Journal of Frontiers of Computer Science and Technology ›› 2023, Vol. 17 ›› Issue (2): 263-278.DOI: 10.3778/j.issn.1673-9418.2207067
• Frontiers·Surveys • Previous Articles Next Articles
YAN Run, HUANG Libo, GUO Hui, WANG Yongxin, ZHANG Xincheng, ZHANG Hongru
Online:
2023-02-01
Published:
2023-02-01
闫润,黄立波,郭辉,王永鑫,张鑫铖,张鸿儒
YAN Run, HUANG Libo, GUO Hui, WANG Yongxin, ZHANG Xincheng, ZHANG Hongru. Review of Real-Time Ray Tracing Technique Research[J]. Journal of Frontiers of Computer Science and Technology, 2023, 17(2): 263-278.
闫润, 黄立波, 郭辉, 王永鑫, 张鑫铖, 张鸿儒. 实时光线追踪相关研究综述[J]. 计算机科学与探索, 2023, 17(2): 263-278.
Add to citation manager EndNote|Ris|BibTeX
URL: http://fcst.ceaj.org/EN/10.3778/j.issn.1673-9418.2207067
[1] BURLEY B, ADLER D, CHIANG J Y, et al. The design and evolution of Disney??s hyperion renderer[J]. ACM Transactions on Graphics, 2018, 37(3): 1-22. [2] CHRISTENSEN P, FONG J, SHADE J, et al. RenderMan: an advanced path-tracing architecture for movie rendering[J]. ACM Transactions on Graphics, 2018, 37(3): 1-21. [3] FASCIONE L, HANIKA J, LEONE M, et al. Manuka: a batch-shading architecture for spectral path tracing in movie production[J]. ACM Transactions on Graphics, 2018, 37(3): 1-18. [4] MARRS A, SHIRLEY P, WALD I. Ray tracing gems II: next generation real-time rendering with DXR, Vulkan, and OptiX[M]. California: Springer Nature, 2021. [5] HAINES E, HOFFMAN N. Real-time rendering[M]. Boca Raton: CRC Press, 2018. [6] WHITTED T. An improved illumination model for shaded display[C]//Proceedings of the 6th Annual Conference on Computer Graphics and Interactive Techniques, Chicago, Aug 8-10, 1979. New York: ACM, 1979: 14. [7] FUJIMOTO A, TANAKA T, IWATA K J C G, et al. ARTS: accelerated ray-tracing system[J]. IEEE Computer Graphics and Applications, 1986, 6(4): 16-26. [8] NERY A S, NEDJAH N. GridRT: a massively parallel architecture for ray-tracing using uniform grids[C]//Proceedings of the 12th Euromicro Conference on Digital System Design, Architectures, Methods and Tools, Patras, Aug 27-29, 2009. Washington: IEEE Computer Society, 2009: 211-216. [9] BENTLEY J L. Multidimensional binary search trees used for associative searching[J]. Communications of the ACM, 1975, 18(9): 509-517. [10] CLARK J H. Hierarchical geometric models for visible surface algorithms[J]. Communications of the ACM, 1976, 19(10): 547-554. [11] HAVRAN V. Heuristic ray shooting algorithms[D]. Prague: Czech Technical University, 2000. [12] MEISTER D, OGAKI S, BENTHIN C, et al. A survey on bounding volume hierarchies for ray tracing[J]. Computer Graphics Forum, 2021, 40(2): 683-712. [13] NVIDIA. NVIDIA Ampere GA102 GPU architecture[R/OL]. [2022-05-01]. https://www.nvidia.com/content/PDF/nvidia-ampere-ga-102-gpu-architecture-whitepaper-v2.1.pdf. [14] AMD. RDNA2 architecture[R/OL]. [2022-05-01]. https://www.amd.com/en/technologies/rdna-2. [15] BEETS K. Introduction to the PowerVR Photon architecture[R/OL]. [2022-05-01]. https://www.imaginationtech.com/products/gpu/graphics-architecture/powervr-photon/. [16] BURGESS J. RTX on—the NVIDIA turing GPU[J]. IEEE Micro, 2020, 40(2): 36-44. [17] SHKURKO K, YUKSEL