This is an archival copy of the Visualization Group's web page 1998 to 2017. For current information, please vist our group's new web page.

Visualization Vignettes

Visualization plays an integral role in the scientific process - allowing a way to see the unseen by creating images of experimental data or theoretical simulation results. The projects listed on this page represent recent or current collaborative efforts between the CRD Data Analytics and Visualization Group and others performing scientific research in both simulation/computational and experimental sciences.

2017 |2016 |2015 |2014 | 2013 | 2012 | 2011 | 2010

2009 | 2008 | 2007 | 2006 | 2005 | 2004 | 2003 | 2002 | 2001 | 2000

1999 | 1998 | 1997 | 1993

2017

NWB:N -- Beta of Neurodata Without Borders 2.0 Format and Software Released

Image Credit: Oliver Ruebel

Neurodata Without Borders: Neurophysiology (NWB:N) is a project to develop a unified data format for cellular-based neurophysiology data. The NWB:N team consists of neuroscientists and software developers who recognize that adoption of a unified data format is an important step toward breaking down the barriers to data sharing in neuroscience. Neuroscientists can now explore a beta version of the new Neurodata Without Borders: Neurophysiology (NWB:N 2.0) software and format. The 2.0 software version was developed by Lawrence Berkeley National Laboratory's Oliver Ruebel and Andrew Tritt, in close collaboration with Kristofer Bouchard (Berkeley Lab), Loren Frank (UCSF), Eddie Chang (UCSF), and the broader Neurodata Without Borders (NWB) community. The beta update was released in November 2017 in conjunction with the 2017 Society for Neuroscience meeting in Washington D.C. last month.

For more information download the PDF of the poster by clicking on the image on the left and see the following LBNL news article. The NWB:N format schema and PyNWB Python API have been released to the public online on GitHub.

BASTet: Berkeley Analysis and Storage Toolkit

Image Credit: Oliver Ruebel

BASTet is a novel framework for shareable and reproducible data analysis that supports standardized data and analysis interfaces, integrated data storage, data provenance, workflow management, and a broad set of integrated tools. BASTet has been motivated by the critical need to enable MSI researchers to share, reuse, reproduce, validate, interpret, and apply common and new analysis methods.

For more information see the BASTet homepage as well as the IEEE TVCG article on BASTet. BASTet has been released to the public; Sources (GitHub) and the Online Documentation.

2016

2015

OpenMSI Receives R&D 100 Award

The OpenMSI software/service developed by Oliver Ruebel and Benjamin P. Bowen (LBNL) was selected as "One of the 100 Most Technologically Significant New Products of the Year in Software/Services."

For more information see the following LBNL news article. For a full list of award winners see here. OpenMSI has been released to the public and is available online at openmsi.nersc.gov

BrainFormat: A Data Standardization Framework for Neuroscience Data

Image Credit: Wikimedia Commons

Thanks to standardized image file formats---like JPEG, PNG or TIFF---people can easily share selfies and other pictures with anybody connected to a computer, mobile phone or the Internet, without having to download any special software to see the pictures. But in many science fields---like neuroscience---sharing data is not that simple because no standard data format exists. The BrainFormat library developed at LBNL specifies a general data format standardization framework based on the widely used HDF5 format and implements a novel file format for management and storage of neuroscience data, in particular Electrocorticography (ECoG) data.

For more information see the following LBNL news article as well as the Frontiers in Neuroinformatics article. The BrainFormat library has been released to the public and is available online at bitbucket.org

2014

Visible-Wavelength Polarized Light Emission with Small-Diameter InN Nanowires

Using NERSC's Cray XC30 supercomputer "Edison", University of Michigan researchers found that the semiconductor indium nitride (InN), which typically emits infrared light, will emit green light if reduced to 1 nanometer-wide wires. Moreover, just by varying their sizes, these nanostructures could be tailored to emit different colors of light, which could lead to more natural-looking white lighting while avoiding some of the efficiency loss today's LEDs experience at high power. Visualization and analysis of the simulation data were done using custom tools based on VTK, ParaView, and finally rendering the result with POVRay. The visualizations appeared on the cover of ACS Nano Letter, on NERSC web site, and were made into a stereoscopic 3D presentation for SC14. (More information)

Petascale Study of Ion Foreshock Dynamics

This research leverages petascale simulations of the Earth’s magnetosphere to study the physics and dynamics of space weather phenomenon. A radial interplanetary magnetic field(IMF) configuration was studied. Such configurations are common during high intensity solar storms when the solar wind becomes highly turbulent. The study is based upon one of the largest global simulations of the Earth's magnetosphere ever made. The simulation ran on 150,000 cores for 368 hours, for a total of approximately 55.2 Million core hours. The fields and derived quantities are kept on a 1024x2048x1024 grid, and 1 Trillion Particles were simulated. The simulation produced more that 128 TB of analysis data. The NERSC DAS group applied parallel visualization and analysis techniques using ParaView, VTK, and POVRay. Including interactive and batch volume rendering on Edison using ParaView on 256 cores, and batch mode ray tracing using POV-Ray on 36,000 cores. (More information)

2013

OpenMSI: A Science Gateway to Sort Through Bio-Imaging's Big Datasets

OpenMSI is a collaborative research effort with the goal to make the most high-performance, advanced data management, model building, analysis and visualization resources for mass spectrometry imaging accessible to scientists via the web. The development and application of cutting-edge analytical methods is a core driver for new scientific discoveries, medical diagnostics, and commercial-innovation. Mass spectrometry imaging (MSI) holds the promise for being a transformative technology for advanced studies of metabolic processes with broad applications in life sciences, bioenergy, and health. MSI enables fast assays of microbial metabolism essential in bioengineering problems common to the development of biofuels, drugs, and diagnostics for cancer and other diseases. While the data can be routinely collected, the broad application of MSI is currently limited by the lack of easily accessible analysis methods that can process data of the size, volume, diversity and complexity generated by MSI experiments. The OpenMSI project will overcome these challenges, allowing broad use of MSI to researchers by providing a web-based gateway for management and storage of MSI data, the visualization of the hyper-dimensional contents of the data, and the statistical analysis.

