Dynamisk visualisering av rymdvädersimuleringsdata - PDF

LiU-ITN-TEK-A-14/009-SE Dynamisk visualisering av rymdvädersimuleringsdata Victor Sand Department of Science and Technology Linköping University SE Norrköping, Sweden Institutionen för

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LiU-ITN-TEK-A-14/009-SE Dynamisk visualisering av rymdvädersimuleringsdata Victor Sand Department of Science and Technology Linköping University SE Norrköping, Sweden Institutionen för teknik och naturvetenskap Linköpings universitet Norrköping LiU-ITN-TEK-A-14/009-SE Dynamisk visualisering av rymdvädersimuleringsdata Examensarbete utfört i Medieteknik vid Tekniska högskolan vid Linköpings universitet Victor Sand Handledare Alexander Bock Examinator Anders Ynnerman Norrköping Upphovsrätt Detta dokument hålls tillgängligt på Internet eller dess framtida ersättare under en längre tid från publiceringsdatum under förutsättning att inga extraordinära omständigheter uppstår. Tillgång till dokumentet innebär tillstånd för var och en att läsa, ladda ner, skriva ut enstaka kopior för enskilt bruk och att använda det oförändrat för ickekommersiell forskning och för undervisning. Överföring av upphovsrätten vid en senare tidpunkt kan inte upphäva detta tillstånd. All annan användning av dokumentet kräver upphovsmannens medgivande. För att garantera äktheten, säkerheten och tillgängligheten finns det lösningar av teknisk och administrativ art. Upphovsmannens ideella rätt innefattar rätt att bli nämnd som upphovsman i den omfattning som god sed kräver vid användning av dokumentet på ovan beskrivna sätt samt skydd mot att dokumentet ändras eller presenteras i sådan form eller i sådant sammanhang som är kränkande för upphovsmannens litterära eller konstnärliga anseende eller egenart. För ytterligare information om Linköping University Electronic Press se förlagets hemsida Copyright The publishers will keep this document online on the Internet - or its possible replacement - for a considerable time from the date of publication barring exceptional circumstances. The online availability of the document implies a permanent permission for anyone to read, to download, to print out single copies for your own use and to use it unchanged for any non-commercial research and educational purpose. Subsequent transfers of copyright cannot revoke this permission. All other uses of the document are conditional on the consent of the copyright owner. The publisher has taken technical and administrative measures to assure authenticity, security and accessibility. According to intellectual property law the author has the right to be mentioned when his/her work is accessed as described above and to be protected against infringement. For additional information about the Linköping University Electronic Press and its procedures for publication and for assurance of document integrity, please refer to its WWW home page: Victor Sand Dynamic Visualization of Space Weather Data Victor Sand Civilingenjör Medieteknik Linköping University Master s thesis Goddard Space Flight Center, Maryland, USA Norrköping, Sweden June 2014 Abstract The work described in this thesis is part of the Open Space project, a collaboration between Linköping University, the National Aeronautics and Space Administration and the American Museum of Natural History. The long-term goal of Open Space is a multi-purpose, open-source scientific visualization software. The thesis covers the research and implementation of a pipeline for preparing and rendering volumetric data. The developed pipeline consists of three stages: A data formatting stage which takes data from various sources and prepares it for the rest of the pipeline, a pre-processing stage which builds a tree structure of of the raw data, and finally an interactive rendering stage which draws a volume using ray-casting. Large parts of the system are built around the use of a Time-Space Partitioning tree, originally described by Shen et al. This tree structure uses an error metric system and an octree-based structure to efficiently choose the appropriate level of detail during rendering. The data storage and structure are similar to the one in the GigaVoxels system by Crassin et al. Using a combination of these concepts and constructing the pipeline around them, space weather related volumes have been successfully rendered at interactive rates. The pipeline is a fully working proof-of-concept for future development of Open Space, and can be used as-is to render space weather data. Many concepts and ideas from this work can be utilized in the larger-scale software project. iv Acknowledgements First of all, I would like to thank my examinator, professor Anders Ynnerman, for the fantastic opportunity and for keeping the project running. Thanks also to my excellent advisor Alexander Bock for many late hours of support and idea discussions. Your willingness to help and share your vast graphics knowledge has been truly invaluable. Thank you Masha for your tireless and dedicated work with CCMC and for taking