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Modern Scientific Visualization is more than Just Pretty Pictures

Description: While the primary product of scientific visualization is images and movies, its primary objective is really scientific insight. Too often, the focus of visualization research is on the product, not the mission. This paper presents two case studies, both that appear in previous publications, that focus on using visualization technology to produce insight. The first applies"Query-Driven Visualization" concepts to laser wakefield simulation data to help identify and analyze the process of beam formation. The second uses topological analysis to provide a quantitative basis for (i) understanding the mixing process in hydrodynamic simulations, and (ii) performing comparative analysis of data from two different types of simulations that model hydrodynamic instability.
Date: December 5, 2008
Creator: Bethel, E Wes; Rubel, Oliver; Wu, Kesheng; Weber, Gunther; Pascucci, Valerio; Childs, Hank et al.
Partner: UNT Libraries Government Documents Department

Production-quality Tools for Adaptive Mesh RefinementVisualization

Description: Adaptive Mesh Refinement (AMR) is a highly effectivesimulation method for spanning a large range of spatiotemporal scales,such as astrophysical simulations that must accommodate ranges frominterstellar to sub-planetary. Most mainstream visualization tools stilllack support for AMR as a first class data type and AMR code teams usecustom built applications for AMR visualization. The Department ofEnergy's (DOE's) Science Discovery through Advanced Computing (SciDAC)Visualization and Analytics Center for Enabling Technologies (VACET) isextending and deploying VisIt, an open source visualization tool thataccommodates AMR as a first-class data type, for use asproduction-quality, parallel-capable AMR visual data analysisinfrastructure. This effort will help science teams that use AMR-basedsimulations and who develop their own AMR visual data analysis softwareto realize cost and labor savings.
Date: October 25, 2007
Creator: Weber, Gunther H.; Childs, Hank; Bonnell, Kathleen; Meredith,Jeremy; Miller, Mark; Whitlock, Brad et al.
Partner: UNT Libraries Government Documents Department

Recent Advances in VisIt: AMR Streamlines and Query-Driven Visualization

Description: Adaptive Mesh Refinement (AMR) is a highly effective method for simulations spanning a large range of spatiotemporal scales such as those encountered in astrophysical simulations. Combining research in novel AMR visualization algorithms and basic infrastructure work, the Department of Energy's (DOEs) Science Discovery through Advanced Computing (SciDAC) Visualization and Analytics Center for Enabling Technologies (VACET) has extended VisIt, an open source visualization tool that can handle AMR data without converting it to alternate representations. This paper focuses on two recent advances in the development of VisIt. First, we have developed streamline computation methods that properly handle multi-domain data sets and utilize effectively multiple processors on parallel machines. Furthermore, we are working on streamline calculation methods that consider an AMR hierarchy and detect transitions from a lower resolution patch into a finer patch and improve interpolation at level boundaries. Second, we focus on visualization of large-scale particle data sets. By integrating the DOE Scientific Data Management (SDM) Center's FastBit indexing technology into VisIt, we are able to reduce particle counts effectively by thresholding and by loading only those particles from disk that satisfy the thresholding criteria. Furthermore, using FastBit it becomes possible to compute parallel coordinate views efficiently, thus facilitating interactive data exploration of massive particle data sets.
Date: November 12, 2009
Creator: Weber, Gunther; Ahern, Sean; Bethel, Wes; Borovikov, Sergey; Childs, Hank; Deines, Eduard et al.
Partner: UNT Libraries Government Documents Department

Seeing the Unseeable

Description: The SciDAC Visualization and Analytics Center for Enabling Technologies (VACET) isa highly productive effort combining the forces of leading visualization researchersfrom five different institutions to solve some of the most challenging dataunderstanding problems in modern science. The VACET technology portfolio isdiverse, spanning all typical visual data analysis use models and effectivelybalancing forward-looking research with focused software architecture andengineering resulting in a production-quality software infrastructure. One of the keyelements in VACET's success is a rich set of projects that are collaborations withscience stakeholders: these efforts focus on identifying and overcoming obstacles toscientific knowledge discovery in modern, large, and complex scientific datasets.
Date: May 30, 2008
Creator: Bethel, Edward W; Bethel, E. Wes; Johnson, Chris; Hansen, Charles; Silva, Claudio; Parker, Steven et al.
Partner: UNT Libraries Government Documents Department

High Performance Multivariate Visual Data Exploration for Extremely Large Data

Description: One of the central challenges in modern science is the need to quickly derive knowledge and understanding from large, complex collections of data. We present a new approach that deals with this challenge by combining and extending techniques from high performance visual data analysis and scientific data management. This approach is demonstrated within the context of gaining insight from complex, time-varying datasets produced by a laser wakefield accelerator simulation. Our approach leverages histogram-based parallel coordinates for both visual information display as well as a vehicle for guiding a data mining operation. Data extraction and subsetting are implemented with state-of-the-art index/query technology. This approach, while applied here to accelerator science, is generally applicable to a broad set of science applications, and is implemented in a production-quality visual data analysis infrastructure. We conduct a detailed performance analysis and demonstrate good scalability on a distributed memory Cray XT4 system.
Date: August 22, 2008
Creator: Rubel, Oliver; Wu, Kesheng; Childs, Hank; Meredith, Jeremy; Geddes, Cameron G.R.; Cormier-Michel, Estelle et al.
Partner: UNT Libraries Government Documents Department