More information is available in the following LBNL and science.energy.gov news articles as well on the OpenMSI project website at openmsi.nersc.gov

2012

High Performance Visualization—Reference Book
	Visualization and analysis tools, techniques, and algorithms have undergone a rapid evolution in recent decades to accommodate explosive growth in data size and complexity and to exploit emerging multi- and many-core computational platforms. High Performance Visualization: Enabling Extreme-Scale Scientific Insight focuses on the subset of scientific visualization concerned with algorithm design, implementation, and optimization for use on today's largest computational platforms. (More information)
Streamline Integration using MPI-Hybrid Parallelism on a Large, Multi-Core Architecture
	Studies show the hybrid-parallel implementation of streamline integration, a key visualization algorithm, performs better and moves less data than a traditional MPI-only implementation. (More information)
Efficient Parallel Extraction of Crack-free Isosurfaces from Adaptive Mesh Refinement Data
	Efficient parallel extraction of crack-free isosurfaces from AMR data in a distributed memory setting. (More information)
MetroMaps: Map-based Representations for Analyzing Optimization Solution Spaces
	Using the Morse complex to understand energy functions in chemical systems. (More information)
Topological Cacti: Combining Structural and Quantitative Information
	Visualizing topological and quantitative information about isosurfaces. (More information)
Pattern Detection in Climate Data
	New algorithms and tools help climate scientists study extreme weather events like hurricanes using large, parallel computational platforms. (More information)
Parallel I/O, Analysis, and Visualization of a Trillion-Particle Simulation
	First-ever trillion-particle runs of a plasma physics code, the computer science research needed to enable this feat, and the science discoveries that result. (More information)
Performance Optimization and Auto-tuning
	Studies show up to a 30x performance gain is possible on some codes and platforms depending upon settings for tunable algorithmic parameters, algorithmic optimizations, and use of device-specific features. (More information)
High-throughput Characterization of Porous Materials
	The goal of this work is to enable high-throughput screening of large material databases to characterize material properties and enable fast identification of candidate materials for application-specific problems such as carbon capture. (More information)
Query-Driven Analysis of Large Scale Time-dependent Data
	Query-driven analysis based on single timestep queries is a versatile tool for the identification and extraction of temporally persistent and instantaneous data features. Many questions of interest ---such as, which particles become accelerated, which locations exhibit high velocities during an extended timeframe, which particles reach a local maximum energy, or which particles change their state--- inherently depend on information from multiple timesteps and cannot directly answered based on single-timestep queries alone. The goal of this effort is to extend our query-driven analysis capabilities to enable scientists to formulate time-dependent queries that accumulate information from multiple timesteps, here called cumulative queries. (More information)
Linking PointCloudXplore and Matlab: Making Advanced Analysis Easily Accessible
	Three-dimensional gene expression PointCloud data, generated by the Berkeley Drosophila Transcription Network Project (BDTNP), provides quantitative information about the spatial and temporal expression of genes in early Drosophila embryos at cellular resolution. The goal of this work has been to maximize the impact of BDTNP PointCloud data by integrating the visualization system PointCloudXplore with Matlab to: i) make PointCloud data easy to comprehend for developers, ii) to enable developers to deploy their analyses within the context of an advanced easy-to-use visualizations system, and iii) to make novel, advanced analyses capabilities easily accessible to biologist users. (More information)
High-performance Computing for Computational Finance
	The SEC and CFTC recently proposed the development of a Consolidated Audit Trail System (CATS), a next-generation system for market monitoring. The goal of our work has been to evaluate how high-performance computing can support financial data analysis and, in particular, the development and implementation of early warning systems for detection and analysis of market anomalies.. (More information)
Environmental Management: Hanford Site Nuclear Waste Clean-up
	The U.S. Department of Energy's (DOE) Office of Environmental Management (DOE/EM) supports an effort to understand and predict contaminant fate and transport in natural and engineered systems. Geologists, hydrologists, physicists and computer scientists are working together to create models of existing, contaminated sites, and to simulate their behavior. Simulation results are verified based on historical data and extrapolated into the future. Visualization is used for model setup verification, visual analysis of high-performance computing simulation results, and uncertainty quantification. The image depicts simulated Technetium-99 contamination under six cribs at the Hanford site (volume rendering). (More information) MPEG4 Movie clip (3.3MB).
Parallel Stream Surface Computation for Large Data Sets
	Stream surfaces, a useful flow visualization technique, are difficult to compute accurately and efficiently on large, parallel platforms. Our team has developed a new algorithm that addresses both of these challenges. (More information)
CO₂ Sequestration and Storage: From Raw Micro-CT to Quality Measurements
	Working closely with earth sciences researchers, we have developed a collection of algorithms and software tools that helps scientists to conduct quantitative analysis of 3D imaging data in order to better understand how to store CO₂ in geologic reservoirs. (More information)
Flying Through the Known Universe in 3D
	Berkeley Lab researchers created a 3D movie where the viewer flies through the known universe. (More information)