care of us thesis students. Your genuine interest in the project is a requirement for its success! I m sure the next couple of students will feel just as welcome. Thank you Carter for keeping us busy and for the great private tour of the museum. Bob, thank you for keeping an eye on the big picture! Aki, thanks for making my commute shorter, my lunches more tasty and my country music knowledge more solid. Nate, thanks for being a bro and thanks Avery for letting me sleep on your floor for a while. Come to Sweden and I ll repay the favors! Thanks Martin for doing a great job during the first stage of the project and thereby making my job easier. Thanks to my many different roomates and friends in Washington D.C. for making my stay so much more than only work. I hope to see many of you again soon! Many thanks to Holmen AB, Sparbankstiftelsen Alfa and Stiftelsen Anna Whitlocks Minnesfond for the financial help when CSN wouldn t lend me more money. I could have not completed my stay without it. Finally, thanks to my family for the endless support and encouragement! Victor Stockholm, February 2014 ii Contents 1 Introduction Background Aim and Goals Method Limitations Thesis Structure Background Space Weather Community Coordinated Modeling Center Open Space Previous Work Volume Ray-Casting TSP Tree Acceleration Overview and Motivation Structure Traversal Error Metrics Rendering of Large Voxel Datasets Data Structure Rendering Pipeline Overview Pipeline Stages Inputs and Outputs iii CONTENTS 5 TSP Tree Implementation Bricks Separation of Structure and Data Memory Layout Error Metrics Pointer Structure Traversal Data Formatting Space Weather Data Sources ENLIL CDF Data Format Kameleon Furnace Voxel Data Format Data Pre-Processing Forge TSP Tree Construction Brick Padding Octree Construction BST Assembling TSP Data Format Rendering Flare TSP Structure and Error Metrics Construction TSP Structure Construction Error Metrics Calculation Error Caching Intra-Frame Pipeline View Ray Generation TSP Tree Probing Brick Uploading iv CONTENTS Ray-Casting Asynchronous Execution Rendering Parameters Cluster Rendering SGCT Results Hardware Rendering Benchmarks Error Metrics Benchmarks Visual Results Desktop Rendering Dome Rendering Discussion and Future Work Visual Quality Rendering Interactivity Performance Pipeline Encapsulation TSP Tree Structure Construction Storage Data Formats Error Metrics Calculation Control Rendering Conclusions 51 References 53 v CONTENTS A Code Samples 55 A.1 TSP Tree Traversal A.2 Brick Padding A.3 Octree Construction A.4 BST Assembling A.5 TSP Tree Structure Construction A.6 Error Metrics A.7 Rendering Loop vi 1 Introduction This first chapter briefly discusses the background and goals of the work. It also describes used methods as well as the thesis s structure and limitations. Note that the background is described in more detail in chapter Background Open Space is the working title for a project initiated in the fall of Collaborators in the project are Linköping University, the Community Coordinated Modeling Center (CCMC) at the National Aeronautics and Space Administration (NASA) and the American Museum of Natural History (AMNH). The long-term goal of Open Space is an open-source scientific visualization software with focus on space-related data sources. This software will be capable of producing efficient, accurate and beautiful visualizations of phenomena on a scale ranging from the size of atoms to the size of the entire known universe. The uses for this software will be both scientific as well as for public dissemination. In order to accomplish this goal, the participants are engaged in a Master s thesis student project. This collaboration enables students from Linköping to be on-site at NASA Goddard Space Flight Center, working close to the NASA scientists and the data sources. Input and feature requests for the project come from all three stakeholders, giving the project a broad purpose that is rooted in computer graphics research, in space science and in multimedia. 1 1. INTRODUCTION The part of the Open Space project described in this thesis aims to efficiently render time-varying data sets of space weather using volumetric voxel rendering. 1.2 Aim and Goals One of the most challenging aspects of volumetric rendering is handling large data sets efficiently. Time-varying data sets provide additional challenges due to memory limitations and the need to update the rendering often in order to achieve an animation with an acceptable frame rate. The aim of the work presented within this thesis is to implement an efficient volumetric rendering pipeline, capable of handling large time-varying data sets. The results of this work will later be implemented in the larger-scale Open Space project. Additionally, the implemented rendering system will have enough functionality to provide visualizations that can be used in presentations, videos et cetera. 