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检索条件"任意字段=Proceedings of the IEEE 2001 symposium on parallel and large-data visualization and graphics"

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proceedings - 2020 ieee 10th symposium on large data Analysis and visualization, LDAV 2020

Proceedings - 2020 IEEE 10th Symposium on Large Data Analysi...

引用

10th ieee symposium on large data Analysis and visualization, LDAV 2020

ISBN: (纸本)9781728184685

The proceedings contain 7 papers. The topics discussed include: DIVA: a declarative and reactive language for in situ visualization;data parallel hypersweeps for in situ topological analysis;comparing time-to-solution for in situ visualization paradigms at scale;interactive visualization of terascale data in the browser: fact or fiction?;cinema darkroom: a deferred rendering framework for large-scale datasets;spatial partitioning strategies for memory-efficient ray tracing of particles;and a distributed algorithm for force directed edge bundling.

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Moving from Composable to Programmable

Moving from Composable to Programmable

引用

ieee International symposium on parallel and Distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Zhongyi Chen Luc Renambot Lance Long Maxine Brown Andrew E. Johnson Electronic Visualization Lab Computer Science Univ Illinois Chicago Chicago Illinois USA

ISBN: (数字)9781665497473

ISBN: (纸本)9781665497480

In today's Big data era, data scientists require modern workflows to quickly analyze large-scale datasets using complex codes to maintain the rate of scientific progress. These scientists often rely on available campus resources or off-the-shelf computational systems for their applications. Unified infrastructure or over-provisioned servers can quickly become bottlenecks for specific tasks, wasting time and resources. Composable infrastructure helps solve these problems by providing users with new ways to increase resource utilization. Composable infrastructure disaggregates a computer's components - CPU, GPU (accelerators), storage and networking - into fluid pools of resources, but typically relies upon infrastructure engineers to architect individual machines. Infrastructure is either managed with specialized command-line utilities, user interfaces or specification files. These management models are cumbersome and difficult to incorporate into data-science workflows. We developed a high-level software API, Composastructure, which, when integrated into modern workflows, can be used by infrastructure engineers as well as data scientists to reorganize composable resources on demand. Composastructure enables infrastructures to be programmable, secure, persistent and reproducible. Our API composes machines, frees resources, supports multi-rack operations, and includes a Python module for Jupyter Notebooks.

关键词： Symbiosis Codes Shape graphics processing units Ethernet User interfaces Software

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ieee Pacific visualization symposium

IEEE Pacific Visualization Symposium

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13th ieee Pacific visualization symposium, PacificVis 2020

ISBN: (纸本)9781728156972

The proceedings contain 30 papers. The topics discussed include: towards rigorously designed preference visualizations for group decision making;a study of mental maps in immersive network visualization;quality metrics for symmetric graph drawings;BatchLayout: a batch-parallel force-directed graph layout algorithm in shared memory;ExplainExplore: visual exploration of machine learning explanations.;interactive attention model explorer for natural language processing tasks with unbalanced data sizes;visual interpretation of recurrent neural network on multi-dimensional time-series forecast;visualization of unsteady flow using heat kernel signatures;and tensor spines - a hyperstreamlines variant suitable for indefinite symmetric second-order tensors.

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parallel Particle Advection and Lagrangian Analysis for 3D-PLI Fiber Orientation Maps 9

Parallel Particle Advection and Lagrangian Analysis for 3D-P...

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9th ieee symposium on large data Analysis and visualization (LDAV)

作者： Demiralp, Ali C. Zielasko, Daniel Axer, Markus Vierjahn, Tom Kuhlen, Torsten W. Rhein Westfal TH Aachen Visual Comp Inst JARA HPC Aachen Germany Univ Trier Trier Germany Julich Res Ctr Julich Germany Westphalian Univ Appl Sci Gelsenkirchen Germany

ISBN: (纸本)9781728126050

3D-Polarized Light Imaging (3D-PLI) is a recent neuroimaging technique which is able to record the orientation of nerve fibers in unprecedented detail, reaching micrometer scale. Particle advection, which streamline tractography is based upon, is an established tool to study the structure of fiber tracts within the brain. This work presents a distributed particle advection pipeline for 3D-PLI fiber orientation maps, which are time-invariant vector fields describing the dominant orientation of nerve fibers at each point. Due to the high resolution, 3D-PLI creates large datasets ranging from few gigabytes up to hundreds of terabytes, which is addressed through a data-parallel approach to advection. Furthermore, we propose Lagrangian analysis of time-invariant brain data through computation of Finite-Time Lyapunov Exponents (FTLE), which may aid identification of macroscopic fiber bundles.