Application of High-performance Visual Analysis Methods to Laser Wakefield Particle Acceleration Data

Description: Our work combines and extends techniques from high-performance scientific data management and visualization to enable scientific researchers to gain insight from extremely large, complex, time-varying laser wakefield particle accelerator simulation data. We extend histogram-based parallel coordinates for use in visual information display as well as an interface for guiding and performing data mining operations, which are based upon multi-dimensional and temporal thresholding and data subsetting operations. To achieve very high performance on parallel computing platforms, we leverage FastBit, a state-of-the-art index/query technology, to accelerate data mining and multi-dimensional histogram computation. We show how these techniques are used in practice by scientific researchers to identify, visualize and analyze a particle beam in a large, time-varying dataset.
Date: August 28, 2008
Creator: Rubel, Oliver; Prabhat, Mr.; Wu, Kesheng; Childs, Hank; Meredith, Jeremy; Geddes, Cameron G.R. et al.
Partner: UNT Libraries Government Documents Department

FastBit: Interactively Searching Massive Data

Description: As scientific instruments and computer simulations produce more and more data, the task of locating the essential information to gain insight becomes increasingly difficult. FastBit is an efficient software tool to address this challenge. In this article, we present a summary of the key underlying technologies, namely bitmap compression, encoding, and binning. Together these techniques enable FastBit to answer structured (SQL) queries orders of magnitude faster than popular database systems. To illustrate how FastBit is used in applications, we present three examples involving a high-energy physics experiment, a combustion simulation, and an accelerator simulation. In each case, FastBit significantly reduces the response time and enables interactive exploration on terabytes of data.
Date: June 23, 2009
Creator: Wu, Kesheng; Ahern, Sean; Bethel, E. Wes; Chen, Jacqueline; Childs, Hank; Cormier-Michel, Estelle et al.
Partner: UNT Libraries Government Documents Department

Coupling Visualization and Data Analysis for Knowledge Discovery from Multi-dimensional Scientific Data

Description: Knowledge discovery from large and complex scientific data is a challenging task. With the ability to measure and simulate more processes at increasingly finer spatial and temporal scales, the growing number of data dimensions and data objects presents tremendous challenges for effective data analysis and data exploration methods and tools. The combination and close integration of methods from scientific visualization, information visualization, automated data analysis, and other enabling technologies"such as efficient data management" supports knowledge discovery from multi-dimensional scientific data. This paper surveys two distinct applications in developmental biology and accelerator physics, illustrating the effectiveness of the described approach.
Date: June 8, 2010
Creator: Rubel, Oliver; Ahern, Sean; Bethel, E. Wes; Biggin, Mark D.; Childs, Hank; Cormier-Michel, Estelle et al.
Partner: UNT Libraries Government Documents Department

VACET: Proposed SciDAC2 Visualization and Analytics Center forEnabling Technologies

Description: This paper accompanies a poster that is being presented atthe SciDAC 2006 meeting in Denver, CO. This project focuses on leveragingscientific visualization and analytics software technology as an enablingtechnology for increasing scientific productivity and insight. Advancesincomputational technology have resultedin an "information big bang,"which in turn has createda significant data understanding challenge. Thischallenge is widely acknowledged to be one of the primary bottlenecks incontemporary science. The vision for our Center is to respond directly tothat challenge by adapting, extending, creating when necessary anddeploying visualization and data understanding technologies for ourscience stakeholders. Using an organizational model as a Visualizationand Analytics Center for Enabling Technologies (VACET), we are wellpositioned to be responsive to the needs of a diverse set of scientificstakeholders in a coordinated fashion using a range of visualization,mathematics, statistics, computer and computational science and datamanagement technologies.
Date: June 19, 2006
Creator: Bethel, W.; Johnson, Chris; Hansen, Charles; Parker, Steve; Sanderson, Allen; Silva, Claudio et al.
Partner: UNT Libraries Government Documents Department

SciDAC Visualization and Analytics Center for EnablingTechnology

Description: The SciDAC2 Visualization and Analytics Center for EnablingTechnologies (VACET) began operation on 10/1/2006. This document, dated11/27/2006, is the first version of the VACET project management plan. Itwas requested by and delivered to ASCR/DOE. It outlines the Center'saccomplishments in the first six weeks of operation along with broadobjectives for the upcoming future (12-24 months).
Date: November 28, 2006
Creator: Bethel, E. Wes; Johnson, Chris; Joy, Ken; Ahern, Sean; Pascucci,Valerio; Childs, Hank et al.
Partner: UNT Libraries Government Documents Department

Occam's Razor and Petascale Visual Data Analysis

Description: One of the central challenges facing visualization research is how to effectively enable knowledge discovery. An effective approach will likely combine application architectures that are capable of running on today?s largest platforms to address the challenges posed by large data with visual data analysis techniques that help find, represent, and effectively convey scientifically interesting features and phenomena.
Date: June 12, 2009
Creator: Bethel, E. Wes; Johnson, Chris; Ahern, Sean; Bell, John; Bremer, Peer-Timo; Childs, Hank et al.
Partner: UNT Libraries Government Documents Department