Performance Comparison of Bounding Volume Hierarchies and Kd-Trees for GPU Ray Tracing

We present a performance comparison of bounding volume hierarchies and kd‐trees for ray tracing on many‐core architectures (GPUs). The comparison is focused on rendering times and traversal characteristics on the GPU using data structures that were optimized for very high performance of tracing rays...

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Published in:	Computer graphics forum Vol. 35; no. 8; pp. 68 - 79
Main Authors:	Vinkler, Marek, Havran, Vlastimil, Bittner, Jiří
Format:	Journal Article
Language:	English
Published:	Oxford Blackwell Publishing Ltd 01.12.2016
Subjects:	Analysis Architecture Central processing units Computer architecture CPUs Criteria Data structures GPU Hierarchies I.3.1 [Computer Graphics]: Hardware architecture-Parallel processing I.3.6 [Computer Graphics]: Methodology and Techniques-Graphics data structures and data types I.3.7 [Computational Graphics]: Three-Dimensional Graphics and Realism-Raytracing I.3.7 [Computational Graphics]: Three‐Dimensional Graphics and Realism—Raytracing; I.3.6 [Computer Graphics]: Methodology and Techniques—Graphics data structures and data types; I.3.1 [Computer Graphics]: Hardware architecture—Parallel processing Image processing systems object-partitioning Parallel processing Performance assessment performance comparison Profiling Ray tracing Rendering space-partitioning Studies
ISSN:	0167-7055, 1467-8659
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Abstract	We present a performance comparison of bounding volume hierarchies and kd‐trees for ray tracing on many‐core architectures (GPUs). The comparison is focused on rendering times and traversal characteristics on the GPU using data structures that were optimized for very high performance of tracing rays. To achieve low rendering times, we extensively examine the constants used in termination criteria for the two data structures. We show that for a contemporary GPU architecture (NVIDIA Kepler) bounding volume hierarchies have higher ray tracing performance than kd‐trees for simple and moderately complex scenes. On the other hand, kd‐trees have higher performance for complex scenes, in particular for those with high depth complexity. Finally, we analyse the causes of the performance discrepancies using the profiling characteristics of the ray tracing kernels. We present a performance comparison of bounding volume hierarchies and kd‐trees for ray tracing on many‐core architectures (GPUs). The comparison is focused on rendering times and traversal characteristics on the GPU using data structures that were optimized for very high performance of tracing rays. To achieve low rendering times, we extensively examine the constants used in termination criteria for the two data structures. We show that for a contemporary GPU architecture (NVIDIA Kepler) bounding volume hierarchies have higher ray tracing performance than kd‐trees for simple and moderately complex scenes.
AbstractList	We present a performance comparison of bounding volume hierarchies and kd-trees for ray tracing on many-core architectures (GPUs). The comparison is focused on rendering times and traversal characteristics on the GPU using data structures that were optimized for very high performance of tracing rays. To achieve low rendering times, we extensively examine the constants used in termination criteria for the two data structures. We show that for a contemporary GPU architecture (NVIDIA Kepler) bounding volume hierarchies have higher ray tracing performance than kd-trees for simple and moderately complex scenes. On the other hand, kd-trees have higher performance for complex scenes, in particular for those with high depth complexity. Finally, we analyse the causes of the performance discrepancies using the profiling characteristics of the ray tracing kernels. We present a performance comparison of bounding volume hierarchies and kd-trees for ray tracing on many-core architectures (GPUs). The comparison is focused on rendering times and traversal characteristics on the GPU using data structures that were optimized