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The High Performance Computing for 3D Dynamic Holographic Simulation Based on Multi-GPU Cluster

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Book cover Theory, Methodology, Tools and Applications for Modeling and Simulation of Complex Systems (AsiaSim 2016, SCS AutumnSim 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 643))

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Abstract

Two different methods for high performance calculation cluster are proposed to optimize holographic algorithms of computer generated holography (CGH). We completed the numerical simulations and finish the experience. Results show that we can reconstruct a satisfied object by using our holography. Moreover, the computation process of CGH for three-dimensional (3D) dynamic holographic display has been sped up by programming with these methods. Not only can it optimize file loading process but also inline calculation process. The CGH of gigabyte data is generated finally. Besides, the first method can effectively reduce time costs of loading and writing files on CPU. It is believed the proposed method can support the huge data processing for 3D dynamic holographic simulation and virtual reality in near future.

This work was supported by the national 863 program (2015AA042101).

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References

  1. Hao, Q.-Y., Mao-Bin, H., Cheng, X.-Q., Song, W.-G., Jiang, R., Qing-Song, W.: Pedestrian flow in a lattice gas model with parallel update. Phys. Rev. E 82(2), 2365–2376 (2010)

    Article  Google Scholar 

  2. Zhang, H., Xie, J., Liu, J., et al.: Elimination of a zero-order beam induced by a pixelated spatial light modulator for holographic projection. Appl. Opt. 48(30), 5834–5841 (2009)

    Article  Google Scholar 

  3. Zhang, H., Tan, Q., Jin, G.: Holographic display system of a three-dimensional image with distortion-free magnification and zero-order elimination. Opt. Eng. 51, 075801 (2012)

    Article  Google Scholar 

  4. Zhang, H., Collings, N., Chen, J., et al.: Full parallax three-dimensional display with occlusion effect using computer generated hologram. Opt. Eng. 50(7), 074003-1–074003-5 (2011)

    Google Scholar 

  5. Jia, J., Wang, Y., Liu, J. et al.: 3D holographic display with enlarged image using a concave reflecting mirror. In: Proceedings of SPIE, vol 8557: 85570B_1–5 (2012)

    Google Scholar 

  6. Ichihashi, Y., Oi, R., Senoh, T., Yamamoto, K., Kurita, T.: Real-time capture and reconstruction systemwith multiple GPUs for a 3D live scene by ageneration from 4 K IP images to 8 K holograms. Opt. Express 20(19), 21645–24655 (2012)

    Article  Google Scholar 

  7. Stein, A.D., Wang Jr., Z., Leigh, J.S.: Computer-generated holograms: a simplified ray-tracing approach. Comput. Phys. 6, 389 (1992)

    Article  Google Scholar 

  8. Lucente, M.: Interactive computation of holograms using a look-up table. J. Electr. Imag. 2, 28–34 (1993)

    Article  Google Scholar 

  9. Pan, Y., Xu, X., Solanki, S., et al.: Fast CGH computation using S-LUT on GPU. Opt. Express 17(21), 18543–18555 (2009)

    Article  Google Scholar 

  10. Jia, J., Wang, Y., Liu, J., Li, X., et al.: Reducing the memory usage for effective computer-generated hologram calculation using compressed look-up table in full-color holographic display. Appl. Opt. 52(7), 1404–1412 (2013)

    Article  Google Scholar 

  11. Zhang, Y., Wang, P., Chen, H., et al.: Computer-generated-hologram-accelerated computing method based on mixed programming. Chin. Opt. Lett. 12(3), 030902-1–030902-4 (2014)

    Google Scholar 

  12. Jia, J., Wang, Y., Liu, J., et al.: Progress of dynamic 3D display of the computer-generated hologram. Laser & Optoelectronics Progress 49(5), 050002 (2012)

    Article  Google Scholar 

  13. Shimobaba, T., Ito, T., Masuda, N., et al.: Fast calculation of computer-generated-hologram on AMD HD5000 series GPU and OpenCL. Opt. Express 18(10), 9955–9960 (2010)

    Article  Google Scholar 

  14. Ahrenberg, L., Benzie, P., Magnor, M., et al.: Computer generated holography using parallel commodity graphics hardware. Opt. Express 14(17), 7636–7641 (2006)

    Article  Google Scholar 

  15. Pan, Y., Xu, X., Liang, X.: Fast distributed large-pixel-count hologram computation using a GPU cluster. Appl. Opt. 52(26), 6562–6571 (2013)

    Article  Google Scholar 

  16. Jackin, B.J., Miyata, H., Ohkawa, T., et al.: Distributed calculation method for large pixel-number holograms by decomposition of object and hologram planes. Opt. Letters 39(24), 6867–6870 (2014)

    Article  Google Scholar 

  17. Merrill, D., Grimshaw, A.: High performance and scalable radix sorting: a case study of implementing dynamic parallelism for GPU computing. Parallel Process Lett. 21(2), 245–272 (2011)

    Article  MathSciNet  Google Scholar 

  18. Dong, J., Wang, F., Yuan, B.: Accelerating BIRCH for clustering large scale streaming data using CUDA dynamic parallelism. In: Yin, H., Tang, K., Gao, Y., Klawonn, F., Lee, M., Weise, T., Li, B., Yao, X. (eds.) IDEAL 2013. LNCS, vol. 8206, pp. 409–416. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  19. Wang, J., Yalamanchili, S.: Characterization and analysis of dynamic parallelism in unstructured GPU applications. In: Proceedings of the 2014 IEEE International Symposium on Work-load Characterization (2014)

    Google Scholar 

  20. Sun, Z.: Application of File Mapping in the Real-time Historical Database of DCS. Comput. Knowl. Technol. 9(19), 4363–4366 (2013)

    Google Scholar 

  21. Zheng, G., Muhlenbernd, H., Kenney, M., Li, G., Zentgraf, T., Zhang, S.: Metasurface holograms reaching 80 % efficiency. Nat. Nanotechnol. 10, 308–312 (2015)

    Article  Google Scholar 

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Correspondence to Zhang Yingxi .

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Yingxi, Z., Tingyu, L., Liqin, G. (2016). The High Performance Computing for 3D Dynamic Holographic Simulation Based on Multi-GPU Cluster. In: Zhang, L., Song, X., Wu, Y. (eds) Theory, Methodology, Tools and Applications for Modeling and Simulation of Complex Systems. AsiaSim SCS AutumnSim 2016 2016. Communications in Computer and Information Science, vol 643. Springer, Singapore. https://doi.org/10.1007/978-981-10-2663-8_45

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  • DOI: https://doi.org/10.1007/978-981-10-2663-8_45

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  • Print ISBN: 978-981-10-2662-1

  • Online ISBN: 978-981-10-2663-8

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