieve high performance code. As a result porting of applications to GPUs is typically limited to time-dominant algorithms and routines, leaving the remainder not accelerated which can open a serious Amdahl's law issue. The Lattice QCD application Chroma allows us to explore a different porting strategy. The layered structure of the software architecture logically separates the data-parallel from the application layer. The QCD data-parallel software layer provides data types and expressions with stencil-like operations suitable for lattice field theory. Chroma implements algorithms in terms of this high-level interface. Thus by porting the low-level layer one effectively ports the whole application layer in one swing. The QDP-JIT/PTX library, our reimplementation of the low-level layer, provides a framework for Lattice QCD calculations for the CUDA architecture. The complete software interface is supported and thus applications can be run unaltered on GPU-based parallel computers. This reimplementation was possible due to the availability of a JIT compiler which translates an assembly language (PTX) to GPU code. The existing expression templates enabled us to employ compile-time computations in order to build code generators and to automate the memory management for CUDA. Our implementation has allowed us to deploy the full Chroma gauge-generation program on large scale GPU-based machines such as Titan and Blue Waters and accelerate the calculation by more than an order of magnitude.

关键词： Application framework C++ CUDA GPU JIT Lattice QCD PTX Lattice QCD GRAPPER PICK UP graphics Processing Unit Application Framework just in time compiler data parallel application layer Store management LOW LEVEL Code generation Chroma Frameworks software interface

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A GPU-based parallel computing framework for accelerating the reconstruction of q-ball imaging

A GPU-based parallel computing framework for accelerating th...

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International symposium on Computer, Consumer and Control (IS3C)

作者： Lai, Hong-Che Yeh, Chun-Hung Cho, Kuan-Hung Lin, Ching-Po Lee, Chia-Yen Chao, Yi-Ping Natl Yang Ming Univ Inst Brain Sci Taipei Taiwan Natl Yang Ming Univ Inst Neurosci Taipei 112 Taiwan Chang Gung Univ Dept Comp Sci & Informat Engn Taoyuan Taiwan Natl Unite Univ Dept Elect Engn Durham NC USA

ISBN: (纸本)9781479952779

High-angular resolution diffusion imaging(HARDI) relative to the diffusion tensor imaging(DTI) can resolve the complex fiber crossing of each voxel in the brain, however, the image reconstruction time is longer than conventional technology, therefore, to improve the performance is a very important work to do. We used graphic processing unit (GPU) and CUDA to compute the spherical harmonic function on the reconstruction of QBI. It's very useful on massive performance data(Bid data). With the large number of matrix elements in GPU for parallel computing. By evaluating with different video cards, the improved performance showed 179 to 574 speed up through shared memory access for computation. Finally, the results wiil be used in an extension of the three-dimensional spatial visualization and probabilistic tractography.

关键词： HARDI GPU CUDA QBI parallel computing

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Moving beyond sequential design: Reflections on a rich multi-channel approach to data visualization

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ieee TRANSACTIONS ON visualization AND COMPUTER graphics 2014年第12期20卷 2171-2180页

作者： Wood, Jo Beecham, Roger Dykes, Jason City Univ London giCtr London England

We reflect on a four-year engagement with transport authorities and others involving a large dataset describing the use of a public bicycle-sharing scheme. We describe the role visualization of these data played in fostering engagement with policy makers, transport operators, the transport research community, the museum and gallery sector and the general public. We identify each of these as 'channels' - evolving relationships between producers and consumers of visualization - where traditional roles of the visualization expert and domain expert are blurred. In each case. we identify the different design decisions that were required to support each of these channels and the role played by the visualization process. Using chauffeured interaction with a flexible visual analytics system we demonstrate how insight was gained by policy makers into gendered spatio-temporal cycle behaviors;how this led to further insight into workplace commuting activity, group cycling behavior and explanations for street navigation choice. We demonstrate how this supported, and was supported by, the seemingly unrelated development of narrative-driven visualization via TEDx, of the creation and the setting of an art installation and the curating of digital and physical artefacts. We assert that existing models of visualization design, of tool/technique development and of insight generation do not adequately capture the richness of parallel engagement via these multiple channels of communication. We argue that developing multiple channels in parallel opens up opportunities for visualization design and analysis by building trust and authority and supporting creativity. This rich, non-sequential approach to visualization design is likely to foster serendipity, deepen insight and increase impact.

关键词： Movement visualization visual analytics bikeshare impact visualization models design study

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Combing the Communication Hairball: Visualizing parallel Execution Traces using Logical Time

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ieee TRANSACTIONS ON visualization AND COMPUTER graphics 2014年第12期20卷 2349-2358页

作者： Isaacs, Katherine E. Bremer, Peer-Timo Jusufi, Ilir Gamblin, Todd Bhatele, Abhinav Schulz, Martin Hamann, Bernd Univ Calif Davis Davis CA 95616 USA Lawrence Livermore Natl Lab Livermore CA USA

With the continuous rise in complexity of modern supercomputers, optimizing the performance of large-scale parallel programs is becoming increasingly challenging. Simultaneously, the growth in scale magnifies the impact of even minor inefficiencies - potentially millions of compute hours and megawatts in power consumption can be wasted on avoidable mistakes or sub-optimal algorithms. This makes performance analysis and optimization critical elements in the software development process. One of the most common forms of performance analysis is to study execution traces, which record a history of per-process events and inter-process messages in a parallel application. Trace visualizations allow users to browse this event history and search for insights into the observed performance behavior. However, current visualizations are difficult to understand even for small process counts and do not scale gracefully beyond a few hundred processes. Organizing events in time leads to a virtually unintelligible conglomerate of interleaved events and moderately high process counts overtax even the largest display. As an alternative, we present a new trace visualization approach based on transforming the event history into logical time inferred directly from happened-before relationships. This emphasizes the code's structural behavior, which is much more familiar to the application developer. The original timing data, or other information, is then encoded through color, leading to a more intuitive visualization. Furthermore, we use the discrete nature of logical timelines to cluster processes according to their local behavior leading to a scalable visualization of even long traces on large process counts. We demonstrate our system using two case studies on large-scale parallel codes.