关键词： D.1.3 [Software]: Programming Techniques Concurrent programming I.3.5 [Computer graphics]: Computational Geometry and Object Modeling Curve, surface, solid and object representations

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Interactive visualization of Terascale data in the Browser: Fact or Fiction?

Interactive Visualization of Terascale Data in the Browser: ...

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ieee symposium on large data Analysis and visualization (LDAV)

作者： Will Usher Valerio Pascucci SCI Institute University of Utah

ISBN: (数字)9781728184685

ISBN: (纸本)9781728184692

Information visualization applications have become ubiquitous, in no small part thanks to the ease of wide distribution and deployment to users enabled by the web browser. Scientific visualization applications, relying on native code libraries and parallel processing, have been less suited to such widespread distribution, as browsers do not provide the required libraries or compute capabilities. In this paper, we revisit this gap in visualization technologies and explore how new web technologies, WebAssembly and WebGPU, can be used to deploy powerful visualization solutions for large-scale scientific data in the browser. In particular, we evaluate the programming effort required to bring scientific visualization applications to the browser through these technologies and assess their competitiveness against classic native solutions. As a main example, we present a new GPU-driven isosurface extraction method for block-compressed data sets, that is suitable for interactive isosurface computation on large volumes in resource-constrained environments, such as the browser. We conclude that web browsers are on the verge of becoming a competitive platform for even the most demanding scientific visualization tasks, such as interactive visualization of isosurfaces from a 1TB DNS simulation. We call on researchers and developers to consider investing in a community software stack to ease use of these upcoming browser features to bring accessible scientific visualization to the browser.

关键词： Browsers Isosurfaces graphics processing units Servers Rendering (computer graphics) Libraries Arrays

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2019 ieee 9th symposium on large data Analysis and visualization, LDAV 2019

2019 IEEE 9th Symposium on Large Data Analysis and Visualiza...

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9th ieee symposium on large-Scale data Analysis and visualization, LDAV 2019

ISBN: (纸本)9781728126050

The proceedings contain 16 papers. The topics discussed include: VAMD: visual analytics for multimodal data;low-overhead in situ visualization using halo replay;bringing the field into the lab: large-scale visualization of animal movement trajectories within a virtual island;topological analysis of high velocity turbulent flow;a lifeline-based approach for work requesting and parallel particle advection;and topology-based spectral sparsi?cation.

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parallel Partial Reduction for large-Scale data Analysis and visualization 8

Parallel Partial Reduction for Large-Scale Data Analysis and...

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8th ieee symposium on large-Scale data Analysis and visualization (LDAV)

作者： He, Wenbin Guo, Hanqi Peterka, Tom Di, Sheng Cappello, Franck Shen, Han-Wei Ohio State Univ Dept Comp Sci & Engn Columbus OH 43210 USA Argonne Natl Lab Math & Comp Sci Div Lemont IL USA

ISBN: (纸本)9781538668733

We present a novel partial reduction algorithm to aggregate sparsely distributed intermediate results that are generated by data-parallel analysis and visualization algorithms. Applications of partial reduction include flow trajectory analysis, big data online analytical processing, and volume rendering. Unlike traditional full parallel reduction that exchanges dense data across all processes, the purpose of partial reduction is to exchange only intermediate results that correspond to the same query, such as line segments of the same flow trajectory. To this end, we design a three-stage algorithm that minimizes the communication cost: (1) partitioning the result space into groups;(2) constructing and optimizing the reduction partners for each group;and (3) initiating collective reduction operations for all groups concurrently. Both theoretical and empirical analyses show that our algorithm outperforms the traditional methods when the intermediate results are sparsely distributed. We also demonstrate the effectiveness of our algorithm for flow visualization, big log data analysis, and volume rendering.