2011

Parallel Query-driven Analysis of Electron Linac Simulations
	Researcher of the Accelerator & Fusion Research Division at Lawrence Berkeley National Laboratory (LBNL) utilize large-scale, high-resolution simulations of beam dynamics in electron linacs for studies of a proposed next-generation x-ray free electron laser (FEL) at LBNL (external link). Particle-in-cell-based simulations of this type of accelerator require large numbers of macroparticles (> 10⁸) to control the numerical macroparticle shot noise and to avoid overestimation of the microbunching instability, resulting in massive particle datasets. The sheer size of the data generated by these types of simulations poses significant challenges with respect to data I/O, storage, and analysis. For more information on how we address these challenges see here.
Visualizing the Universe @100Gbps
	LBL Visualization group worked closely with ESnet personnel to showcase a real-time streaming demo at SC11. The demo was able to attain maximum bandwidth utilizaton on ESnet's 100Gbps link and showed a live data stream from NERSC to Seattle. (More information)
Environmental Management: Nuclear Waste Site Clean-up
	The U.S. Department of Energy's (DOE) Office of Environmental Management (DOE/EM) supports an effort to understand and predict contaminant fate and transport in natural and engineered systems. Geologists, hydrologists, physicists and computer scientists are working together to create models of existing, contaminated sites, and to simulate their behavior. Simulation results are verified based on historical data and extrapolated into the future. Visualization is used for model setup verification, visual analysis of high-performance computing simulation results, and uncertainty quantification. The image depicts contamination under the Savannah River F-area basin as a contour plot over time along with a terrain model (structured mesh with elevation data) and well sites. (More information) MPEG4 Movie clip (341MB).
Exploring How Advanced Architectures Can Accelerate Flow Visualization
	(More information)

2010

Analysis of Void Space of Porous Materials Used in Energy-related Applications
	We have developed partial differential equations-based tools that perform analysis of porous materials. These tools involve the application of the Fast Marching Method (FMM) to predict if a molecule can traverse through a channel system representing void space of the materials, map accessible parts of these void spaces and calculate accessible volumes and surfaces. (More information) MPEG4 Movie clip (2MB).
Unveiling the Interior of 3D Micro-CT from Iron-Sand Composite
	In this project, we apply computer vision techniques to Micro-CT datasets with the eventual goal of characterizing materials for carbon sequestration. (More information) MPEG4 Movie clip (2MB).
Visualizing Type Ia Supernova Explosions
	Deep inside a dying star in a galaxy far, far away, a carbon fusion flame ignites. Ignition may happen in the middle or displaced slightly to one side, but this simulation explores the consequences of central ignition. In a localized hot spot, represented here by a deformed sphere with an average radius of 100 km, carbon is assumed to have already fused to iron, producing hot ash (~10 billion K) with a density about 20% less than its surroundings. As the burning progresses, this hot buoyant ash rises up and interacts with cold fuel. Rayleigh-Taylor fingers give rise to shear and turbulence, which interacts with the flame, causing it to move faster. In about 2 seconds, the energy released blows the entire white dwarf star up, leaving nothing behind but a rapidly expanding cloud of radioactive nickel, iron, and other heavy elements. A Type Ia supernova is born. Credits: produced by Hank Childs of VACET in conjunction with members of the Computation Astrophysics Consortium (CAC): Haitao Ma and Stan Woosley of UC Santa Cruz, and John Bell, Ann Almgren, and Andy Nonaka of LBL. MPEG4 Movie clip (48MB).
Buoyant Burning Bubbles in Type Ia Supernovae
	Flame ignition in type Ia supernovae leads to isolated bubbles of burning buoyant fluid. As a bubble rises due to gravity, it becomes deformed by shear instabilities and transitions to turbulent evolution. This simulation shows the temperature field of such a bubble burning in a uniform background. The simulation was conducted using a specialized low Mach number hydrodynamics code for thermonuclear flames. Adaptive mesh refinement was used to focus resolution on the bubble, reducing computational expense. The effective resolution was 4096^3. Research and Visualization courtesy of Andy Aspden and John Bell (LBNL). (More information) MPEG movie (1MB)
Turbulent Jets with Off-Source Heating
	Latent heat release associated with condensation during cloud formation leads to enhanced buoyancy in atmospheric plumes, and results in anomalous entrainment behavior. These simulations are based on the laboratory experiment of Bhat and Narasimha (1996) who injected an acidic jet into a deionized ambient, and used electrodes to selectively heat the jet fluid, analogous to condensation. The simulations were conducted with CCSE's incompressible Navier-Stokes solver (IAMR), and shows the tracer fluid. Adaptive mesh refinement was used to focus resolution on the jet fluid, reducing computational expense. The effective resolution was 512 x 512 x 768. Analysis of the data shed light on the complex feedback mechanism between heating, turbulence and entrainment. Research and Visualization courtesy of Andy Aspden and John Bell (LBNL). (More information) MPEG movie (3MB)
Hurricane Season
	Visualization of hurricane formation and evolution. (More information) MPEG movie (40MB)
Visualization of Jablonowski Test Case
	Visualization of the Jablonowski test case on a geodesic grid. We plot temperature and vorticity fields. (More information) MPEG movie (20MB)
GPU Implementations of 3D Image Denoising Filters
	Denoising is a important step in many image processing pipelines for brain magnetic resonance imaging (MRI). Using GPUs, we have accelerated the runtime for two 3D filters, the bilateral filter and the anisotropic diffusion filter, that remove noise and smooth features within MR images while at the same time preserving edges. (More information)
Hybrid Parallelism for Volume Rendering at Large Scale
	We studied the performance and scalability characteristics of ``hybrid'' parallel programming and execution as applied to raycasting volume rendering — a staple visualization algorithm — on a large, multi-core platform. Our findings indicated that the hybrid-parallel implementation, at levels of concurrency ranging from 1,728 to 216,000, performs better, uses a smaller absolute memory footprint, and consumes less communication bandwidth than the traditional, MPI-only implementation. (More information)

2009

Smashing the Trillion Zone Barrier

LBL visualization researchers helped lead an effort to test the scalability limits of production visualization software on very large data sets, including meshes with trillions of grid points. (More information)

Analysis of Laser Wakefield Particle Acceleration Data

In collaboration with researchers of the LOASIS program (LBNL) and the SciDAC SDM center (LBNL) we have been working on various efforts aimed at improving the analysis of laser wakefield particle acceleration data. This page provides and overview of these various efforts. (More information)

Visit also the other related vignette pages with more detailed information about the individual efforts.