C, KOPTA D, et al. Time interval ray tracing for motion blur[J]. IEEE Transactions on Visualization and Computer Graphics, 2017, 24(12): 3225-3238. [18] LIU E. DLSS 2.0-image reconstruction for real-time rendering with deep learning[C]//Proceedings of the GPU Technology Conference, California, Mar 23, 2020. [19] AMD. AMD FidelityFXTM super resolution[R/OL]. [2022-05-01]. https://www.amd.com/en/technologies/fidelityfx-super-resolution. [20] WALD I, SLUSALLEK P, BENTHIN C, et al. Interactive rendering with coherent ray tracing[J]. Computer Graphics Forum, 2001, 20(3): 153-165. [21] BOULOS S, EDWARDS D, LACEWELL J D, et al. Packet-based whitted and distribution ray tracing[C]//Proceedings of the Graphics Interface 2007 Conference, Montreal, May 28-30, 2007. New York: ACM, 2007: 177-184. [22] GUNTHER J, POPOV S, SEIDEL H P, et al. Realtime ray tracing on GPU with BVH-based packet traversal[C]//Proceedings of the 2007 IEEE Symposium on Interactive Ray Tracing, Ulm, Sep 10-12, 2007. Piscataway: IEEE, 2007: 113-118. [23] MANSSON E, MUNKBERG J, AKENINE-MOLLER T. Deep coherent ray tracing[C]//Proceedings of the 2007 IEEE Symposium on Interactive Ray Tracing, Ulm, Sep 10-12, 2007. Piscataway: IEEE, 2007: 79-85. [24] RESHETOV A, SOUPIKOV A, HURLEY J. Multi-level ray tracing algorithm[J]. ACM Transactions on Graphics, 2005, 24(3): 1176-1185. [25] OVERBECK R, RAMAMOORTHI R, MARK W R. Large ray packets for real-time whitted ray tracing[C]//Proceedings of the 2008 IEEE Symposium on Interactive Ray Tracing, Los Angeles, Aug 9-10, 2008. Piscataway: IEEE, 2008: 41-48. [26] AILA T, LAINE S. Understanding the efficiency of ray traversal on GPUs[C]//Proceedings of the Conference on High Performance Graphics 2009, New Orleans, Aug 1-3, 2009. New York: ACM, 2009: 145-149. [27] BENTHIN C, WALD I, WOOP S, et al. Combining single and packet-ray tracing for arbitrary ray distributions on the Intel MIC architecture[J]. IEEE Transactions on Visualization and Computer Graphics, 2011, 18(9): 1438-1448. [28] FUETTERLING V, LOJEWSKI C, PFREUNDT F J, et al. Accelerated single ray tracing for wide vector units[C]//Proceedings of the High Performance Graphics 2017, Los Angeles, Jul 28-30, 2017. New York: ACM, 2017: 1-9. [29] SMITS B E. Efficiency issues for ray tracing[C]//Proceedings of the 2005 International Conference on Computer Graphics and Interactive Techniques, Los Angeles, Jul 31-Aug 4, 2005. New York: ACM, 2005: 6. [30] FOLEY T, SUGERMAN J. KD-tree acceleration structures for a GPU raytracer[C]//Proceedings of the ACM SIGGRAPH/EUROGRAPHICS Symposium on Graphics Hardware 2005, Los Angeles, Jul 30-31, 2005. Aire-la-Ville: Eurographics Association, 2005: 15-22. [31] THRANE N, SIMONSEN L O. A comparison of acceleration structures for GPU assisted ray tracing[D]. Aarhus: University of Aarhus, 2005. [32] POPOV S, GüNTHER J, SEIDEL H P, et al. Stackless KD-tree traversal for high performance GPU ray tracing[J]. Computer Graphics Forum, 2007, 26(3): 415-424. [33] LAINE S. Restart trail for stackless BVH traversal[C]//Proceedings of the 2010 Conference on High Performance Gra-phics, Saarbrucken, Jun 25-27, 