for very high performance of tracing rays. To achieve low rendering times, we extensively examine the constants used in termination criteria for the two data structures. We show that for a contemporary GPU architecture (NVIDIA Kepler) bounding volume hierarchies have higher ray tracing performance than kd-trees for simple and moderately complex scenes. We present a performance comparison of bounding volume hierarchies and kd-trees for ray tracing on many-core architectures (GPUs). The comparison is focused on rendering times and traversal characteristics on the GPU using data structures that were optimized for very high performance of tracing rays. To achieve low rendering times, we extensively examine the constants used in termination criteria for the two data structures. We show that for a contemporary GPU architecture (NVIDIA Kepler) bounding volume hierarchies have higher ray tracing performance than kd-trees for simple and moderately complex scenes. On the other hand, kd-trees have higher performance for complex scenes, in particular for those with high depth complexity. Finally, we analyse the causes of the performance discrepancies using the profiling characteristics of the ray tracing kernels. We present a performance comparison of bounding volume hierarchies and kd‐trees for ray tracing on many‐core architectures (GPUs). The comparison is focused on rendering times and traversal characteristics on the GPU using data structures that were optimized for very high performance of tracing rays. To achieve low rendering times, we extensively examine the constants used in termination criteria for the two data structures. We show that for a contemporary GPU architecture (NVIDIA Kepler) bounding volume hierarchies have higher ray tracing performance than kd‐trees for simple and moderately complex scenes. On the other hand, kd‐trees have higher performance for complex scenes, in particular for those with high depth complexity. Finally, we analyse the causes of the performance discrepancies using the profiling characteristics of the ray tracing kernels. We present a performance comparison of bounding volume hierarchies and kd‐trees for ray tracing on many‐core architectures (GPUs). The comparison is focused on rendering times and traversal characteristics on the GPU using data structures that were optimized for very high performance of tracing rays. To achieve low rendering times, we extensively examine the constants used in termination criteria for the two data structures. We show that for a contemporary GPU architecture (NVIDIA Kepler) bounding volume hierarchies have higher ray tracing performance than kd‐trees for simple and moderately complex scenes.
Author	Bittner, Jiří Havran, Vlastimil Vinkler, Marek
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References	[VBHH13] Vinkler M., Bittner J., Havran V., Hapala M.: Massively parallel hierarchical scene processing with applications in rendering. Computer Graphics Forum 32, 8 (2013), 13-25. [WHG84] Weghorst H., Hooper G., Greenberg D. P.: Improved computational methods for ray tracing. ACM Transactions on Graphics 3, 1 (1984), 52-69. [HZDS09] Havran V., Zajac J., Drahokoupil J., Seidel H.-P.: MPII Building Model as Data for Your Research. Res. rep. MPI-I-2009-4-004, MPI Informatik, Dec. 2009. [ML03] Masso J. P. M., Lopez P. G.: Automatic hybrid hierarchy creation: A cost-model based approach. Computer Graphics Forum 22, 1 (2003), 5-13. [BHH13] Bittner J., Hapala M., Havran V.: Fast insertion-based optimization of bounding volume hierarchies. Computer Graphics Forum 32, 1 (2013), 85-100. [WMG*09] Wald I., Mark W. R., Günther J., Boulos S., Ize T., Hunt W., Parker S. G., Shirley P.: State of the art in ray tracing animated scenes. Computer Graphics Forum 28, 6 (2009), 1691-1722. [GS87] Goldsmith J., Salmon J.: Automatic creation of object hierarchies for ray tracing. IEEE Computer Graphics and Applications 7, 5 (1987), 14-20. [Hai87] Haines E. A.: A proposal for standard graphics environments. IEEE Computer Graphics and Applications 7, 11 (1987), 3-5. [HB02] Havran V., Bittner J.: On improving KD-trees for ray shooting. Journal of WSCG 10, 1 (2002), 209-216. [ASK14] Áfra A. T., Szirmay-Kalos L.: Stackless multi-BVH traversal for CPU, MIC and GPU ray tracing. Computer Graphics Forum 33, 1 (2014), 129-140. [DPS10] Danilewski P., Popov S., Slusallek P.: Binned SAH Kd-Tree Construction on a GPU. Tech. Rep., Computer Graphics Group, Saarland University, June 2010. [HH11] Hapala M., Havran V.: Review: Kd-tree traversal algorithms for ray tracing. Computer Graphics Forum 30, 1 (2011), 199-213. 