“Real-time rendering on a power budget” by Wang, Yu, Marco, Hu, Gutierrez, et al. …

  • ©Rui Wang, Bowen Yu, Julio Marco, Tianlei Hu, Diego Gutierrez, and Hujun Bao

Conference:


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Title:

    Real-time rendering on a power budget

Session/Category Title:   RENDERING & SIMULATION WITH GPUS


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Abstract:


    With recent advances on mobile computing, power consumption has become a significant limiting constraint for many graphics applications. As a result, rendering on a power budget arises as an emerging demand. In this paper, we present a real-time, power-optimal rendering framework to address this problem, by finding the optimal rendering settings that minimize power consumption while maximizing visual quality. We first introduce a novel power-error, multi-objective cost space, and formally formulate power saving as an optimization problem. Then, we develop a two-step algorithm to efficiently explore the vast power-error space and leverage optimal Pareto frontiers at runtime. Finally, we show that our rendering framework can be generalized across different platforms, desktop PC or mobile device, by demonstrating its performance on our own OpenGL rendering framework, as well as the commercially available Unreal Engine.

References:


    1. Akenine-Möller, T., and Strom, J. 2008. Graphics processing units for handhelds. Proceedings of the IEEE 96, 5 (May), 779–789.Google ScholarCross Ref
    2. Arnau, J.-M., Parcerisa, J.-M., and Xekalakis, P. 2014. Eliminating redundant fragment shader executions on a mobile GPU via hardware memoization. SIGARCH Comput. Archit. News 42, 3 (June), 529–540. Google ScholarDigital Library
    3. Beloglazov, A., Abawajy, J., and Buyya, R. 2012. Energy-aware resource allocation heuristics for efficient management of data centers for cloud computing. Future Gener. Comput. Syst. 28, 5 (May), 755–768. Google ScholarDigital Library
    4. Chen, H., Wang, J., Chen, W., Qu, H., and Chen, W. 2014. An image-space energy-saving visualization scheme for OLED displays. Computers & Graphics 38, 61–68. Google ScholarDigital Library
    5. Chen, W., Chen, W., Chen, H., Zhang, Z., and Qu, H. 2016. An energy-saving color scheme for direct volume rendering. Computers & Graphics 54, 57–64. Google ScholarDigital Library
    6. Cheng, W.-C., and Pedram, M. 2004. Power minimization in a backlit TFT-LCD display by concurrent brightness and contrast scaling. IEEE Transactions on Consumer Electronics 50, 1, 25–32. Google ScholarDigital Library
    7. Chuang, J., Weiskopf, D., and Mller, T. 2009. Energy aware color sets. Computer Graphics Forum 28, 2, 203–211.Google ScholarCross Ref
    8. Cohade, A., and de los Santos, S. 2015. Power efficient programming: How funcom increased play time in lego minifigures. In Game Developer’s Conference.Google Scholar
    9. Colbert, M., and Krivánek, J. 2007. GPU-based importance sampling. GPU Gems 3, 459–476.Google Scholar
    10. Deb, K., Pratap, A., Agarwal, S., and Meyarivan, T. 2002. A fast and elitist multiobjective genetic algorithm: NSGA-II. Trans. Evol. Comp 6, 2, 182–197. Google ScholarDigital Library
    11. Dong, M., and Zhong, L. 2012. Power modeling and optimization for oled displays. IEEE Transactions on Mobile Computing 11, 9, 1587–1599. Google ScholarDigital Library
    12. Dong, M., Choi, Y.-S. K., and Zhong, L. 2009. Power-saving color transformation of mobile graphical user interfaces on oled-based displays. In Proceedings of the 2009 ACM/IEEE International Symposium on Low Power Electronics and Design, ISLPED ’09, 339–342. Google ScholarDigital Library
    13. Forrest, S. R. 2003. The road to high efficiency organic light emitting devices. Organic Electronics 4, 2-3, 45–48.Google ScholarCross Ref
    14. Gharbi, M., Shih, Y., Chaurasia, G., Ragan-Kelley, J., Paris, S., and Durand, F. 2015. Transform recipes for efficient cloud photo enhancement. ACM Trans. Graph. 34, 6 (Oct.), 228:1–228:12. Google ScholarDigital Library
    15. He, Y., Foley, T., Tatarchuk, N., and Fatahalian, K. 2015. A system for rapid, automatic shader level-of-detail. ACM Trans. Graph. 34, 6 (Oct.), 187:1–187:12. Google ScholarDigital Library
    16. Iyer, S., Luo, L., Mayo, R., and Ranganathan, P. 2003. Energy-adaptive display system designs for future mobile environments. In Proceedings of the 1st International Conference on Mobile Systems, Applications and Services, MobiSys ’03, 245–258. Google ScholarDigital Library
