Hardware Implementation of Micropolygon Rasterization with Motion and Defocus Blur
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John Brunhaver |
Kayvon Fatahalian |
Pat Hanrahan | ||
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In the Proceedings of High Performance Graphics 2010 |
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Abstract:
Current GPUs rasterize micropolygons (polygons approximately one pixel in size) inefficiently. Additionally, they do not natively support triangle rasterization with jittered sampling, defocus, or motion blur. We perform a microarchitectural study of fixed-function micropolygon rasterization using custom circuits. We present three rasterization designs: the first optimized for triangle micropolygons that are not blurred, a second for stochastic rasterization of micropolygons with motion and defocus blur, and third that is a hybrid combination of the two. Our designs achieve high area and power efficiency by using low-precision operations and rasterizing pairs of adjacent triangles in parallel. We demonstrate optimized designs synthesized in a 45 nm process showing that a micropolygon rasterization unit with a throughput of 3 billion micropolygons per second would consume 2.9 W and occupy 4.1 mm^2 which is 0.77% of the die area of a GeForce GTX 480 GPU.
Paper:
Posted 05/16/2010 |