From the Publisher:
Level of detail (LOD) techniques are increasingly used by professional real-time developers to strike the balance between breathtaking virtual worlds and smooth, flowing animation. Level of Detail for 3D Graphics brings together, for the first time, the mechanisms, principles, practices, and theory needed by every graphics developer seeking to apply LOD methods.
Continuing advances in level of detail management have brought this powerful technology to the forefront of 3D graphics optimization research. This book, written by the very researchers and developers who have built LOD technology, is both a state-of-the-art chronicle of LOD advances and a practical sourcebook, which will enable graphics developers from all disciplines to apply these formidable techniques to their own work. 
Features
Is a complete, practical resource for programmers wishing to incorporate LOD technology into their own systems. Is an important reference for professionals in game development, computer animation, information visualization, real-time graphics and simulation, data capture and preview, CAD display, and virtual worlds. Is accessible to anyone familiar with the essentials of computer science and interactive computer graphics. Covers the full range of LOD methods from mesh simplification to error metrics, as well as advanced issues of human perception, temporal detail, and visual fidelity measurement. Includes an accompanying Web site rich in supplementary material including source code, tools, 3D models, public domain software, documentation, LOD updates, and more. 

Author Biography:David Luebke
David is an Assistant Professor in the Department of Computer Science at the University of Virginia. His principal research interest is the problem of rendering very complex scenes at interactive rates. His research focuses on software techniques such as polygonal simplification and occlusion culling to reduce the complexity of such scenes to manageable levels. Luebke's dissertation research, summarized in a SIGGRAPH '97 paper, introduced a dynamic, view-dependent approach to polygonal simplification for interactive rendering of extremely complex CAD models. He earned his Ph.D. at the University of North Carolina, and his Bachelors degree at the Colorado College. 
Martin Reddy
Martin is a Senior Computer Scientist at SRI International where he works in the area of terrain visualization. This work involves the real-time display of massive terrain databases that are distributed over wide-area networks. His research interests include level of detail, visual perception, and computer graphics. His doctoral research involved the application of models of visual perception to real-time computer graphics systems, enabling the selection of level of detail based upon measures of human perception. He received his B.Sc. from the University of Strathclyde and his Ph.D. from the University of Edinburgh, UK. He is on the Board of Directors of the Web3D Consortium and chair of the GeoVRML Working Group. 
Jonathan D. Cohen
Jon is an Assistant Professor in the Department of Computer Science at The Johns Hopkins University. He earned his Doctoral and Masters degrees from The University of North Carolina at Chapel Hill and earned his Bachelors degree from Duke University. His interests include polygonal simplification and other software acceleration techniques, parallel rendering architectures, collision detection, and high-quality interactive computer graphics. 
Amitabh Varshney
Amitabh is an Associate Professor in the Department of Computer Science at the University of Maryland. His research interests lie in interactive computer graphics, scientific visualization, molecular graphics, and CAD. Varshney has worked on several aspects of level-of-detail simplifications including topology-preserving and topology-reducing simplifications, view-dependent simplifications, parallelization of simplification computation, as well as using triangle strips in multiresolution rendering. Varshney received his PhD and MS from the University of North Carolina at Chapel Hill in 1994 and 1991 respectively. He received his B. Tech. in Computer Science from the Indian Institute of Technology at Delhi in 1989. 
Benjamin Watson
Ben is an Assistant Professor in Computer Science at Northwestern University. He earned his doctoral and Masters degrees at Georgia Tech's GVU Center, and his Bachelors degree at the University of California, Irvine. His dissertation focused on user performance effects of dynamic level of detail management. His other research interests include object simplification, medical applications of virtual reality, and 3D user interfaces. 
Robert Huebner
Robert is the Director of Technology at Nihilistic Software, an independent development studio located in Marin County, California. Prior to co-founding Nihilistic, Robert has worked on a number of successful game titles including "Jedi Knight: Dark Forces 2" for LucasArts Entertainment, "Descent" for Parallax Software, and "Starcraft" for Blizzard Entertainment. Nihilistic's first title, "Vampire The Masquerade: Redemption" was released for the PC in 2000 and sold over 500,000 copies worldwide. Nihilistic's second project will be released in the Winter of 2002 on next-generation game consoles. Robert has spoken on game technology topics at SIGGRAPH, the Game Developer's Conference (GDC), and Electronic Entertainment Expo (E3). He also serves on the advisory board for the Game Developer's Conference and the International Game Developer's Association (IGDA). Robert's e-mail address is .

