Multi-GPU Parallel Pipeline Rendering with Splitting Frame
Authors: 
Haitang Zhang, Junchao Ma, Zixia Qiu, Junmei Yao, Mustafa A. Al Sibahee, Zaid Ameen Abduljabbar, Vincent Omollo NyangaresiAuthors Info & Claims
Haitang Zhang, Junchao Ma, Zixia Qiu, Junmei Yao, Mustafa A. Al Sibahee, Zaid Ameen Abduljabbar, Vincent Omollo NyangaresiAuthors Info & ClaimsPages 223 - 235
Abstract
In order to achieve real-time rendering of cloud gaming, a large amount of computing resources of graphics processing units (GPU) are required. In this paper, we propose a multi-GPU parallel pipeline rendering approach that makes full use the computing power of multiple GPUs to accelerate real-time ray tracing rendering effectively. This approach enables heterogeneous GPUs to render the same frame cooperatively through a dynamic splitting frame load balancing scheme, and ensures that each GPU is assigned with the suitable size of splitting frame based on its rendering ability. A fine-grained parallel pipeline method divides the process of rendering into more detailed steps that enable multiple frames to be rendered in parallel, which improves the utilization of each step and speeds up the output of frames. With the experiments on various dynamic scenes, the results show that the number of frames per second (FPS) of the multi-GPU system composed of two GPUs is 2.2 times higher than that of the single GPU system, while the multi-GPU system composed of three GPUs has increased to 3.3 times.
References
[1]
AMD. ATI CrossFire Pro User Guide. Tech. rep. (2009)
[2]
Bikker, J.: Real-time ray tracing through the eyes of a game developer. In: 2007 IEEE Symposium on Interactive Ray Tracing, pp. 1–10 (2007)
[3]
Brodtkorb AR, Hagen TR, and Sætra ML Graphics processing unit (GPU) programming strategies and trends in GPU computing J. Parall. Distrib. Comput. 2013 73 1 4-13
[4]
Budge B, Bernardin T, Stuart JA, Sengupta S, Joy KI, and Owens JD Out-of-core data management for path tracing on hybrid resources Comput. Graph. Forum 2009
[5]
Cai, W., et al.: A survey on cloud gaming: Future of computer games. IEEE Access 4 (2016)
[6]
Carr, N.A., Hall, J.D., Hart, J.C.: The ray engine. In: Proceedings of the ACM SIGGRAPH/EUROGRAPHICS Conference on Graphics Hardware, pp. 37–46 (2002)
[7]
Deng N, He Z, and Yang X Render-based factorization for additive light field display Comput. Animat. Virt. Worlds 2021 32 3–4
[8]
Dong, Y., Peng, C.: Multi-GPU multi-display rendering of extremely large 3d environments. Vis. Comput. 1–17 (2022)
[9]
Eilemann S, Makhinya M, and Pajarola R Equalizer: a scalable parallel rendering framework IEEE Trans. Visual Comput. Graph. 2009 15 3 436-452
[10]
Huang, C.Y., Hsu, C.H., Chang, Y.C., Chen, K.T.: Gaminganywhere: an open cloud gaming system. In: Proceedings of the 4th ACM Multimedia Systems Conference (MMSys 2013), pp. 36–47. Association for Computing Machinery (2013)
[11]
Igehy, H., Stoll, G., Hanrahan, P.: The design of a parallel graphics interface. In: Proceedings of the 25th Annual Conference on Computer Graphics and Interactive Techniques, pp. 141–150 (1998).
[12]
Jia S, Zhang W, Wang G, Pan Z, and Yu X A real-time deformable cutting method using two levels of linked voxels for improved decoupling between collision and rendering Vis. Comput. 2023 39 2 765-783
[13]
Liu, H., Wang, P., Wang, K., Cai, X., Zeng, L., Li, S.: Scalable multi-GPU decoupled parallel rendering approach in shared memory architecture. In: 2011 International Conference on Virtual Reality and Visualization, pp. 172–178. IEEE (2011)
[14]
de Macedo DV and Rodrigues MAF Real-time dynamic reflections for realistic rendering of 3d scenes Vis. Comput. 2018 34 337-346
[15]
Moerschell, A., Owens, J.D.: Distributed texture memory in a multi-GPU environment. Comput. Graph. Forum 27, 130–151 (2008)
[16]
Molnar S, Cox M, Ellsworth D, and Fuchs H A sorting classification of parallel rendering IEEE Comput. Graph. Appl. 1994 14 4 23-32
[17]
NVIDIA. SLI Best Practices. Tech. rep. (2011)
[18]
Purcell, T.J., Buck, I., Mark, W.R., Hanrahan, P.: Ray tracing on programmable graphics hardware. In: ACM SIGGRAPH 2005 Courses (SIGGRAPH 2005), p. 268-es. Association for Computing Machinery (2005)
[19]
Qin, Y., Chi, X., Sheng, B., Lau, R.W.: Guiderender: large-scale scene navigation based on multi-modal view frustum movement prediction. Vis. Comput. 1–11 (2023).
[20]
Qiu, Z., Ma, J., Zhang, H., Al Sibahee, M.A., Abduljabbar, Z.A., Nyangaresi, V.O.: Concurrent pipeline rendering scheme based on GPU multi-queue and partitioning images. In: International Conference on Optics and Machine Vision (ICOMV) (2023)
[21]
Ren, X., Lis, M.: Chopin: scalable graphics rendering in multi-GPU systems via parallel image composition. In: 2021 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 709–722. IEEE (2021)
[22]
Riley, S., Diefes, L., Bechtold, L., Barry, M.: Multi-GPU accelerated ray tracing using cuda, pp. 676-686 (2022). https://scholar.sun.ac.za/
[23]
Shea R, Liu J, Ngai ECH, and Cui Y Cloud gaming: architecture and performance IEEE Network 2013 27 4 16-21
[24]
Soler, C., Hoel, O., Rochet, F.: A deferred shading pipeline for real-time indirect illumination. In: ACM SIGGRAPH 2010 Talks. Association for Computing Machinery (2010).
[25]
Tolo, L.O., Viola, I., Geitung, A., Soleim, H., Patel, D.: Multi-GPU rendering with the open Vulkan API. In: Norsk IKT-konferanse for forskning og utdanning (2018)
[26]
Wang F, Ito T, and Shimobaba T High-speed rendering pipeline for polygon-based holograms Photon. Res. 2023 11 2 313-328
[27]
Whitted, T.: An improved illumination model for shaded display. In: ACM Siggraph 2005 Courses, p. 4-es (2005)
[28]
Wihlidal, G.: Optimizing the graphics pipeline with compute. In: Game Developers Conference, vol. 2 (2016)
[29]
Willems, S.: Examples and demos for the new Vulkan API (2018). https://github.com/SaschaWillems/Vulkan
[30]
Zhang B, Sheng B, Li P, and Lee TY Depth of field rendering using multilayer-neighborhood optimization IEEE Trans. Vis. Comput. Graph. 2019 26 8 2546-2559
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Information
Published In
Aug 2023
517 pages
ISBN:978-3-031-50071-8
DOI:10.1007/978-3-031-50072-5
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Publisher
Springer-Verlag
Berlin, Heidelberg
Publication History
Published: 29 December 2023
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