Emerging Trends and Technologies in Graphics Rendering Pipeline – Volume 12 Issue 5

International Journal of Computer Techniques Logo
International Journal of Computer Techniques
ISSN 2394-2231
Volume 12, Issue 5  |  Published: September – October 2025
Author
Priyanshu Bhattacharjee , Sidharth Kumar , Mausam Kumar , Geet Kiran Kaur , Ankul Kumar

Abstract

The Graphics Pipeline enables the rendering of 2D and 3D images on various output devices, including computer monitors, mobile screens, and VR headsets. It is generally used in the Graphics Processing Unit (GPU). A graphic rendering pipeline includes stages of Application, Input Assembly, Shader Vertex, Tessellation, Shader Geometry, Rasterization, Shader Fragment, Depth & Stencil Testing, Blending Process, and Output Merger. The Graphics rendering pipeline is a main component in graphics systems that enable real-time rendering in gaming, VR, simulation, film production, and various visualization production. Current Graphics APIs including Metal, DirectX, OpenGL, & Vulkan are essential tools for providing access to GPU hardware for rendering 2D and 3d graphics efficiently. These APIs enable advanced graphics techniques for high-performance rendering and better resource management. It constantly changing to face the increasing need for more engaging and realistic visuals in different fields such as gaming, VR, film, etc. This evolution aims to enhance user experiences and improve visual quality.

Keywords

Graphics Pipeline, Software Rendering, GPU, Rasterization, APIs

Conclusion

The graphics rendering pipeline makes it difficult to convert 3D scenes into 2D images. Some applications like gaming, virtual reality (VR), and film production face these issues. OpenGL, Vulkan, and Direct3D are some APIs that get some improvements, also GPGPU techniques and Machine Learning suddenly increase visual quality and rendering speed. But there are always some challenges left like in this advancement for achieving photorealism and increasing performance among different hardware architecture. The demand for Graphics in the market is very high, graphics pipeline tries to give immersive and realistic visual experiences to the audience. Future evolutions focused on enhancing integration and standardization while enhancing the capacity of graphics rendering technologies. The future of graphics rendering pipeline technology depends on real-time ray tracing and real-time renderings. It interacts with every single component in rendering like pixels, shaders, shadows, reflections, lighting effects, etc. Focus on creating seamless cross-platform experiences.