Level of Detail for 3D Graphics

Inspired by the attractive Flops/dollar ratio and the incredible growth in the speed of modern graphics processing units (GPUs), we propose to use a cluster of GPUs for high performance scientific computing. As an example application, we have developed a parallel flow simulation using the lattice Boltzmann model (LBM) on a GPU cluster and have simulated the dispersion of airborne contaminants in the Times Square area of New York City. Using 30 GPU nodes, our simulation can compute a 480x400x80 LBM in 0.31 second/step, a speed which is 4.6 times faster than that of our CPU cluster implementation. Besides the LBM, we also discuss other potential applications of the GPU cluster, such as cellular automata, PDE solvers, and FEM.

GPU Cluster for High Performance Computing

This paper describes vCUDA, a general-purpose graphics processing unit (GPGPU) computing solution for virtual machines (VMs). vCUDA allows applications executing within VMs to leverage hardware acceleration, which can be beneficial to the performance of a class of high-performance computing (HPC) applications. The key insights in our design include API call interception and redirection and a dedicated RPC system for VMs. With API interception and redirection, Compute Unified Device Architecture (CUDA) applications in VMs can access a graphics hardware device and achieve high computing performance in a transparent way. In the current study, vCUDA achieved a near-native performance with the dedicated RPC system. We carried out a detailed analysis of the performance of our framework. Using a number of unmodified official examples from CUDA SDK and third-party applications in the evaluation, we observed that CUDA applications running with vCUDA exhibited a very low performance penalty in comparison with the native environment, thereby demonstrating the viability of vCUDA architecture.

vCUDA: GPU-Accelerated High-Performance Computing in Virtual Machines

This paper describes vCUDA, a GPGPU (General Purpose Graphics Processing Unit) computing solution for virtual machines. vCUDA allows applications executing within virtual machines (VMs) to leverage hardware acceleration, which can be beneficial to the performance of a class of high performance computing (HPC) applications. The key idea in our design is: API call interception and redirection. With API interception and redirection, applications in VMs can access graphics hardware device and achieve high performance computing in a transparent way. We carry out detailed analysis on the performance and overhead of our framework. Our evaluation shows that GPU acceleration for HPC applications in VMs is feasible and competitive with those running in a native, non-virtualized environment. Furthermore, our evaluation also identifies the main cause of overhead in our current framework, and we give some suggestions for future improvement.

vCUDA: GPU accelerated high performance computing in virtual machines

Continuing improvements in CPU and GPU performances as well as increasing multi-core processor and cluster-based parallelism demand for flexible and scalable parallel rendering solutions that can exploit multipipe hardware accelerated graphics. In fact, to achieve interactive visualization, scalable rendering systems are essential to cope with the rapid growth of data sets. However, parallel rendering systems are non-trivial to develop and often only application specific implementations have been proposed. The task of developing a scalable parallel rendering framework is even more difficult if it should be generic to support various types of data and visualization applications, and at the same time work efficiently on a cluster with distributed graphics cards. In this paper we introduce a novel system called Equalizer, a toolkit for scalable parallel rendering based on OpenGL which provides an application programming interface (API) to develop scalable graphics applications for a wide range of systems ranging from large distributed visualization clusters and multi-processor multipipe graphics systems to single-processor single-pipe desktop machines. We describe the system architecture, the basic API, discuss its advantages over previous approaches, present example configurations and usage scenarios as well as scalability results.

/pdf/equalizer-a-scalable-parallel-rendering-framework-4rxsvio0zv.pdf

Equalizer: A Scalable Parallel Rendering Framework

We describe WireGL, a system for scalable interactive rendering on a cluster of workstations. WireGL provides the familiar OpenGL API to each node in a cluster, virtualizing multiple graphics accelerators into a sort-first parallel renderer with a parallel interface. We also describe techniques for reassembling an output image from a set of tiles distributed over a cluster. Using flexible display management, WireGL can drive a variety of output devices, from standalone displays to tiled display walls. By combining the power of virtual graphics, the familiarity and ordered semantics of OpenGL, and the scalability of clusters, we are able to create time-varying visualizations that sustain rendering performance over 70,000,000 triangles per second at interactive refresh rates using 16 compute nodes and 16 rendering nodes.

/pdf/wiregl-a-scalable-graphics-system-for-clusters-1senvt8kxl.pdf

WireGL: a scalable graphics system for clusters

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WireGL: a scalable graphics system for clusters