1.3 Method The thesis work will be carried out by implementing a volumetric rendering system from the ground up. The input to this rendering system will be data from space weather simulations. The system will be continuously improved as the work develops. Having a basic functionality working early enables an iterative approach, and makes modular implementation and testing easier as more advanced features are implemented. 1.4 Limitations Since the thesis focuses on the rendering efficiency and the pipeline, less focus will be put on the space weather application domain. Although the software will be capable of rendering arbitrary volumetric data provided the right preprocessing steps are taken, a smaller amount of time is spent on the applications than in the previous prototyping phase (see section 2.3). For the same reasons, the rendering techniques are very simple compared to what is possible today. 2 1.5 Thesis Structure 1.5 Thesis Structure To properly familiarize the reader with the subject and the project that this thesis work is a part of, the thesis will start with a brief section on space weather and some of the background of the collaboration. Then some previous work on Open Space and computer graphics will be presented, before describing the implemented pipeline. The chapter Pipeline Overview does not go into any implementation details, but is very useful for putting the subsequent chapters in context. After the high-level overview some time is spent on describing the implementation one of the main techniques, the Time-Space Partitioning (TSP) tree. These methods are used in many parts of the pipeline, and are therefore also presented early in the thesis. Following the introductory chapters are the three chapters that each describe a different part of the pipeline. Results, future work topics and discussion of the work are presented last in the main part of the thesis. To further explain some of the implementation thesis, an appendix with selected code samples is included in the back. 3 1. INTRODUCTION 4 2 Background This chapter will provide context to the thesis by outlining the Open Space project, and breifly discussing what space weather is and how it is being studied. 2.1 Space Weather The National Research Council explains the concept of space weather in the following way (1). Space weather describes the conditions in space that affect Earth and its technological systems. Our space weather is a consequence of the behavior of the sun, the nature or Earth s magnetic field and atmosphere, and our location in the solar system. The National Space Weather Program Council has a similar description of the subject and also mentions the effects that space weather can have on earth (2): Space weather refers to conditions on the sun and in the solar wind, magnetosphere, ionosphere, and thermosphere that can influence the performance and reliability of space-born and ground-based technological system and can endanger human life or health. Adverse conditions in the space environment can cause disruptions of satellite operations, communications, navigations, and electric power distribution grids, leading to a variety of socioeconomic losses. 5 2. BACKGROUND 2.2 Community Coordinated Modeling Center Given the possible effects on earth, it is desirable to study and predict space weather events. The Community Coordinated Modeling Center (CCMC) at NASA Goddard Space Flight Center works with space weather simulation and forecasting. The center also provides the scientific community access to the models and resources for development and research. 2.3 Open Space The prototyping phase of the Open Space project resulted in a thesis by Törnros (3). This work contains a thorough summary of the modeling and simulations tools used at CCMC, as well as an overview of pre-existing visualization software. The thesis also presents an approach for visualizing space weather data by means of volumetric rendering and ray-casting. An open-source software for interactive volume rendering, Voreen (4), is used and extended to produce interactive renderings of space weather events. These renderings are done for one time step at a time. Screenshots from Törnros thesis can be found in figures 2.1 and 2.2. The results of this prototyping phase provide an entry point for the work described in this thesis, where the goal is to enable working with time-varying data sets. 6 2.3 Open Space Figure 2.1: Screenshot of a coronal mass ejection event visualization Figure 2.2: Screenshot of the Voreen workspace 7 2. BACKGROUND 8 3 Previous Work The Previous Work section of the report provides a theoretical background of the techniques and concepts used in the implementation, mainly related to volumetric visualization and rendering of large voxel datasets. 