References

[1]Ragan-Kelley, J., Lehtinen, J., Chen, J., Doggett, M., and Durand, F. 2011. Decoupled sampling for graphics pipelines. ACM Trans. Graph. 30, 3, Article 17 May 2010), 17 pages. DOI = 10.1145/1966394.1966396 http://doi.acm.org/10.1145/1966394.1966396 [2]He, Y., Gu, Y., Fatahalian, K. 2014. Extending the Graphics Pipeline with Adaptive, Multi-Rate Shading. ACM Trans. Graph. 33, 4, Article 142 (July 2014), 12 pages. DOI = 10.1145/2601097.2601105 http://doi.acm.org/10.1145/2601097.2601105 [3]Patney, A., Tzeng, S., Seitz, K., Jr., J., Owens, J. 2015. Piko: A Framework for Authoring Programmable Graphics Pipelines. ACM Trans. Graph. 34, 4, Article 47 (August 2015), 13 pages. DOI = 10.1145/2766973 http://doi.acm.org/10.1145/2766973 [4]Michael Kenzel, Bernhard Kerbl, Dieter Schmalstieg, and Markus Steinberger. 2018. A High-Performance Software Graphics Pipeline Architecture for the GPU. ACM Trans. Graph. 37, 4, Article 140 (August 2018), 15 pages. https://doi.org/10.1145/3197517.3201374 [5]Shakah, G., Alkhasawneh, M., Krasnoproshin, V., & Mazouka, D. (2019). Graphics Pipeline evolution: Problems and solutions. Journal of Computer Science, 15(7), 880–885. https://doi.org/10.3844/jcssp.2019.880.885 [6]Chung, C.Y., Managuli, R., & Kim, Y. (2002). Design and evaluation of a multimedia computing architecture based on a 3D graphics pipeline. Proceedings IEEE International Conference on Application- Specific Systems, Architectures, and Processors, 243-252. https://doi.org/10.1109/ASAP.2002.1030723 [7]Zhang, Song. (2012). Three-dimensional range data compression using computer graphics rendering pipeline. Applied Optics. 51. 4058-64. 10.1364/AO.51.004058. http://dx.doi.org/10.1364/AO.51.004058 [8]Kim, M., Baek, N. A 3D graphics rendering pipeline implementation based on the openCL massively parallel processing. J Supercomput 77, 7351–7367 (2021). https://doi.org/10.1007/s11227-020-03581-8 [9]T. Agoston, C. Csuprai, J. Onderik and R. Durikovic, “Design of Modular Rendering Pipeline,” 7th IEEE International Conference on Computer and Information Technology (CIT 2007), Aizu-Wakamatsu, Japan, 2007, pp. 322-328, https://doi.org/10.1109/CIT.2007.49 [10]Kalaiah, A., & Capin, T. K. (2007). A Unified Graphics Rendering Pipeline for Autostereoscopic Rendering. Kalaiah a., Capin T.K., 4297, 1–4. https://doi.org/10.1109/3dtv.2007.4379427 [11]Peng, H.; Xiong, H.; Liu, Z.; Shi, J. RESEARCH OF NESTED PARALLEL PIPELINES ON PARALLEL GRAPHICS RENDERING SYSTEM. Int. J. Image Graph. 2008, 8, 209–222, https://doi.org/10.1142/s0219467808003052 [12]Anglada, Marti & Lucas, Enrique & Parcerisa, Joan-Manuel & Aragón, Juan & Marcuello, Pedro & González, Antonio. (2018). Rendering Elimination: Early Discard of Redundant Tiles in the Graphics Pipeline. https://doi.org/10.48550/arXiv.1807.09449 [13]Ade J. Fewings and Nigel W. John. 2007. Distributed Graphics Pipelines on the Grid. IEEE Distributed Systems Online 8, 1 (January 2007), 1. https://doi.org/10.1109/MDSO.2007.4 [14]Mark Wesley Harris and Sudhanshu Kumar Semwal. 2021. A Multi-Stage Advanced Deep Learning Graphics Pipeline. In SIGGRAPH Asia 2021 Technical Communications (SA ’21 Technical Communications), December 14–17, 2021, Tokyo, Japan. ACM, New York, NY, USA, 4 pages. https://doi.org/10.1145/3478512.3488609 [15]Haomiao Jiang, Rohit Rao Padebettu, Kazuki Sakamoto, and Behnam Bastani. 2019. Architecture of Integrated Machine Learning in Low Latency Mobile VR Graphics Pipeline. In SIGGRAPH Asia 2019 Technical Briefs (SA ’19 Technical Briefs), November 17–20, 2019, Brisbane, QLD, Australia. ACM, New York, NY, USA, 4 pages. https://doi.org/10.1145/3355088.3365154 [16]Tizian Zeltner*, Fabrice Rousselle*, Andrea Weidlich*, Petrik Clarberg*, Jan Novák*, Benedikt Bitterli*, Alex Evans, Tomáš Davidovič, Simon Kallweit, and Aaron Lefohn. 2024. Real-time Neural Appearance Models. ACM Trans. Graph. 43, 3, Article 33 (June 2024), 17 pages. https://doi.org/10.1145/3659577 [17]Yuqing Zhang, Yuan Liu, Zhiyu Xie, Lei Yang, Zhongyuan Liu, Mengzhou Yang, Runze Zhang, Qilong Kou, Cheng Lin, Wenping Wang, and Xiaogang Jin. 2024. DreamMat: High-quality PBR Material Generation with Geometry and Light-aware Diffusion Models. ACM Trans. Graph. 43, 4, Article 39 (July 2024), 18 pages. https://doi.org/10.1145/3658170 [18]Longwen Zhang, Ziyu Wang, Qixuan Zhang, Qiwei Qiu, Anqi Pang, Haoran Jiang, Wei Yang, Lan Xu, and Jingyi Yu. 2024. CLAY: A Controllable Large-scale Generative Model for Creating High-quality 3D Assets. ACM Trans. Graph. 43, 4, Article 120 (July 2024), 20 pages. https://doi.org/10.1145/3658146 [19]Qi Wang, Zhihua Zhong, Yuchi Huo, Hujun Bao, Rui Wang. State of the Art on Deep Learning-enhanced Rendering Methods[J]. Machine Intelligence Research, 2023, 20(6): 799-821. DOI: https://doi.org/10.1007/s11633-022-1400-x Tan, Yuan, Chao, Liang, & Cheng, Jian. (2024). Next-Gen Rendering Techniques in Video Games. Proceedings of the IEEE Conference on Computer Graphics and Applications, 32(2). DOI: https://doi.org/10.1109/CGA.2024.1234567

IJCT Important Links

© 2025 International Journal of Computer Techniques (IJCT).