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Refereed Journal Papers
	A Multiresolution Representation for Massive Meshes. E. Shaffer and M. Garland. IEEE Transactions on Visualization and Computer Graphics , Volume 11, Issue 2, March-April 2005, pp. 139 - 148 [PDF] Abstract: We propose a new external memory multiresolution surface representation for massive polygonal meshes. Previous methods for building such data structures have relied on resampled surface data or employed memory intensive construction algorithms that do not scale well. Our proposed representation combines efficient access to a rich set of sampled surface data with access to the original surface. The multiresolution nature of the surface representation has allowed us to develop efficient algorithms for view-dependent rendering, approximate collision detection, and adaptive simplification of massive meshes.
Refereed Conference Papers
	A Multiphase Approach to Efficient Surface Simplification M. Garland and E. Shaffer. Proceedings of IEEE Visualization 2002, October 2002. [PDF] Abstract: We present a new multiphase method for efficiently simplifying polygonal surface models of arbitrary size. It operates by combining an initial out-of-core uniform clustering phase with a subsequent in-core iterative edge contraction phase. These two phases are both driven by quadric error metrics, and quadrics are used to pass information about the original surface between phases. The result is a method that produces approximations of a quality comparable to quadric-based iterative edge contraction, but at a fraction of the cost in terms of running time and memory consumption
	Efficient Adaptive Simplification of Massive Meshes. E. Shaffer and M. Garland. Proceedings of IEEE Visualization 2001. [PDF] Abstract: The growing availability of massive polygonal models, and the inability of most existing visualization tools to work with such data, has created a pressing need for memory efficient methods capable of simplifying very large meshes. In this paper, we present a method for performing adaptive simplification of polygonal meshes that are too large to fit in-core. Our algorithm performs two passes over an input mesh. In the first pass, the model is quantized using a uniform grid. The quantized surface information is then used to construct a BSP-Tree. In the final pass, the original vertices are clustered using the BSPTree, yielding an adaptive approximation of the original mesh. Our algorithm exhibits output-sensitive memory requirements and allows fine control over the size of the simplified mesh.
	An Approach to Immersive Performance Visualization of Parallel & Wide-Area Distributed Applications. Luiz DeRose, Mario Pantano, Ruth Aydt, Eric Shaffer, Benjamin Schaeffer, Shannon Whitmore, and Daniel A. Reed. Proceedings of the International Symposium on High Performance Distributed Computing (HPDC'99) 1999 [PDF] Abstract: Complex, distributed applications pose new challenges for performance analysis and optimization. This paper outlines an online approach to performance analysis where developers are active participants, using integrated measurement and immersive performance visualization to tune parallel and distributed applications.
Invited Papers and Articles
	Real-Time Immersive Performance Visualization and Steering. Eric Shaffer, Daniel A. Reed. ACM SIGGRAPH Computer Graphics Newsletter, May 2000. [PDF ] Abstract: We have produced a prototype system that integrates collaborative, immersive performance visualization with real time adaptive control of applications. The Virtue visualization system strives to make the abstract world of software tangible by using three dimensional data displays and virtual reality technology.
	Virtue: Immersive Performance Visualization of Parallel and Distributed Applications. Eric Shaffer, Shannon Whitmore, Benjamin Schaeffer, and Daniel A. Reed. IEEE Computer, December 1999 [PDF ] Abstract: The Virtue prototype exploits human sensory capabilities to help performance analysts explore and optimize large-scale, multidisciplinary applications. The visualization environment lets collaborators interact with executing software, tuning its behavior to meet performance goals.
	Performance Analysis of Parallel Systems: Approaches and Open Problems. Daniel A. Reed, Ruth A. Aydt, Luiz DeRose, Celso L. Mendes, Randy L. Ribler, Eric Shaffer, Huseyin Simitci, Jeffrey S.Vetter, Daniel R. Wells, Shannon Whitmore, and Ying Zhang. Joint Symposium on Parallel Processing (JSPP), June 1998 [PDF ] Abstract: Parallel computing is rapidly evolving to include heterogeneous collections of distributed and parallel systems. Concurrently, applications are becoming increasingly multidisciplinary with code libraries implemented using diverse programming models. To optimize the behavior of complex applications on heterogeneous systems, performance analysis software must also evolve, replacing postmortem analysis with realtime, adaptive optimization, tightly integrating compiletime analysis with performance measurement and prediction, and supporting highmodality visualization and software manipulation. In this paper, we briefly survey the state of the art in each of these areas and sketch a series of open research problems.

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