3.1 Volume Ray-Casting Volume ray-casting is an image order volume rendering technique. This means that the image is produced by iterating over pixels rather than iterating over objects in the scene. To determine the color of each pixel, view rays are sent from the position of the camera through the volume (figure 3.1), and the volume is sampled at points along these rays. As the samples along each ray are gathered, each intensity is mapped to an RGBA color using a transfer function (figure 3.2). The colors from the transfer function mappings are composited into the final ray color using front-to-back compositing. The equationstocalculatethecomposited colorandopacityc anda giventheaccumulated values and the mapped color and opacity C and A are given in equation 3.1. C i = C i 1 +(1 A i)c i A i = A i 1 +(1 A i)a i (3.1) 9 3. PREVIOUS WORK Figure 3.1: The concept of volume ray-casting. View rays are shot from a virtual eye/- camera position through the image plane. Figure 3.2: Top: The volume is sampled along the view ray. Bottom: Each sampled intensity is mapped to a color using a transfer function. 10 3.2 TSP Tree Acceleration 3.2 TSP Tree Acceleration While straight-forward rendering techniques can be adequate for small data sets, they are often not efficient enough for large amounts of data with high requirements on speed. Researchers in the field of volumetric rendering and 3D graphics in general continuously strive to improve efficiency in data handling by the use of various acceleration structures. One such structure is called a Time-Space Partitioning(TSP) tree, and is the chosen data structure for this work. Implementation details are described in chapter 5. Overview and Motivation The TSP tree was first introduced by Shen et. al (5) and was later improved by Ellsworth et al (6). It is designed to capture and exploit both temporal and spatial coherency in a time-varying data set. The tree traversal algorithm uses user-supplied error tolerances to choose the correct level of detail at runtime. By separating the time domain from the spatial domain and treating them differently, the scheme can efficiently handle data sets where there is a large discrepancy between the resolutions in those domains. Error metrics are stored in the tree nodes, and the tree can be built once and then used repeatedly. Structure A TSP tree uses a complete octree as a skeleton. This octree subdivides the volume until a certain spatial subdivision level has been reached. Each octree node (inner nodes as well as leaves), in turn contains a binary search tree (BST) that contains the temporal information for that spatial subdivision. The binary search tree leaves are the individual time steps, and each level above the leaves represents a time span of twice the length. The binary search tree roots represent the whole temporal extent. In other words, the search tree roots represent averages of the octree nodes values over all time steps. The overall structure is illustrated in figure 3.3. Traversal TSP tree traversal starts in the octree. For every octree node, the corresponding BST is traversed top-down until a node with satisfying error metrics is found or a leaf 11 3. PREVIOUS WORK Figure 3.3: TSP structure (illustrated using a quadtree). The example uses two spatial subdivisions and eight time steps. The top section represents the octree skeleton, and the bottom tree is the binary search tree for one of the octree nodes. 12 3.3 Rendering of Large Voxel Datasets is reached. If the error at the leaf is too big, the traversal continues with the next subdivision level in the octree. See section 5.6 for the full TSP traversal algorithm. Error Metrics The concept of error metrics is key in the use of TSP tree techniques. To separate the spatial and temporal domains, two different error metrics are used by the TSP tree algorithm. The spatial error indicates how coherent the voxels within a subvolume are, and the temporal error is a measure of how coherent the voxels between two or several time steps are. The first TSP tree publication (5) uses error metric based on the scalar values of voxels. To make the error metrics more accurate and closely related to the visible image, a color-based approach was introduced (6). The color-based approach is useful for any image where mapping from scalar values to colors are used, for example when using transfer functions. 3.3 Rendering of Large Voxel Datasets One of the more prominent works in the field of voxel graphics is the GigaVoxels system, presented in the Ph.D. thesis by Crassin et. al (7). Their work outlines an extensive pipeline for handling very large sets of data. While the thesis extensively covers the subject of turning traditional scene to voxels (in contrast of working directly with voxels), a sophisticated pipeline for processing the data has been developed. This pipeline mainly deals with transferring data between system and video memory through a custom GPU paging system. Data Structure GigaVoxels makes use of a spatial, octree-based structure for hierarchical space subdivision. The smallest entities, the octree nodes, in this subdivision are called bricks, small voxel grids that represent the volume s subdivision at a given level. Bricks make it possible to combine efficient 3D texture features of GPUs and give good flexibility in the subdivision. Furthermore, GigaVox
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