High-performance interactive visualization of LWFA simulations
Automatic Beam Path Analysis of LWFA data
Automatic Beam Detection
Laser Wakefield Particle Acceleration

Automatic Beam Path Analysis of LWFA data

Numerical simulations of laser wakefield particle accelerators play a key role in the understanding of the complex acceleration process and in the design of expensive experimental facilities. As the size and complexity of simulation output grows, one main challenge is the need for computational techniques that aid in scientific knowledge discovery. The automatic beam path analysis consists of a set of data-understanding algorithms that work in concert in a pipeline fashion to automatically locate and analyze high energy particle bunches undergoing acceleration in very large simulation datasets. (More information)

This vignette is part of an ongoing collaboration with the LOASIS program at LBNL. For an overview of the various efforts within that project see here.

Visualization of Microearthquake Data from Enhanced Geothermal Systems

cut-out of 3D visualization of microearthquake data
from The Geysers geothermal field in California

We are working with geophysicists in the Earth Sciences Division (ESD) at LBNL to generate 3D visualizations of microearthquake data from geothermal sites. The importance of this work is that it provides the means for the geothermal site operators - and the public - to see where microearthquakes are occurring as geothermal energy is produced at a site. The 3D visualizations are being made available via a Web site hosted by the ESD.

More information.

PointCloudXplore: Visualization and Analysis of 3D Gene Expression Data

In collaboration with the BDTNP at LBNL and IDAV at UC-Davis we developed PointCloudXplore, a visualization system designed for the analysis of 3D gene expression data. PointCloudXplore supports advanced physical and abstract visualizations linked via the concept of cell selection. The user can select cells of interest in any view and investigate further properties of the selected cells in any other view. The BDTNP has made PointCloudXplore available for download free of charge via their webpage. (More information)

Visualization of Quantum Monte-Carlo simulations

NERSC Analytics personnel are supporting researchers at UC Berkeley and LBNL in aiding visualization of quantum monte-carlo simulations. We developed VisIt plugins to import CUBE and XML formats and generated visualizations demonstrating the interplay of electron densities, trajectories and energy configurations. (More information)

Global Cloud Resolving Models

Climate researchers led by Dave Randall (CSU) are developing a novel Global Cloud Resolving Model based on a geodesic grid. We are supporting Dave Randall and collaborators from PNNL in facilitating high-performance I/O on franklin; developing a data model for the geodesic grid and developing plugins in VisIt to handle the large simulation datasets. (More information)

2008

High-performance interactive visualization of LWFA simulations
	Analysis of laser wakefield particle acceleration data is a challenging task. Our approach combines and extends techniques from high performance scientific data management and visualization, enabling researchers to gain insight from extremely large, complex, time-varying laser wakefield accelerator simulation data. We extend histogram-based parallel coordinates which we use as visual information display and interface for guiding and performing data mining operations. We use multi-dimensional thresholding as vehicle for selecting particles of interest at a particular timepoint. We use FastBit, a state-of-the-art index/query system for data extraction and subsetting. (More information) This vignette is part of an ongoing collaboration with the LOASIS program at LBNL. For an overview of the various efforts within that project see here
Visualization of large-scale GFDL/NOAA climate simulations
	NERSC Analytics personnel supported climate scientists from GFDL/NOAA in running large scale runs of their next generation CM2.4 and c180 models at very high resolutions. In order to efficiently render the large datasets, VisIt plugins were developed for the file formats. Custom visualizations depicting phenomena of interest (hurricane formation, etc) were also developed. More information.
Direct Numerical Simulation of Turbulent Flame Quenching by Fine Water Droplets
	NERSC Analytics staff supported Incite12 collaborators in using VisIt for analyzing their simulation runs. We resolved a number of data import issues and enabled generation of publication-quality images. A number of tutorials on using VisIt for simulation data are provided. More information.

2007

Visualization of Magneto-rotational instability and turbulent angular momentum transport
	This project, led by by Fausto Cattaneo, University of Chicago, used a previous allotment of 2 million processor-hours to study the forces that help newly born stars and black holes increase in size. In space, gases and other matter often form swirling disks around attracting central objects such as newly formed stars. The presence of magnetic fields can cause the disks to become unstable and develop turbulence, thereby causing the disk material to fall onto the central object. This run at NERSC was used to set up initial conditions for a larger scale simulations. The Visualization Group assisted this project in generating High-quality visualizations of data produced in these runs. Based on these initial results, the project continues to carry out large-scale simulations to test theories on how turbulence can develop in such disks. (More information)
Visualization Research
	One fundamental element of scientific inquiry is the discovery of relationships. We have developed a new technique suitable for computing and displaying relationships, thereby accelerating knowledge discovery in large and complex scientific datasets. (More information)
Sunfall: Visual Analytics for Astrophysics
	The Visualization Group participated in the design and implementation of Sunfall, a collaborative visual analytics system for the Nearby Supernova Factory (SNfactory), the largest data volume supernova search currently in operation. Sunfall utilizes interactive visualization and analysis techniques to facilitate insight into complex, noisy, high-dimensional, high-volume, time-critical data. The image at left is from the "supernova details view" from the Supernova Warehouse, one component of Sunfall. The details view enables access to photometric supernova images, spectral data, lightcurves, and associated metadata. More information.
Fusion: NIMROD HDF5 VisIt Plugin
	The Visualization group is writing a NIMROD HDF5 database plugin for VisIt (http://www.llnl.gov/visit). The plugin can be recompiled in unix platforms to use with a local version of VisIt or it can be used directly in davinci.nersc.gov. The HDF5 data model is specified in the Fusion Simulation Markup Language (FSML) project. More information.
SciDAC Computational Astrophysics
	This project, "When Good Stars Go Bang", is part of the SciDAC Computational Astrophysics Consortium studying supernovae, gamma-ray bursts, and nucleosynthesis More information.