2010. Aire-la-Ville: Eurographics Association, 2010: 107-111. [34] HAPALA M, DAVIDOVI? T, WALD I, et al. Efficient stack-less BVH traversal for ray tracing[C]//Proceedings of the 27th Spring Conference on Computer Graphics, Vinicné, Apr 28-30, 2011. New York: ACM, 2011: 7-12. [35] BINDER N, KELLER A. Efficient stackless hierarchy traversal on GPUs with backtracking in constant time[C]//Proceedings of the High Performance Graphics 2016, Dublin, Jun 20-22, 2016. New York: ACM, 2016: 41-50. [36] VAIDYANATHAN K, WOOP S, BENTHIN C. Wide BVH traversal with a short stack[C]//Proceedings of the 2019 Conference on High Performance Graphics. Aire-la-Ville: Eurographics Association, 2019: 15-19. [37] REIS N T, COSTA V S, PEREIRA J M. Coherent ray-space hierarchy via ray hashing and sorting[C]//Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, Porto, Feb 27-Mar 1, 2017: 195-202. [38] COSTA V, PEREIRA J M, JORGE J A, et al. Accelerating occlusion rendering on a GPU via ray classification[J]. International Journal of Creative Interfaces and Computer Graphics, 2015, 6(2): 1-17. [39] AILA T, KARRAS T. Architecture considerations for tracing incoherent rays[C]//Proceedings of the 2010 Conference on High Performance Graphics, Saarbrucken, Jun 25-27, 2010. Aire-la-Ville: Eurographics Association, 2010: 113-122. [40] MOON B, BYUN Y, KIM T J, et al. Cache-oblivious ray reordering[J]. ACM Transactions on Graphics, 2010, 29(3): 1-10. [41] MEISTER D, BOKSANSKY J, GUTHE M, et al. On ray reordering techniques for faster GPU ray tracing[C]//Proceedings of the 2020 Symposium on Interactive 3D Graphics and Games, San Francisco, May 5-7, 2020. New York: ACM, 2020: 1-9. [42] MICROSOFT. DirectX raytracing (DXR) functional Spec[R/OL]. [2022-05-01]. https://microsoft.github.io/DirectX-Specs/d3d/Raytracing.html. [43] NVIDIA. NVIDIA OptiX 7.2-Programming guide[R/OL]. [2022-05-01]. https://docs.nvidia.com/gameworks/content/gameworkslibrary/optix/optix_programming_guide.htm. [44] CHRISTENSEN P H, FONG J, LAUR D M, et al. Ray tracing for the movie ‘Cars’[C]//Proceedings of the 2006 IEEE Symposium on Interactive Ray Tracing, Salt Lake City, Sep 18-20, 2006. Piscataway: IEEE, 2006: 1-6. [45] WALD I, BENTHIN C, BOULOS S J I. Getting rid of packets-efficient SIMD single-ray traversal using multi-branching BVHs[C]//Proceedings of the 2008 IEEE Symposium on Interactive Ray Tracing, Los Angeles, Aug 9-10, 2008. Piscataway: IEEE, 2008: 49-57. [46] ERNST M, GREINER G. Multi bounding volume hierarchies[C]//Proceedings of the 2008 IEEE Symposium on Interactive Ray Tracing, Los Angeles, Aug 9-10, 2008. Piscataway: IEEE, 2008: 35-40. [47] GUTHE M. Latency considerations of depth-first GPU ray tracing[C]//Proceedings of the 35th Annual Conference of the European Association for Computer Graphics, Strasbourg, Apr 7-11, 2014. Aire-la-Ville: Eurographics Association, 2014: 53-56. [48] YLITIE H, KARRAS T, LAINE S. Efficient incoherent ray traversal on GPUs through compressed wide BVHs[C]//Proceedings of the High Performance Graphics 2017, Los Angeles, Jul 28-30, 2017. New York: ACM, 2017: 1-13. [49] BENTHIN C, WALD I, WOOP S, et