Por favor, use este identificador para citar o enlazar este ítem: https://doi.org/10.1109/TVCG.2021.3087863

Título: Omega-Test: A Predictive Early-Z Culling to Improve the Graphics Pipeline Energy-Efficiency
Fecha de publicación: 1-dic-2022
Editorial: IEEE
Cita bibliográfica: IEEE Transactions on Visualization and Computer Graphics, vol. 28, issue 12, pp. 4375-4388, ISSN: 1077-2626, Diciembre 2022
ISSN: 1077-2626
Palabras clave: Graphics processors
Mobile processors
Portable devices
Hardware architecture
Processor architecture
Energy-aware systems
Low-power design
Hidden line/surface removal
Visibility determination
Resumen: 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.
Autor/es principal/es: Corbalán-Navarro, D.
Aragón, J.L.
Anglada, M.
de Lucas, E.
Parcerisa, J.M.
González, A.
Director/es: Aragón, J.L.
González, A.
Facultad/Departamentos/Servicios: Facultades, Departamentos, Servicios y Escuelas::Departamentos de la UMU::Ingeniería y Tecnología de Computadores
URI: http://hdl.handle.net/10201/138264
DOI: https://doi.org/10.1109/TVCG.2021.3087863
Tipo de documento: info:eu-repo/semantics/article
Número páginas / Extensión: 14
Derechos: info:eu-repo/semantics/openAccess
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
Descripción: ©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
Aparece en las colecciones:Artículos: Ingeniería y Tecnología de Computadores

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