2006

Fast Contour Descriptor Algorithm for Supernova Image Classification
	Members of the Visualization Group collaborated on the development of a fast contour descriptor algorithm which was applied to a high-volume supernova detection system (the Nearby Supernova Factory) Our shape-detection algorithm reduced the number of false positives generated by the supernova search pipeline by 41% while producing no measurable impact on running time. Because the number of Fourier terms to be calculated is fixed and small, the algorithm runs in linear time, rather than the O(n log n) time of an FFT. More information.
Supernova Recognition Using Support Vector Machines
	This work demonstrates the great potential impact that supervised learning has to improve the efficiency of large-scale digital sky surveys that are slated to collect terabytes of nightly imagery in search of celestial objects (SNAP, LSST, DES, Pan-STARRS). The Nearby Supernova Factory (SNfactory) is an international project to obtain spectrophotometry data on a large sample of Type Ia supernovae in a nearby redshift range in order to measure the expansion history of the universe. Members of the Visualization Group have used supervised learning techniques (Support Vector Machines (SVMs), boosted decision trees, random forests) to automatically classify all incoming subimages on a nightly basis and rank-order them by the classifier decision value, allowing astrophysicists to quickly examine the 20 or so most promising candidates arriving each morning. More information.
Laser Wakefield Particle Acceleration
	Particle-in-Cell Simulation of Laser Wakefield Particle Acceleration: A 2006 INCITE Project. This project, led by Cameron Geddes of Berkeley Lab, was awared 2.5 million hours to perform detailed 3D models of laser-driven wakefield particle accelerators. These plasma-based accelerators are not subject to electrical breakdown and have demonstrated accelerating gradients thousands of times those obtained in conventional accelerators. The particle-in-cell simulations proposed in this study will interpret recent experiments and assist in the planning of the next generation of particle accelerators and ultrafast applications in chemistry and biology. More information. This vignette is part of an ongoing collaboration with the LOASIS program at LBNL. For an overview of the various efforts within that project see here
SciDAC2 Visualization and Analytics
	A fundamental aspect of large-scale, data-intensive computational and experimental science is the ability to quickly gain knowledge from large and complex collections of scientific data. To respond to this challenge, we have assembled a leading team of researchers and developers to tackle this very problem over a five-year period as part of DOE's SciDAC2 program. This effort marks the first SciDAC Visualization Center, and will play a key role in scientific knowledge discovery in the latter half of the first decade of the 21st Century. At the 2006 SciDAC meeting in Denver, CO held during June 2006, we presented a white paper and poster describing out team's approach.
Biophysics
	Cryo-EM and single molecule biophysical studies of dsDNA packaging in Bacillus subtilis bacteriophage Phi 29. Luis R. Comolli 1, Andrew Spakowitz 2, Cristina E. Siegerist 1, Shelley Grimes 3, Paul Jardine 3, Kenneth H. Downing 1, Dwight Anderson 3 and Carlos Bustamante 1,2. 1 Lawrence Berkeley National Laboratory, 2 Physics Department, University of California at Berkeley, 3 Academic Health Center, University of Minnesota.
High Performance Visualization — Query-Driven Network Traffic Analysis
	Query-driven visualization plays an important role in high performance visualization and data-intensive knowledge discovery. This case study explains the technology and shows how it is applied to a "hero-sized" network traffic analysis problem. More information. E. Wes Bethel (CRD/LBNL), Scott Campbell (NERSC/LBNL), Eli Dart (ESnet/LBNL), Kurt Stockinger (CRD/LBNL), Kesheng (John) Wu (CRD/LBNL).
Climate Modeling
	This plot is a 3D view of 6000 months of net primary productivity, 2m air temperature and soil moisture at Harvard Forest generated by a coupled climate model (CSM1.4+Carbon) with biogeochemistry component in the land model. Yun Helen He, LBNL
Physical Chemistry: Journal Cover
	Computational studies of molecular hydrogen binding affinities: The role of dispersion forces, electrostatics, and orbital interactions , Rohini C. Lochan and Martin Head-Gordon, Physical Chemistry Chemical Physics, 2006, 8, 1357 - 1370 Rohini Lochan, Martin Head-Gordon, UC Berkeley

2005

Beam Dynamics: new images of particle tracking
	More images. Andreas Adelmann, PSI
Visualization of Magneto-rotational instability and turbulent angular momentum transport
	In space, gases and other matter often form swirling disks around attracting central objects such as newly formed stars. The presence of magnetic fields can cause the disks to become unstable and develop turbulence, thereby causing the disk material to fall onto the central object. This project carries out large-scale simulations to test theories on how turbulence can develop in such disks. More information on this project. For more information on the NERSC 2005 Incite projects click here Fausto Cattaneo et al. University of Chicago
Life Sciences: Cell Division of Caulobacter Crescentus.
	Composite image showing original 2D cryo electron microscopy image (center) and membrane models and volume rendering of the 3D recontruction (right upper corner and left lower corner). More information. Ken Downing, Luis Comolli, LBNL.
Combustion: Rod-stabilized V-flame
	Curvature of a premixed combustion front. CCSE web page. More images J.Bell et al., CCSE, LBNL
Electron Cloud Simulations
	This image shows a proton beam moving along the beam pipe (z-axis) in the presence of an electron cloud. The proton beam is shown in red in the center of the pipe. The model, incomplete, you will see no velocity component for the electrons along the z-axis, was a first approximation to model the proton-electron interaction in the beam line. The pipe is colored by the electron density, the same information is shown in the upper graph. MPEG Movie of the simulation (4.8MB). More images soon. A. Adelmann, PSI
Fluid Turbulence
	Visualization of Fluid Turbulence using AVS/Express, CEI/Ensight and Paraview. More images. P.K.Yeung, D.Donzis, Georgia Tech
Electron Pair Localization Function Visualization
	EPLF of F2 More information. W.Lester, UC Berkeley