al. Compressed-leaf bounding volume hierarchies[C]//Proceedings of the High-Performance Graphics 2018, Vancouver, Aug 10-12, 2018. New York: ACM, 2018: 1-4. [50] LIER A, STAMMINGER M, KAI S. CPU-style simd ray traversal on GPUs[C]//Proceedings of the High Performance Graphics 2018, Vancouver, 2018. New York: ACM, 2018: 1-4. [51] MCGUIRE M, LUEBKE D. Hardware-accelerated global illumination by image space photon mapping[C]//Proceedings of the High Performance Graphics 2009, New Orleans, Aug 1-3, 2009. New York: ACM: 77-89. [52] PARK S, BAEK N. A shader-based ray tracing engine[J]. Applied Sciences, 2021, 11(7): 3264. [53] DAMMERTZ H, SEWTZ D, HANIKA J, et al. Edge-avoiding A-trous wavelet transform for fast global illumination filtering[C]//Proceedings of the High Performance Graphics 2010, Saarbrucken, Jun 25-27, 2010. New York: ACM, 2010: 67-75. [54] SCHIED C, KAPLANYAN A, WYMAN C, et al. Spatiotemporal variance-guided filtering: real-time reconstruction for path-traced global illumination[C]//Proceedings of the High Performance Graphics 2017, Los Angeles, Jul 28-30, 2017. New York: ACM, 2017: 1-12. [55] MARA M, MCGUIRE M, BITTERLI B, et al. An efficient denoising algorithm for global illumination[C]//Proceedings of the High Performance Graphics 2017, Los Angeles, Jul 28-30, 2017. New York: ACM, 2017: 3105762-3105774. [56] ROUSSELLE F, KNAUS C, ZWICKER M. Adaptive rendering with non-local means filtering[J]. ACM Transactions on Graphics, 2012, 31(6): 1-11. [57] KALANTARI N K, BAKO S, SEN P. A machine learning approach for filtering Monte Carlo noise[J]. ACM Transactions on Graphics, 2015, 34(4): 122. [58] VOGELS T, ROUSSELLE F, MCWILLIAMS B, et al. Denoising with kernel prediction and asymmetric loss functions[J]. ACM Transactions on Graphics, 2018, 37(4): 1-15. [59] XU B, ZHANG J, WANG R, et al. Adversarial Monte Carlo denoising with conditioned auxiliary feature modulation[J]. ACM Transactions on Graphics, 2019, 38(6): 224. [60] YANG L, LIU S, SALVI M. A survey of temporal antialiasing techniques[J]. Computer Graphics Forum, 2020, 39(2): 607-621. [61] SCHIED C, PETERS C, DACHSBACHER C. Gradient estimation for real-time adaptive temporal filtering[J]. Proceedings of the ACM on Computer Graphics and Interactive Techniques, 2018, 1(2): 1-16. [62] KOSKELA M, IMMONEN K, M?KITALO M, et al. Blockwise multi-order feature regression for real-time path-tracing reconstruction[J]. ACM Transactions on Graphics, 2019, 38(5): 1-14. [63] NVIDIA. RTX global illumination (RTXGI)[R/OL]. [2022-05-01]. https: //developer.nvidia.com/rtx/ray-tracing/rtxgi. [64] MAJERCIK Z, MARRS A, SPJUT J, et al. Scaling probe-based real-time dynamic global illumination for production[J]. arXiv:2009.10796, 2020. [65] CHAITANYA C R A, KAPLANYAN A S, SCHIED C, et al. Interactive reconstruction of Monte Carlo image sequences using a recurrent denoising autoencoder[J]. ACM Transactions on Graphics, 2017, 36(4): 1-12. [66] HOFMANN N, HASSELGREN J, CLARBERG P, et al. Interactive path tracing and reconstruction of sparse volumes[J]. Proceedings of the ACM on Computer Graphics and Interactive Techniques, 2021, 4(1): 