1) Interactive Visibility Ordering of Geometric Primitives in Complex Environments
2) A Cache-Efficient Sorting Algorithm for Database and Data
Mining Computations using Graphics Processors
1) Interactive Visibility Ordering of Geometric Primitives in Complex Environments
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These images demonstrate the performance of our visibility ordering algorithm on a CAD model with 820K triangles and high depth complexity. The left image shows the original model rendered with opaque objects. The outer walls and structures (represented with 91K triangles) of the powerplant are rendered with transparency in the right image. Our algorithm computes a back-to-front ordering of the transparent primitives at 7 - 10 frames on a 3.4 GHz PC with NVIDIA GeForce FX 6800 GPU and renders them with a vertex shader.
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Dynamic Scene: This scene is composed of 18 deforming bunnies moving in a room. The scene consists of 25K triangles and has a high depth complexity of 8 - 10 in
many view directions. One such view is shown in the left image where the scene is rendered with transparency using our visibility ordering algorithm (at 10 frames a second). In the
right image, the same scene rendered with opaque objects is shown. In this dynamic environment, we are able to perform interactive collision computations at 25 frames per second.
A Cache-Efficient Sorting Algorithm for Database and Data Mining Computations using Graphics ProcessorsAbstractWe present a fast sorting algorithm using graphics processors (GPUs) that adapts well to database and data mining applications. Our algorithm uses texture mapping and blending functionalities of GPUs to implement an efficient bitonic sorting network. We take into account the communication bandwidth overhead to the video memory on the GPUs and reduce the memory bandwidth requirements. We also present strategies to exploit the tile-based computational model of GPUs. Our new algorithm has a memory-efficient data access pattern and we describe an efficient instruction dispatch mechanism to improve the overall sorting performance. We have used our sorting algorithm to accelerate join-based queries and stream mining algorithms. Our results indicate up to an order of magnitude improvement over prior CPU-based and GPU-based sorting algorithms.
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CB #3175, Department of Computer Science
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