关键词： I.3.1 [COMPUTER graphics]: Hardware Architecture-parallel processing I.3.2 [COMPUTER graphics]: graphics Systems-Distributed/network graphics

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Comparing Binary-Swap Algorithms for Odd Factors of Processes 8

Comparing Binary-Swap Algorithms for Odd Factors of Processe...

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8th ieee symposium on large-Scale data Analysis and visualization (LDAV)

作者： Moreland, Kenneth Sandia Natl Labs Livermore CA 94550 USA

ISBN: (纸本)9781538668733

A key component of most large-scale rendering systems is a parallel image compositing algorithm, and the most commonly used compositing algorithms are binary swap and its variants. Although shown to be very efficient, one of the classic limitations of binary swap is that it only works on a number of processes that is a perfect power of 2. Multiple variations of binary swap have been independently introduced to overcome this limitation and handle process counts that have factors that are not 2. To date, few of these approaches have been directly compared against each other, making it unclear which approach is best. This paper presents a fresh implementation of each of these methods using a common software framework to make them directly comparable. These methods to run binary swap with odd factors are directly compared. The results show that some simple compositing approaches work as well or better than more complex algorithms that are more difficult to implement.

关键词： Computing methodologies Computer graphics Rendering Computing methodologies parallel computing methodologies parallel algorithms Massively parallel algorithms

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A Proposed Framework for Interactive Virtual Reality In Situ visualization of parallel Numerical Simulations

A Proposed Framework for Interactive Virtual Reality In Situ...

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ieee symposium on large data Analysis and visualization (LDAV)

作者： Aryaman Gupta Ulrik Günther Pietro Incardona Ata Deniz Aydin Raimund Dachselt Stefan Gumhold Ivo F. Sbalzarini Technische Universität Dresden & Center for Systems Biology Dresden (CSBD) & MPI-CBG Dresden Technische Universität Dresden Interactive Media Lab Dresden Cluster of Excellence Physics of Life Technische Universität Dresden Cluster of Excellence Physics of Life Technische Universität Dresden CSBD & MPI-CBG Dresden Cluster of Excellence Physics of Life

As computer simulations progress to increasingly complex, non-linear, and three-dimensional systems and phenomena, intuitive and immediate visualization of their results is becoming crucial. While Virtual Reality (VR) and Natural User Interfaces (NUIs) have been shown to improve understanding of complex 3D data, their application to live in situ visualization and computational steering is hampered by performance requirements. Here, we present the design of a software framework for interactive VR in situ visualization of parallel numerical simulations, as well as a working prototype implementation. Our design is targeted towards meeting the performance requirements for VR, and our work is packaged in a framework that allows for easy instrumentation of simulations. Our preliminary results inform about the technical feasibility of the architecture, as well as the challenges that remain.

关键词： data visualization Rendering (computer graphics) Computational modeling Solid modeling Numerical models Prototypes data models

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Galaxy: Asynchronous Ray Tracing for large High-Fidelity visualization 8

Galaxy: Asynchronous Ray Tracing for Large High-Fidelity Vis...

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8th ieee symposium on large-Scale data Analysis and visualization (LDAV)

作者： Abram, Greg Navratil, Paul Grossett, Pascal Rogers, David Ahrens, James Texas Adv Comp Ctr Austin TX 78758 USA Los Alamos Natl Lab Los Alamos NM USA

ISBN: (纸本)9781538668733

We present Galaxy, a fully asynchronous distributed parallel rendering engine geared towards using full global illumination for large-scale visualization. Galaxy provides performant distributed rendering of complex lighting and material models, particularly those that require ray traversal across nodes. Our design is favorable for tightly-coupled in situ scenarios, where data remains on simulation nodes. By employing asynchronous framebuffer updates and a novel subtractive lighting model, we achieve acceptable image quality from the first ray generation, and improve quality throughout the render epoch. On simulated in situ rendering tasks, Galaxy outperforms the current best-of-breed scientific ray tracer by over 3x for distributed geometric and particle data, while providing expanded rendering capability for global illumination and complex materials.

关键词： Human-Centered Computing visualization Computer graphics Rendering Ray Tracing

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