1-19. [67] KETTUNEN M, H?RK?NEN E, LEHTINEN J. Deep convolutional reconstruction for gradient-domain rendering[J]. ACM Transactions on Graphics, 2019, 38(4): 1-12. [68] VERBIN D, HEDMAN P, MILDENHALL B, et al. Ref-NeRF: structured view-dependent appearance for neural radiance fields[C]//Proceedings of the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition, New Orleans, Jun 21-24, 2022. Piscataway: IEEE, 2022: 5481-5490. [69] DAHM K, KELLER A. Learning light transport the reinforced way[C]//Proceedings of the ACM SIGGRAPH 2017 Talks, Los Angeles, Jul 30-Aug 3, 2017. New York: ACM, 2017: 1-2. [70] DONG C, LOY C C, HE K, et al. Image super-resolution using deep convolutional networks[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015, 38(2): 295-307. [71] LEDIG C, THEIS L, HUSZáR F, et al. Photo-realistic single image super-resolution using a generative adversarial network[C]//Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, Boston, Jun 7-12, 2017. Washington: IEEE Computer Society, 2017: 4681-4690. [72] XIAO L, NOURI S, CHAPMAN M, et al. Neural supersampling for real-time rendering[J]. ACM Transactions on Graphics, 2020, 39(4): 142. [73] THOMAS M M, LIKTOR G, PETERS C, et al. Temporally stable real-time joint neural denoising and supersampling[J]. Proceedings of the ACM on Computer Graphics and Interactive Techniques, 2022, 5(3): 1-22. [74] CHOWDHURY H, KAWIAK R, DE BOER R, et al. Intel XeSS—an AI based super sampling solution for real-time rendering[C]//Proceedings of the Game Developers Conference 2022, San Francisco, Mar 21-25, 2022. [75] CARR N A, HALL J D, HART J C. The ray engine[C]//Proceedings of the 2002 ACM SIGGRAPH/EUROGRAPHICS on Graphics Hardware, Saarbrucken, Sep 1-2, 2002. New York: ACM, 2002: 37-46. [76] PURCELL T J, BUCK I, MARK W R, et al. Ray tracing on programmable graphics hardware[C]//Proceedings of the ACM SIGGRAPH 2005 Courses, Los Angeles, Jul 31-Aug 4, 2005. New York: ACM, 2005. [77] AILA T, LAINE S, KARRAS T. Understanding the efficiency of ray traversal on GPUs—Kepler and Fermi addendum: NVR-2012-002[R]. City of Santa Clara, 2012. [78] HANIKA J, KELLER A. Towards hardware ray tracing using fixed point arithmetic[C]//Proceedings of the 2007 IEEE Symposium on Interactive Ray Tracing, Ulm, Sep 10-12, 2007. Piscataway: IEEE, 2007: 119-128. [79] HEINLY J, RECKER S, BENSEMA K, et al. Integer ray tracing[J]. Journal of Graphics, GPU, and Game Tools, 2009, 14(4): 31-56. [80] KEELY S. Reduced precision for hardware ray tracing in GPUs[C]//Proceedings of the High Performance Graphics 2014, Goslar, Jun 23-25, 2014. New York: ACM, 2014: 29-40. [81] VAIDYANATHAN K, AKENINE-M?LLER T, SALVI M. Watertight ray traversal with reduced precision[C]//Proceedings of the High Performance Graphics 2016, Goslar, Jun 20-22, 2016. New York: ACM, 2016: 33-40. [82] LIKTOR G, VAIDYANATHAN K. Bandwidth-efficient BVH layout for incremental hardware traversal[C]//Proceedings of the High Performance Graphics 2016. New York: ACM, 2016: 51-61. [83] Lü Y S, HUANG L B, SHEN L, et al. Unleashing the power of GPU for physically-based rendering via dynamic ray shuffling[C]//Proceedings