ANALYSIS OF GRAPHICS PIPELINES
DOI:
https://doi.org/10.30890/2709-2313.2024-30-00-019Keywords:
Graphics pipeline, DirectX, OpenGL, Parallelization, Vertex Shader, Fragment ShaderAbstract
In the work, the concept of graphics pipeline is analyzed. The features of OpenGL and DirectX graphics pipelines are compared. The perspectives of graphics pipeline development are discussed.Metrics
References
Romanyuk, O., Romanyuk, O., & Chekhmestruk, R. (2023). Kompiuterna hrafika [Computer Graphics]. Vinnytsia National Technical University. https://ir.lib.vntu.edu.ua/handle/123456789/37689.
Romanyuk, O., & Chornyi, A. (2006). Vysokoproduktyvni metody ta zasoby zafarbovuvannia tryvymirnykh hrafichnykh obiektiv [High-performance methods and means of shading three-dimensional graphic objects]. UNIVERSUM-Vinnytsia.
Romanyuk, O., Maidaniuk, V., & Trukhan, D. (2023). Osoblyvosti Hrafichnoho 3D-Konveiera [Features of Graphics 3D-Pipeline]. In Materials of t the 33th International Scientific and Practical Conference Modern Aspects of Modernization of Science: Status, Problems, Development (pp. 359–364). Paola; VADND.
Romanyuk, O., Romanyuk, S., & Romanyuk, O. (2022). Osnovni protsedury hrafichnoho konveiera [Main procedures of graphics pipeline]. In Information Technologies in Culture, Art, Education, Science, Economy and Business: Proceedings of the VII International Scientific and Practical Conference (pp. 45–47). Kyiv; KNUKiM.
Zavalniuk, Y., & Romanyuk, O. (2023). Bazovi vymohy do prohramnykh system renderynhu [Basic requirements for software rendering systems]. In «Information Technologies and Automation– 2023» Proceedings of the XVI International Scientific and Practical Conference (pp. 434–437). Odesa; ONTU.
Romanyuk, O., Marushchak, A., & Shmaliukh, V. (2022). Sheidery ta yikh movy prohramuvannia [Shaders and their programming languages]. In The 18th International scientific and practical conference “Modern Science, Practice, Society” (pp. 402–406). Boston; ISG.
Rendering pipeline overview. Rendering Pipeline Overview - OpenGL Wiki. (2022). https://www.khronos.org/opengl/wiki/Rendering_Pipeline_Overview.
Tiwari, J. (2022, September 29). OpenGL Rendering Pipeline: An overview. GeeksforGeeks.https://www.geeksforgeeks.org/opengl-rendering-pipeline-overview/.
Stevewhims, & Mattwojo. (2022). Graphics pipeline - UWP applications. UWP applications | Microsoft Learn. https://learn.microsoft.com/en-us/windows/uwp/graphics-concepts/graphics-pipeline.
Cebenoyan, C. (2007). Chapter 28. graphics pipeline performance. NVIDIA Developer. https://developer.nvidia.com/gpugems/gpugems/part-v-performance-and-practicalities/chapter-28-graphics-pipeline-performance.
Romanyuk, O., & Dudnyk, O. (2016). Evoliutsiia Konveiera Renderynhu v Videokartakh [Evolution of the Rendering Pipeline in Video Cards]. In Electronic information resources: creation, use, access: Proceedings of the International Scientific and Practical Internet Conference (pp. 438–446). Vinnytsia; VNTU.
Chan, A., & Romanyuk, O. (2021). Analiz modyfikatsii klasychnykh hrafichnykh konveieriv dlia optymizatsii rozpodilennia resursiv [Analysis of the modification of classical graphic pipelines to optimize the allocation of resources]. In State, achievements and prospects of information systems and technologies. (pp. 103–104). Odesa; ONAKT.
Eldridge, M., Igehy, H., & Hanrahan, P. (2000). Pomegranate: a Fully Scalable Graphics Architecture. Proceedings of the 27th Annual Conference on Computer Graphics and Interactive Techniques - SIGGRAPH ’00. https://doi.org/10.1145/344779.344981.
Zavalniuk, Y., & Romanyuk, O. (2023). Analiz protsedur rozparalelennia renderynhu hrafichnykh stsen [Analysis of parallelization procedures for rendering of graphic scenes]. In Electronic information resources: creation, use, access: Proceedings of the International Scientific and Practical Internet Conference (pp. 105–107). Sumy/Vinnytsia; NIKO/VABO.
Kenzel, M., Kerbl, B., Schmalstieg, D., & Steinberger, M. (2018). A high-performance software graphics pipeline architecture for the GPU. ACM Transactions on Graphics, 37(4), 1–15. https://doi.org/10.1145/3197517.3201374.
Romanyuk, O., & Zavalniuk, Y. (2024). Deep Learning-Based Determination of Optimal Triangles Number of Graphic Object’s Polygonal Model. In IntelITSIS 2024 Proceedings of the 5th International Workshop on Intelligent Information Technologies & Systems of Information Security with CEUR-WS (pp. 39–51). Khmelnytskyi; CEUR-WS.
Harris, M. W., & Semwal, S. K. (2021). A multi-stage advanced deep learning graphics pipeline. SIGGRAPH Asia 2021 Technical Communications. https://doi.org/10.1145/3478512.3488609
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Authors
This work is licensed under a Creative Commons Attribution 4.0 International License.
