Publication: Omega-Test: A Predictive Early-Z Culling to Improve the Graphics Pipeline Energy-Efficiency
Authors
Corbalán-Navarro, D. ; Aragón, J.L. ; Anglada, M. ; de Lucas, E. ; Parcerisa, J.M. ; González, A.
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Aragón, J.L. ; González, A.
Publisher
IEEE
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DOI
https://doi.org/10.1109/TVCG.2021.3087863
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info:eu-repo/semantics/article
Description
©2022. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
This document is the Accepted, version of a Published Work that appeared in final form in IEEE Transactions on Visualization and Computer Graphics (TVCG). To access the final edited and published work see https://doi.org/10.1109/TVCG.2021.3087863
Abstract
The most common task of GPUs is to render images in real time. When rendering a 3D scene, a key step is to determine which parts of every object are visible in the final image. There are different approaches to solve the visibility problem, the Z-Test being the most common. A main factor that significantly penalizes the energy efficiency of a GPU, especially in the mobile arena, is the so-called overdraw , which happens when a portion of an object is shaded and rendered but finally occluded by another object. This useless work results in a waste of energy; however, a conventional Z-Test only avoids a fraction of it. In this article we present a novel microarchitectural technique, the Omega-Test, to drastically reduce the overdraw on a Tile-Based Rendering (TBR) architecture. Graphics applications have a great degree of inter-frame coherence, which makes the output of a frame very similar to the previous one. The proposed approach leverages the frame-to-frame coherence by using the resulting information of the Z-Test for a tile (a buffer containing all the calculated pixel depths for a tile), which is discarded by nowadays GPUs, to predict the visibility of the same tile in the next frame. As a result, the Omega-Test early identifies occluded parts of the scene and avoids the rendering of non-visible surfaces eliminating costly computations and off-chip memory accesses. Our experimental evaluation shows average EDP savings in the overall GPU/Memory system of 26.4 percent and an average speedup of 16.3 percent for the evaluated benchmarks.
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Citation
IEEE Transactions on Visualization and Computer Graphics, vol. 28, issue 12, pp. 4375-4388, ISSN: 1077-2626, Diciembre 2022
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Este ítem está sujeto a una licencia Creative Commons. http://creativecommons.org/licenses/by-nc-nd/4.0/