of the 50th Annual IEEE/ACM International Symposium on Microarchitecture, Massachusetts, Oct 14-18, 2017. New York: ACM, 2017: 560-573. [84] BAKHODA A, YUAN G L, FUNG W W, et al. Analyzing CUDA workloads using a detailed GPU simulator[C]//Proceedings of the 2009 IEEE International Symposium on Performance Analysis of Systems and Software, Boston, Apr 26-28, 2009. Piscataway: IEEE, 2009: 163-174. [85] LIU L, CHANG W, DEMOULLIN F, et al. Intersection prediction for accelerated GPU ray tracing[C]//Proceedings of the MICRO-54: 54th Annual IEEE/ACM International Symposium on Microarchitecture, Greece, Oct 18-22, 2021. New York: ACM, 2021: 709-723. [86] NI Y, DENG Y, LI Z, et al. Agglomerative memory and thread scheduling for high-performance ray-tracing on GPUs[J]. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2021, 41(2): 334-345. [87] HALL D. The AR350: today’s ray trace rendering processor[C]//Proceedings of the 2001 Eurographics/SIGGRAPH Workshop on Graphics Hardware-Hot 3D Session, Los Angeles, 2001: 13-19. [88] KOBAYASHI H, SUZUKI K, SANO K, et al. Interactive ray-tracing on the 3DCGiRAM architecture[C]//Proceedings of the ACM/IEEE MICRO-35, Istanbul, Nov 18-22, 2002. New York: ACM, 2002. [89] FENDER J, ROSE J. A high-speed ray tracing engine built on a field-programmable system[C]//Proceedings of the 2003 IEEE International Conference on Field-Programmable Technology, Tokyo, Dec 15-17, 2003. Piscataway: IEEE, 2004: 188-195. [90] WOOP S, SCHMITTLER J, SLUSALLEK P. RPU: a programmable ray processing unit for realtime ray tracing[J]. ACM Transactions on Graphics, 2005, 24(3): 434-444. [91] SCHMITTLER J. SaarCOR: a hardware architecture for real-time ray tracing[C]//Proceedings of the Graphics Hardware 2006, Goslar, Sep 1-2, 2006. New York: ACM, 2006: 27-36. [92] SCHMITTLER J, WOOP S, WAGNER D, et al. Realtime ray tracing of dynamic scenes on an FPGA chip[C]//Proceedings of the Graphics Hardware 2004, Grenoble, Aug 29-30, 2004. New York: ACM, 2004: 95-106. [93] WOOP S, BRUNVAND E, SLUSALLEK P. Estimating performance of a ray-tracing ASIC design[C]//Proceedings of the 2006 IEEE Symposium on Interactive Ray Tracing, Salt Lake City, Sep 18-20, 2006. Piscataway: IEEE, 2006: 7-14. [94] WOOP S. A programmable hardware architecture for realtime ray tracing of coherent dynamic scenes[D]. Saarbrücken: Sarrland University, 2007. [95] NAH J H, PARK J S, PARK C, et al. T&I engine: traversal and intersection engine for hardware accelerated ray tracing[C]//Proceedings of the 2011 SIGGRAPH Asia Conference, Hong Kong, Dec 12-15, 2011. New York: ACM, 2011: 1-10. [96] NAH J H, KWON H J, KIM D S, et al. RayCore: a ray-tracing hardware architecture for mobile devices[J]. ACM Transactions on Graphics, 2014, 33(5): 1-15. [97] LEE W J, SHIN Y, LEE J, et al. SGRT: a mobile GPU architecture for real-time ray tracing[C]//Proceedings of the 5th High-Performance Graphics Conference, Anaheim, Jul 19-21, 2013. New York: ACM, 2013: 109-119. [98] LEE W J, SHIN Y, LEE J, et al. Real-time ray tracing on future mobile computing platform[C]//Proceedings of the SIGGRAPH Asia 2013 Symposium on