Data-parallel Micropolygon Rasterization
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Date
2010
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
Abstract We implement a tile based sort-middle rasterizer in CUDA and study its performance characteristics when used as a backend for adaptive tessellation down to micropolygons. Tessellation and bucketing map very well to the data-parallel paradigm of CUDA, and the majority of time is spent with rasterization. Despite this, our fastest implementation is able to reach 30-50% of the hardware rasterization performance of an Nvidia GTX 280. Overall we are able to rasterize 4 M textured and Phong shaded microquads into a 1600x1200 framebuffer at 10-12 fps.Abstract We implement a tile based sort-middle rasterizer in CUDA and study its performance characteristics when used as a backend for adaptive tessellation down to micropolygons. Tessellation and bucketing map very well to the data-parallel paradigm of CUDA, and the majority of time is spent with rasterization. Despite this, our fastest implementation is able to reach 30-50% of the hardware rasterization performance of an Nvidia GTX 280. Overall we are able to rasterize 4 M textured and Phong shaded microquads into a 1600x1200 framebuffer at 10-12 fps.
Description
@inproceedings{10.2312:egsh.20101046,
booktitle = {Eurographics 2010 - Short Papers},
editor = {H. P. A. Lensch and S. Seipel},
title = {{Data-parallel Micropolygon Rasterization}},
author = {Eisenacher, Christian and Loop, Charles},
year = {2010},
publisher = {The Eurographics Association},
ISBN = {},
DOI = {10.2312/egsh.20101046}
}