关键词： Information visualization software visualization. timelines traces performance analysis

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Analytical visualization of large-Scale data of 3D Cultural Objects

Analytical Visualization of Large-Scale Data of 3D Cultural ...

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Pacific (formerly Asia-Pacific APVIS) visualization symposium

作者： Satoshi Tanaka Ritsumeikan University

For appreciating 3D cultural objects, e.g., artistic statues, traditional vehicles, and historical buildings or cities, visualization has mainly been used in the following styles: (1) realistic computer graphics, (2) artistic computer graphics, and (3) interactive virtual reality. However, for academic studying of 3D cultural objects, these styles are insufficient. Namely, we need more analytical styles that can extract invisible or veiled features of visualized targets. What makes such analytical visualization more important is recent rapid development of range-sensing technology to digitally archive real 3D objects. For example, modern laser scanning produces over 107 or 108 3D point data for one measurement. To extract useful information from such large-scale and complex data, we need (A) precise 3D transparent visualization, (B) superposition of visual assistants, and (C) time-series visualization.

关键词： Three-dimensional displays data visualization Cultural differences Measurement by laser beam Laser modes Buildings Rendering (computer graphics)

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Space-time volumetric depth images for in-situ visualization

Space-time volumetric depth images for in-situ visualization

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ieee symposium on large data Analysis and visualization (LDAV)

作者： Oliver Fernandes Steffen Frey Filip Sadlo Thomas Ertl University of Stuttgart

Volumetric depth images (VDI) are a view-dependent representation that combines the high quality of images with the explorability of 3D fields. By compressing the scalar data along view rays into sets of coherent supersegments, VDIs provide an efficient representation that supports a-posteriori changes of camera parameters. In this paper, we introduce space-time VDIs that achieve the data reduction that is required for efficient in-situ visualization, while still maintaining spatiotemporal flexibility. We provide an efficient space-time representation of VDI streams by exploiting inter-ray and inter-frame coherence, and introduce delta encoding for further data reduction. Our space-time VDI approach exhibits small computational overhead, is easy to integrate into existing simulation environments, and may help pave the way toward exascale computing.

关键词： data visualization Image color analysis Encoding Computational modeling Rendering (computer graphics) data models Cameras

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Advection-Based Sparse data Management for Visualizing Unsteady Flow

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ieee TRANSACTIONS ON visualization AND COMPUTER graphics 2014年第12期20卷 2555-2564页

作者： Guo, Hanqi Zhang, Jiang Liu, Richen Liu, Lu Yuan, Xiaoru Huang, Jian Meng, Xiangfei Pan, Jingshan Peking Univ Key Lab Machine Percept Minist Educ Sch EECS Beijing Peoples R China Peking Univ Ctr Computat Sci & Engn Beijing Peoples R China Univ Tennessee Dept Elect Engn & Comp Sci Knoxville TN USA Natl Supercomp Ctr Tianjin Tianjin Peoples R China Natl Supercomp Ctr Jinan Shandong Peoples R China

When computing integral curves and integral surfaces for large-scale unsteady flow fields. a major bottleneck is the widening gap between data access demands and the available bandwidth (both I/O and in-memory). In this work, we explore a novel advection-based scheme to manage flow field data for both efficiency and scalability. The key is to first partition flow field into blocklets (e.g. cells or very fine-grained blocks of cells), and then (pre)fetch and manage blocklets on-demand using a parallel key-value store. The benefits are (1) greatly increasing the scale of local-range analysis (e.g. source-destination queries, streak surface generation) that can fit within any given limit of hardware resources;(2) improving memory and I/O bandwidth-efficiencies as well as the scalability of naive task-parallel particle advection. We demonstrate our method using a prototype system that works on workstation and also in supercomputing environments. Results show significantly reduced I/O overhead compared to accessing raw flow data. and also high scalability on a supercomputer for a variety of applications.

关键词： Flow visualization data management High performance visualization Key-value store

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parallel processing and immersive visualization of sonar point clouds

Parallel processing and immersive visualization of sonar poi...

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ieee symposium on large data Analysis and visualization (LDAV)

作者： Alessandro Febretti Kristof Richmond Peter Doran Andrew Johnson Electronic Visualization Lab University of Illinois at Chicago Lake Land College Mattoon IL US Dept. of Environmental Science University of Illinois at Chicago

The investigation of underwater structures and natural features through Autonomous Underwater Vehicles (AUVs) is an expanding field with applications in archaeology, engineering, environmental sciences and astrobiology. Processing and analyzing the raw sonar data generated by automated surveys is challenging due to the presence of complex error sources like water chemistry, zero-depth variations, inertial navigation errors and multipath reflections. Furthermore, the complexity of the collected data makes it difficult to perform effective analysis on a standard display. Point clouds made up of hundreds of millions to billions of points are not uncommon. Highly interactive, immersive visualization is a desirable tool that researchers can use to improve the quality of a final sonar-based data product. In this paper we present a scalable toolkit for the processing and visualization of sonar point clouds on a cluster-based, large scale immersive visualization environment. The cluster is used simultaneously as a parallel processing platform that performs sonar beam-tracing of the source raw data, and as the rendering driver of the immersive display.

关键词： data visualization Sonar Three-dimensional displays Antarctica Lakes Sonar navigation Acoustic beams

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