Hardware Implementation of Micropolygon Rasterization with Motion and Defocus Blur

 

John Brunhaver
Kayvon Fatahalian
Pat Hanrahan

 

In the Proceedings of High Performance Graphics 2010

 

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:

 

PDF (172 KB)


 

Posted 05/16/2010