2004

Incite3: Fluid Turbulence
	Visualization Helps Provide Insight into 3D Fluid Turbulence and Mixing at High Reynolds Number. More information.
Incite1: Quantum Chemistry
	Visualization of Electron Walkers Computed by Quantum Monte Carlo Simulation of Energy Pathways in Photosynthesis Reactions More information.
Delivering Interactive, 3D Visualization to the Desktop
	The MBender project explores the use of QuickTime VR Object Movies to deliver interactive, 3D scientific visualization to the desktop in a remote and distributed visualization setting. More information.
Adaptive Mesh Refinement Visualization
	Adaptive Mesh Refinement (AMR) is a technique for automatically refining (or de-refining) regions of a computational domain during a numerical calculation based upon application-specific criteria, like flamefront tracking during a combustion simulation. The multiresolution and hierarchical nature of AMR grids presents special challenges for mainstream visualization tools, which typically can operate only on single grid domains. At SC04, the LBNL Visualization Group will show ongoing AMR visualization activities. First, LBNL's hardware-accelerated volume renderer is being used to create images for a PBS special movie on cosmology. Second, the group will demonstrate use of custom data converters that permit AMR grids to be visualized using CEI's Ensight and LLNL's Visit, both of which are applications that implement a pipelined/parallel architecture and are effective in remote and distributed visualization contexts. More information.
Tomography - 3D Reconstruction
	Cryo-electron microscopy Reconstruction of tomographic data from a tilt series of images using cryo-electron microscopy. Click here for details Ken Downing's Lab, LBNL
AVS/Express ModelBuilder
	Model Builder ModelBuilder is an application to build a model of surfaces from 3D volume data (uniform mesh). Click here for details .
SciDAC: Terascale Computational Atomic Physics for Controlled Fusion Energy
	Visualization of Computational Atomic Physics for Fusion Atomic physics plays a central role in many of the high temperature and high density plasmas found in magnetic and inertial confinement fusion experiments, which are crucial to our national energy and defense interests, as well as in technological plasmas important to the US economic base. In turn, the development of the necessary atomic physics knowledge depends on advances in both experimental and computational approaches. The Computational Atomic Phyics for Fusion SciDAC project hosted at NERSC is producing early results simulating time evolution of a wavepacket scattering from a Helium atom. Click here for details. M. Pindzola, Auburn University.
Accelerator Modeling SciDAC
	Particle Viewer, PartView PartView is a lightweigth application to preview results of beam dynamics simulations. Click here for details John Shalf, Cristina Siegerist, CRD/LBNL Andreas Adelmann, PSI
Protein Folding
	Protein energy minimization using OPT++. The AMBER empirical energy of protein t209 was minimized using OPT++. In this visualization, the atoms are colored according to their displacement on consecutive minimization iterations. Folding evolution MPEG movies: t209(13M), t209(27M), t209(27M), t209 backbone(26M), t209 log color scale(27M), t209 log color scale no box(27M) Ricardo Oliva, Juan Meza, Silvia Crivelli, CRD/LBNL more images.
Fusion
	Visualization of 3D surface vector data from a plasma flow simulation on an irregular grid with AVS/Express. The AVS/Express streamlines or advector modules do not display streamlines of a vector field on a 2D surface in 3D space, binning the field to a uniform 3D grid allowed the user to visualize streamlines in the 2D surface. D. Spong, ORNL more images.
Electron Cloud Simulation
	Trajectories of electrons selected interactively with a box widget in the projection of the last simulation step along the z direction. The proton beam is rendered as volume density data. The trajectories are rendered as splines colored by the magnitude of the velocities. more images. A. Adelmann, PSI
	Electron cloud rendered as volume density and proton beam rendered as particles (MPEG, 5.8M) (Quick Time, 84M). The color bar on the left encodes the magnitude of the proton velocities and the one on the left the density of electrons. more images. A. Adelmann, PSI
	Electron cloud and proton beam rendered as particles (MPEG, 5.8M) more images. A. Adelmann, PSI
Computational Spin Dynamics
	Monte Carlo simulation of the D'yakonov-Perel' spin relaxation mechanism: Simulation showing the time evolution of the individual spins of an ensemble of 169 electrons in a zincblende. The local effective magnetic fields (white) and the precessing spins (green) are shown subject to pseudorandom scattering events as determined from Monte Carlo techniques. The time dependence of the three components of the total magnetization is shown in the line graph. Movies are presented for a [001] substrate with structural inversion asymmetry (SIA) effects only (MPEG), bulk inversion asymmetry (BIA) and SIA when these effects have equal magnitude (MPEG), and for a [111] substrate with, again, BIA and SIA effects equal, where the spin lifetime of all three components is enhanced (MPEG). more images. Xavier Cartoixà, LBNL, David Z.-Y. Ting, JPL

2003

Computational Astrophysics
	Continuing the work with the calculation of a supernova atmosphere for different geometries. Simulation of photons emitted from the supernova. To see a small test MPEG movie of the emission of photons click here (29M). For a larger MPEG click here (132M). A montage of the emission of photons and the spectrum is here. more information more images. P.Nugent, D.Kasen, LBNL
Fusion
	more images. PPPL

Computational Astrophysics
	Continuing the work with the calculation of a supernova atmosphere for different geometries. Flux as a function of viewing angle QuickTime(133M). QuickTime(74M) MPEG(1.5M) more images. P.Nugent, D.Kasen, LBNL

