Jim K. Nilsson

Coarse pixel shading

We present a novel architecture for flexible control of shading rates in a GPU pipeline, and demonstrate substantially reduced shading costs for various applications. We decouple shading and visibility by restricting and quantizing shading rates to a finite set of screen-aligned grids, leading to simpler and fewer changes to the GPU pipeline compared to alternative approaches. Our architecture introduces different mechanisms for programmable control of the shading rate, which enables efficient shading in several scenarios, e.g., rendering for high pixel density displays, foveated rendering, and adaptive shading for motion and defocus blur. We also support shading at multiple rates in a single pass, which allows the user to compute different shading terms at rates better matching their frequency content.

AMFS: adaptive multi-frequency shading for future graphics processors

We propose a powerful hardware architecture for pixel shading, which enables flexible control of shading rates and automatic shading reuse between triangles in tessellated primitives. The main goal is efficient pixel shading for moderately to finely tessellated geometry, which is not handled well by current GPUs. Our method effectively decouples the cost of pixel shading from the geometric complexity. It thereby enables a wider use of tessellation and fine geometry, even at very limited power budgets. The core idea is to shade over small local grids in parametric patch space, and reuse shading for nearby samples. We also support the decomposition of shaders into multiple parts, which are shaded at different frequencies. Shading rates can be locally and adaptively controlled, in order to direct the computations to visually important areas and to provide performance scaling with a graceful degradation of quality. Another important benefit of shading in patch space is that it allows efficient rendering of distribution effects, which further closes the gap between real-time and offline rendering.

Comparison of projection methods for rendering virtual reality

Virtual reality is rapidly gaining popularity, and may soon become a common way of viewing 3D environments. While stereo rendering has been performed on consumer grade graphics processors for a while now, the new wave of virtual reality display devices have two properties that typical applications have not needed to consider before. Pixels no longer appear on regular grids and the displays subtend a wide field-of-view. In this paper, we evaluate several techniques designed to efficiently render for head-mounted displays with such properties. We show that the amount of rendered pixels can be reduced down to 36% without compromising visual fidelity compared to traditional rendering, by rendering multiple optimized sub-projections.

Design and novel uses of higher-dimensional rasterization

This paper assumes the availability of a very fast higher-dimensional rasterizer in future graphics processors. Working in up to five dimensions, i.e., adding time and lens parameters, it is well-known that this can be used to render scenes with both motion blur and depth of field. Our hypothesis is that such a rasterizer can also be used as a flexible tool for other, less conventional, usage areas, similar to how the two-dimensional rasterizer in contemporary graphics processors has been used for widely different purposes other than the original intent. We show six such examples, namely, continuous collision detection, caustics rendering, higher-dimensional sampling, glossy reflections and refractions, motion blurred soft shadows, and finally multi-view rendering. The insights gained from these examples are used to put together a coherent model for what a future graphics pipeline that supports these and other use cases should look like. Our work intends to provide inspiration and motivation for hardware and API design, as well as continued research in higher-dimensional rasterization and its uses.