research-article

ShaderTransformer: Predicting Shader Quality via One-shot Embedding for Fast Simplification

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Hujun BaoAuthors Info & Claims

SIGGRAPH '22: ACM SIGGRAPH 2022 Conference Proceedings

Article No.: 44, Pages 1 - 9

https://doi.org/10.1145/3528233.3530722

Published: 24 July 2022 Publication History

Abstract

Given specific scene configurations and target functions, automatic shader simplification searches for the best simplified shader variant from an optimization space with many candidates. Although various speedup methods have been proposed, there is still a costly render-and-evaluate process to obtain variant’s performance and quality, especially when the scene changes.

In this paper, we present a deep learning-based framework for predicting a shader’s simplification space, where the shader’s variants can be embedded into a metric space all at once for efficient quality evaluation. The novel framework allows the one-shot embedding of a space rather than a single instance. In addition, the simplification errors can be interpreted by mutual attention between shader fragments, presenting an informative focus-aware simplification framework that can assist experts in optimizing the codes. The results show that the new framework achieves significant speedup compared with existing search approaches. The focus-aware simplification framework reveals a new possibility of interpreting shaders for various applications.

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https://doi.org/10.3390/en17030613
Fan DLee RZhang X(2024)X-TED: Massive Parallelization of Tree Edit DistanceProceedings of the VLDB Endowment10.14778/3654621.365463417:7(1683-1696)Online publication date: 30-May-2024
https://dl.acm.org/doi/10.14778/3654621.3654634
Liu ZHuang YLiu L(2024)ShaderPerFormer: Platform-independent Context-aware Shader Performance PredictorProceedings of the ACM on Computer Graphics and Interactive Techniques10.1145/36512957:1(1-17)Online publication date: 13-May-2024
https://dl.acm.org/doi/10.1145/3651295
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cover image ACM Conferences

SIGGRAPH '22: ACM SIGGRAPH 2022 Conference Proceedings

July 2022

553 pages

ISBN:9781450393379

DOI:10.1145/3528233

Copyright © 2022 ACM.

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Published: 24 July 2022

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Cited By

Abu-Abed FPivovarov KZhironkin S(2024)Development of Software for 3D Well Visualization Modeling Using Acoustic, Gamma, Neutron and Density Logging for Fossil Energy Sources Sustainable ProductionEnergies10.3390/en1703061317:3(613)Online publication date: 26-Jan-2024
https://doi.org/10.3390/en17030613
Fan DLee RZhang X(2024)X-TED: Massive Parallelization of Tree Edit DistanceProceedings of the VLDB Endowment10.14778/3654621.365463417:7(1683-1696)Online publication date: 30-May-2024
https://dl.acm.org/doi/10.14778/3654621.3654634
Liu ZHuang YLiu L(2024)ShaderPerFormer: Platform-independent Context-aware Shader Performance PredictorProceedings of the ACM on Computer Graphics and Interactive Techniques10.1145/36512957:1(1-17)Online publication date: 13-May-2024
https://dl.acm.org/doi/10.1145/3651295
Abu-Abed FPivovarov KZhironkin VZhironkin S(2023)Development of a Software Tool for Visualizing a Mine (Wellbore) in the Industrial Drilling of Oil WellsProcesses10.3390/pr1102062411:2(624)Online publication date: 18-Feb-2023
https://doi.org/10.3390/pr11020624

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