Protein Folding
	Protein energy minimization using OPT++. The AMBER empirical energy of protein 1e0m was minimized using OPT++. In this visualization, the atoms are colored according to their displacement on consecutive minimization iterations. The initial configuration was constructed using ProteinShop. Folding evolution MPEG movies: with backbone(22M) and without backbone(21M), QuickTime movies: with backbone(133M) and without backbone(127M). MPEG movie colored with the absolute distance with respect to the initial position. Ricardo Oliva, Juan Meza, Silvia Crivelli, CRD/LBNL more images.
	Protein energy minimization using OPT++. The AMBER empirical energy of protein T162 was minimized using OPT++. Folding evolution MPEG. Ricardo Oliva, Juan Meza, Silvia Crivelli, CRD/LBNL more images.
Simulations
	Accumulated Activity of 1D heterogeneous diffusion. Time Evolution Mpeg Salil Akerkar, University of Arizona more images

2002

Accelerator Modeling SciDAC
	Simulation Studies of Beam Dynamics: Simulation showing halo particles being tracked backwards in an accelerator to their starting points. Such simulations and associated visualizations provide insight into the halo formation mechanism in high intensity beams. Color encodes the magnitude of the velocity of the particles. (MPEG) A.Adelmann, LBNL more images
	Simulation Studies of Beam Dynamics: Time dependent density isosurfaces of a particle beam injected into an accelerator. The spiral arms show the result of the interaction of the beam with the environment. (MPEG) A.Adelmann, LBNL more images
	May 2002. Large scale simulations performed on NERSC's IBM/SP supercomputer help accelerator physicists understand the electromagnetic interaction between beams in a collider. These figures show a collision between two bunches of particles. (MPEG) See below for more information. J.Qiang, R. Ryne, LBNL more images new collision images
	March 2002. New work with the Beam Simulation data shows the time evolution in the x-PhaseX (MPEG) plane and in the y-PhaseY plane (MPEG) for 409 time steps. The color encoding shows the magnitude of the velocities. More information. JQiang, R. Ryne, LBNL
Imaging and Visualization
	2002 Summer Research Sample Results on 3D Morphing (MPEG) M.Eser, B. Parvin, LBNL
	This visualization shows the automatic detection of cell structures and localization of protein expression from a volumetric dataset. This is an important step in large scale analysis of cultured colonies and understanding their intercellular interactions. The focus of this initial study is to determine the frequency of gap junction protein complexes as a function of various treatments. For more information: Examples of low dose radiation studies Click on the image to see a 360 degree view of the dataset. Bahram Parvin, Staff Scientist, LBNL
Computational Astrophysics
	Simulation of the collapse of iron cores in the explosion of a supernovae. The image represents the entropy values during a particular timestep of a supernova formation. Salil Akerkar, University of Arizona
	There is mounting evidence that galaxy interactions play an important role in galaxy evolution. Elliptical galaxies, spiral bulges, and a significant fraction of all the stars in the universe may be byproducts of galaxy mergers, especially mergers at high redshift. Hydrodynamical simulations of galaxy interactions have given evidence of the role mergers play in galaxy evolution, but the galaxies used in these simulation have primarily been of equal mass, with low gas fractions typical of spiral galaxies in the local universe. In order to better understand the roles mergers play in galaxy evolution we are using high resolution simulations, including hydrodynamics and star formation, to investigate the full parameter space of pre-merger galaxy properites and interaction parameters. A main goal of our work is modeling the star formation rates and the morphology of interacting galaxies in various wavelengths. Time evolution MPEGs of Gas stars with sfr > 0 zoomed, zoomed with a reference grid, not zoomed. Time evolution of all Gas stars MPEG . Time evolution of the trayectories of stars MPEG . J. Primack, Thomas Cox, UCSC more images
	These figures show a spectrum synthesis calculation of a supernova atmosphere surrounded by a toroid. The layout of the atmosphere is presented on the right while at the left we have a graph of the flux vs. wavelength vs. viewing angle (Figure A) and of the polarization vs wavelength vs. viewing angle (Figure B). For viewing angles where the toroid obscures the underlying atmosphere, a strong absorption feature appears in the flux spectrum. Observations of such a feature allows one to determine the 3-dimensional geometry of the supernova ejecta, and hence put strong constraints on the progenitors and explosion physics of Type Ia supernovae. Flux as a function of viewing angle MPEG. Polarization as a function of viewing angle MPEG. P.Nugent, D.Kasen, LBNL more images
Materials Sciences
	Surface Physics. S.Tomassone, Rugters University more images
Earth Sciences
	Montmorillonite is a common clay mineral with a layered structure and a range of permanent negative charge which allows cations and water molecules to enter the space between clay layers, also known as the interlayer. Click on the image to see a 50 ps portion of a molecular dynamics simulation of the interlayer region of Cs-montmorillonite. More information. R.Sutton and G.Sposito, UC Berkeley