Mobile Graphics and Interactive Applications, Hong Kong, China, Nov 19-22, 2013. New York: ACM, 2013: 1-5. [99] NAH J H, KIM J W, PARK J, et al. HART: a hybrid architecture for ray tracing animated scenes[J]. IEEE Transactions on Visualization and Computer Graphics, 2014, 21(3): 389-401. [100] KIM H Y, KIM Y J, KIM L S. MRTP: mobile ray tracing processor with reconfigurable stream multi-processors for high datapath utilization[J]. IEEE Journal of Solid-State Circuits, 2011, 47(2): 518-535. [101] KIM H Y, KIM Y J, OH J H, et al. A reconfigurable SIMT processor for mobile ray tracing with contention reduction in shared memory[J]. IEEE Transactions on Circuits and Systems I: Regular Papers, 2012, 60(4): 938-950. [102] YAN R, HUANG L, GUO H, et al. RT engine: an efficient hardware architecture for ray tracing[J]. Applied Sciences, 2022, 12(19): 9599. [103] SPJUT J, KENSLER A, KOPTA D, et al. TRaX: a multicore hardware architecture for real-time ray tracing[J]. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2009, 28(12): 1802-1815. [104] KOPTA D, SPJUT J, BRUNVAND E, et al. Efficient MIMD architectures for high-performance ray tracing[C]//Proceedings of the 2010 IEEE International Conference on Computer Design, Amsterdam, Oct 3-6, 2010. Piscataway: IEEE, 2010: 9-16. [105] KOPTA D, SHKURKO K, SPJUT J, et al. Memory considerations for low energy ray tracing[J]. Computer Graphics Forum, 2015, 34(1): 47-59. [106] KOPTA D, SHKURKO K, SPJUT J, et al. An energy and bandwidth efficient ray tracing architecture[C]//Proceedings of the High Performance Graphics 2013, Anaheim, Jul 19-21, 2013. New York: ACM, 2013. [107] SHKURKO K, GRANT T, KOPTA D, et al. Dual streaming for hardware-accelerated ray tracing[C]//Proceedings of the High Performance Graphics 2017. New York: ACM, 2017: 1-11. [108] VASIOU E, SHKURKO K, BRUNVAND E, et al. Mach-RT: a many chip architecture for ray tracing[C]//Proceedings of the High Performance Graphics 2019, Strasbourg, Jul 16-18, 2019. New York: ACM, 2019: 1-6. [109] VASIOU E, SHKURKO K, BRUNVAND E, et al. Mach-RT: a many chip architecture for high performance ray tracing[J]. IEEE Transactions on Visualization and Computer Graphics, 2022, 28(3): 1585-1596. |
[1] | XIAO Han, SUN Lupeng, LI Cailin, ZHOU Qinglei. GPU-Oriented Parallel Algorithm for Histogram Statistical Image Enhancement [J]. Journal of Frontiers of Computer Science and Technology, 2022, 16(10): 2273-2285. |
[2] | LI Jingjun, ZHANG Chen, CAO Qiang. Analyzing Performance of Neural Networks in Training Phase [J]. Journal of Frontiers of Computer Science and Technology, 2018, 12(10): 1645-1657. |
[3] | SONG Yingli, NIU Baoning, SONG Chunhua. Multilevel of Details Texture Rendering on Cubic Panorama [J]. Journal of Frontiers of Computer Science and Technology, 2017, 11(9): 1496-1504. |
[4] | ZHANG Dongpei, XIE Ning, LIU Xiaojun, JIA Jinyuan. Lightweight Real-Time Rendering System for Online Large Scale Underground Space [J]. Journal of Frontiers of Computer Science and Technology, 2015, 9(9): 1034-1043. |
Viewed | ||||||
Full text |
|
|||||
Abstract |
|
|||||
/D:/magtech/JO/Jwk3_kxyts/WEB-INF/classes/