    17. Jimenez, J., Masia, B., Echevarria, J. I., Navarro, F., and Gutierrez, D. 2011. GPU Pro 2.Google Scholar
    18. Johnsson, B., Ganestam, P., Doggett, M., and Akenine-Möller, T. 2012. Power efficiency for software algorithms running on graphics processors. In Proceedings of the Fourth ACM SIGGRAPH / Eurographics Conference on High-Performance Graphics, Eurographics Association, Aire-la-Ville, Switzerland, Switzerland, EGGH-HPG’12, 67–75. Google ScholarDigital Library
    19. Johnsson, B. M. 2014. Energy Analysis for Graphics Processors using Novel Methods & Efficient Multi-View Rendering. PhD thesis, Lund University.Google Scholar
    20. Kajalin, V. 2009. Screen space ambient occlusion. Shader X 7, 413, 24.Google Scholar
    21. Kyung, C.-M., and Yoo, S. 2014. Energy-Aware System Design: Algorithms and Architectures. Springer Publishing Company, Incorporated. Google ScholarDigital Library
    22. Masia, B., Wetzstein, G., Didyk, P., and Gutierrez, D. 2013. A survey on computational displays: Pushing the boundaries of optics, computation, and perception. Computers & Graphics 37, 8, 1012–1038. Google ScholarDigital Library
    23. Mavridis, P., and Papaioannou, G. 2015. MSAA-based coarse shading for power-efficient rendering on high pixel-density displays. In High Performance Graphics.Google Scholar
    24. Moshnyaga, T., and Morikawa, E. 2005. LCD display energy reduction by user monitoring. In IEEE international conference on computer design. Google ScholarDigital Library
    25. Narra, P., and Zinger, D. 2004. An effective LED dimming approach. In IEEE industry applications conference.Google Scholar
    26. NVML, 2015. NVIDIA Management Library. https://developer.nvidia.com/nvidia-management-library-nvml.Google Scholar
    27. Peddie, J. 2013. Trends and forecasts in computer graphics –power-efficient rendering. In Jon Peddie Research.Google Scholar
    28. Pellacini, F. 2005. User-configurable automatic shader simplification. ACM Trans. Graph. 24, 3 (July), 445–452. Google ScholarDigital Library
    29. Pool, J. 2012. Energy-precision tradeoffs in the graphics pipeline. PhD thesis, University of North Carolina at Chapel Hill. Google ScholarDigital Library
    30. PowerVR. 2012. PowerVR: A master class in graphics technology and optimization. In Imagination Technologies.Google Scholar
    31. Ranganathan, P., Geelhoed, E., Manahan, M., and Nicholas, K. 2006. Energy-aware user interfaces and energy-adaptive displays. Computer 39, 3, 31–38. Google ScholarDigital Library
    32. Shearer, F. 2007. Power Management in Mobile Devices. Elsevier Inc. Google ScholarDigital Library
    33. Sitthi-amorn, P., Modly, N., Weimer, W., and Lawrence, J. 2011. Genetic programming for shader simplification. ACM Trans. Graph. 30, 6, 152. Google ScholarDigital Library
    34. Stavrakis, E., Polychronis, M., Pelekanos, N., Artusi, A., Hadjichristodoulou, P., and Chrysanthou, Y. 2015. Toward energy-aware balancing of mobile graphics. In IS&T/SPIE Electronic Imaging, International Society for Optics and Photonics, 94110D–94110D.Google Scholar
    35. UnrealEngine, 2015. Unreal Engine. https://www.unrealengine.com/.Google Scholar
    36. Vaidyanathan, K., Salvi, M., Toth, R., Foley, T., Akenine-Möller, T., Nilsson, J., Munkberg, J., Hasselgren, J., Sugihara, M., Clarberg, P., et al. 2014. Coarse pixel shading. In High Performance Graphics.Google Scholar
    37. Vallerio, K. S., Zhong, L., and Jha, N. K. 2006. Energy-efficient graphical user interface design. IEEE Transactions on Mobile Computing 5, 7 (July), 846–859. Google ScholarDigital Library
    38. Wang, Z., Bovik, A. C., Sheikh, H. R., and Simoncelli, E. P. 2004. Image quality assessment: from error visibility to structural similarity. Image Processing, IEEE Transactions on 13, 4, 600–612. Google ScholarDigital Library
    39. Wang, R., Yang, X., Yuan, Y., Chen, W., Bala, K., and Bao, H. 2015. Automatic shader simplification using surface signal approximation. ACM Trans. Graph. 33, 6 (Nov.), 226:1–226:11. Google ScholarDigital Library
    40. Woo, R., Yoon, C.-W., Kook, J., Lee, S.-J., and Yoo, H.-J. 2002. A 120-mW 3-D rendering engine with 6-Mb embedded DRAM and 3.2-GB/s runtime reconfigurable bus for PDA chip. Solid-State Circuits, IEEE Journal of 37, 10 (Oct), 1352–1355.Google Scholar


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