2001

	This figure shows three electron microscope images of DNA toroids accompanied by computer simulations of toroids in corresponding orientations. This work is motivated by interest in the behavior of DNA, which is sometimes naturally packed into toroidal arrays, and has application for DNA packing in genetic therapies. More information. Ken Downing, Life Sciences Division
	This image shows a 3-D reconstruction of an intact microtubule, obtained using cyro-electron microscopy and image processing at a resolution of about eight Angstroms. Microtubules play fundamental roles throughout the life of eukaryotic cells. More information. Ken Downing, Life Sciences Division
	The nonlinear Schrodinger equation (NLS) is a ubiquitous equation that naturally arises in weakly nonlinear systems whose wave dispersion relation is also a function of amplitude. It is an ideal testing ground for quantum lattice gas algorithms because exact solutions are known for the NLS equation. In particular, some of these exact solutions are solitons - nonlinear localized wavepackets that retain their identity even after collisions with other wavepackets. Click on the image to see the time evolution of two soliton-like intial conditions under the NLS equation with potential V = \|psi\|. The two solitons are unstable and break up resulting in coherent structures(solitons) interacting with a turbulent sea of very small amplitude solitons. The collisions of the coherent structures do not destroy these structures. George Vahala, Physics Dept., William & Mary
	The LEDA experiment is an experiment at Los Alamos National Laboratory to study the generation of halo particles in a periodic transport system. These images and the movie clips: rotating view of a time step MPEG, time evolution MPEG, show the particle phase space (i.e. particle positions and transverse velocities), computed using IMPACT, for the beam propagating in the LEDA Halo Experiment. The colorbar shows the encoding of the magnitude of the velocities. More information. R. Ryne and J.Qiang, LBNL
	Electron-Atom and Electron-Molecule Collision Processes. Click here for more information. C. William McCurdy et al.

2000

This 28 MB movie shows a time-evolving visualization of a numerical Tokomak simulation. (We found this movie in the dust bin, and are unable to provide appropriate citation information. If you know something about his work, please let us know and we'll provide the appropriate citation.) It was most likely computed by a research from the Princeton Plasma Physics Laboratory on a NERSC machine, with visualization performed by the LBL/NERSC Visualization Group.

Visualizing the Interactions of Two Fluids, The goal was to develop a tool to view two interacting fluid species at one time for a NERSC user at the College of William & Mary. The final product was to create movies so that the time dependent nature could be studied. The final tool was written in IDL and the tool and documentation was released to the user. Some examples movies are:

: Plot of one fluid (energy.1): plot_surf,'energy.1'; Plot of one energy.1 & energy.2 and scaling the mins and maxs. plot_surf,'energy.1','energy.2',/noscale,nsteps=600,file1=[.2,.7]
Other movies: vort_1.mpg, vorts_noscale.mpg, vorts_scale.mpg.

George Vahala, Physics Dept., William & Mary

1999

	Semi-local cosmic string simulation performed at NERSC. More information. Julian Borrill, NERSC
	An understanding of Cs-smectite systems is necessary to predict the permeability of clay liners at nuclear waste containment facilities to 137-Cs radioactive waste. More information. Rebecca Sutton, UCB, and Gary Sposito, UCB/LBNL

1998

	This image, which appeared on the cover of Forbes ASAP magazine in 1998, shows the "data fusion" resulting from visualization of simulated and theoretical protein models. Using high performance visualization tools and Virtual Reality interfaces, we explore model rectification and comparison. More information. Ken Downing, UC Berkeley and LBNL.
	The overall goal of this visualization is to highlight the differences between "layers" of molecular movement. In particular, molecules closer to the surface (towards the top of the picture) appear to move more than those further away from the surface (lower in the picture). More information.
	More information.
	These images show a theoretical chemical reaction: the dehydrogenation of ethylene. Two H atoms are removed from the ethylene C2H4 molecule upon interaction with a substrate of Nickel. More information. Michel Van Hove, Lawrence Berkeley National Laboratory
	Researchers at Northwestern University are studying the enzyme beta-lactamase. Specifically, the research is focused upon uncovering the specific molecular mechanisms employed by the enzyme to hydrolyse penicillin G, thus rendering it biologically inactive. More information. Paul Bash, Northwestern University

1997

	This project focused on visualization of quantum physics simulation data generated on the (then) new Cray T3E at NERSC. More information. G. Kilcup, The Ohio State University.
	In a 1997 LDRD, Karsten Pruess (Earth Sciences Division, LBNL) and George Brimhall (Geophysics, UC Berkeley) studied and modeled geophysical and geochemical processes that resulted in an ore body of particular interest in the desert of the Andes Mountains in the El Salvador district of Chile. The images presented on this page show a collaboration with the Visualiztion Group. More information. K. Pruess, LBNL and G. Brimhall, UCB.
	Reservoir characterization involves predicting production. Production is a function of geophysical and geochemical parameters. Typically, these parameters are estimated from samples. The challenge is better predictions of these unknowns, as well as better tools for calculating production given a set of parameters. Two separate projects were demonstrated at Supercomputing 1997 in San Jose, CA. More Images. Don Vasco, Earth Sciences Division, LBNL.
	Spring 1997: The VisGroup is working with scientists in ESD to create a visualization showing the Yucca Mountain storage facility. This visualization integrates divergent types of data, and will be used to ask "what if" questions pertaining to water flow through the site. Look for this model soon in in LBNL's Washington DC office. More information. Mark Feighner, Earth Sciences Division, LBNL.
	Material Science research relies heavily on the use of Nuclear Magnetic Resonance (NMR) to study materials. Researchers at LBNL and UC Berkeley are working with the Visualization Group to explore the results of computer simulations of NMR physics run on the NERSC T3E. More information. Bernd Pfrommer, UCB/LBNL.
	Radiation damage to DNA and the repair thereof is being investigated at LBNL by the Department of Radiation Biology and DNA Repair in the Life Sciences Division. Data sets contain tens of thousands atoms are generated. Hierarchical methods of visualization are being investigated on these data sets. More information. Saira Mian, Bill Holley, Life Sciences Division, LBNL
	Reservoir characterization involves predicting production. Production is a function of geophysical and geochemical parameters. Typically, these parameters are estimated from samples. The challenge is better predictions of these unknowns, as well as better tools for calculating production given a set of parameters. Two separate projects were demonstrated at Supercomputing 1997 in San Jose, CA. More Information. Don Vasco, Earth Sciences Divsion, LBL

1993-94

Our earliest work in combining scientific visualization, virtual reality and scientific computing occured in late 1992 and early 1993 with researchers from LBL's Earth Science Division. More information.