2012 2013; 32 2000 1984; 3 2011 2010 2002; 10 1987; 7 2009 2011; 30 2007 1985 2006 2005 2004 2014 2003 2013 2002 2014; 33 2003; 22 2009; 28 e_1_2_9_30_1 Kaplan M. (e_1_2_9_23_1) 1985 e_1_2_9_11_1 e_1_2_9_34_1 e_1_2_9_10_1 e_1_2_9_35_1 Havran V. (e_1_2_9_16_1) 2002; 10 e_1_2_9_32_1 e_1_2_9_12_1 Havran V. (e_1_2_9_21_1) 2009 Vinkler M. (e_1_2_9_33_1) 2014 Szécsi L. (e_1_2_9_31_1) 2003 e_1_2_9_15_1 e_1_2_9_38_1 e_1_2_9_14_1 e_1_2_9_39_1 e_1_2_9_17_1 e_1_2_9_36_1 e_1_2_9_37_1 e_1_2_9_19_1 e_1_2_9_18_1 Guthe M. (e_1_2_9_13_1) 2014 e_1_2_9_41_1 e_1_2_9_20_1 e_1_2_9_40_1 e_1_2_9_22_1 e_1_2_9_24_1 e_1_2_9_7_1 e_1_2_9_6_1 Akenine‐Möller T. (e_1_2_9_4_1) 2005 e_1_2_9_5_1 e_1_2_9_3_1 e_1_2_9_2_1 Roccia J.‐P. (e_1_2_9_29_1) 2012 Danilewski P. (e_1_2_9_8_1) 2010 e_1_2_9_9_1 e_1_2_9_26_1 e_1_2_9_25_1 e_1_2_9_28_1 e_1_2_9_27_1
References_xml	– reference: [HB02] Havran V., Bittner J.: On improving KD-trees for ray shooting. Journal of WSCG 10, 1 (2002), 209-216. – reference: [Hai87] Haines E. A.: A proposal for standard graphics environments. IEEE Computer Graphics and Applications 7, 11 (1987), 3-5. – reference: [WMG*09] Wald I., Mark W. R., Günther J., Boulos S., Ize T., Hunt W., Parker S. G., Shirley P.: State of the art in ray tracing animated scenes. Computer Graphics Forum 28, 6 (2009), 1691-1722. – reference: [GS87] Goldsmith J., Salmon J.: Automatic creation of object hierarchies for ray tracing. IEEE Computer Graphics and Applications 7, 5 (1987), 14-20. – reference: [HH11] Hapala M., Havran V.: Review: Kd-tree traversal algorithms for ray tracing. Computer Graphics Forum 30, 1 (2011), 199-213. – reference: [ML03] Masso J. P. M., Lopez P. G.: Automatic hybrid hierarchy creation: A cost-model based approach. Computer Graphics Forum 22, 1 (2003), 5-13. – reference: [DPS10] Danilewski P., Popov S., Slusallek P.: Binned SAH Kd-Tree Construction on a GPU. Tech. Rep., Computer Graphics Group, Saarland University, June 2010. – reference: [WHG84] Weghorst H., Hooper G., Greenberg D. P.: Improved computational methods for ray tracing. ACM Transactions on Graphics 3, 1 (1984), 52-69. – reference: [ASK14] Áfra A. T., Szirmay-Kalos L.: Stackless multi-BVH traversal for CPU, MIC and GPU ray tracing. Computer Graphics Forum 33, 1 (2014), 129-140. – reference: [BHH13] Bittner J., Hapala M., Havran V.: Fast insertion-based optimization of bounding volume hierarchies. Computer Graphics Forum 32, 1 (2013), 85-100. – reference: [HZDS09] Havran V., Zajac J., Drahokoupil J., Seidel H.-P.: MPII Building Model as Data for Your Research. Res. rep. 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Snippet	We present a performance comparison of bounding volume hierarchies and kd‐trees for ray tracing on many‐core architectures (GPUs). The comparison is focused on... We present a performance comparison of bounding volume hierarchies and kd-trees for ray tracing on many-core architectures (GPUs). The comparison is focused on...
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SubjectTerms	Analysis Architecture Central processing units Computer architecture CPUs Criteria Data structures GPU Hierarchies I.3.1 [Computer Graphics]: Hardware architecture-Parallel processing I.3.6 [Computer Graphics]: Methodology and Techniques-Graphics data structures and data types I.3.7 [Computational Graphics]: Three-Dimensional Graphics and Realism-Raytracing I.3.7 [Computational Graphics]: Three‐Dimensional Graphics and Realism—Raytracing; I.3.6 [Computer Graphics]: Methodology and Techniques—Graphics data structures and data types; I.3.1 [Computer Graphics]: Hardware architecture—Parallel processing Image processing systems object-partitioning Parallel processing Performance assessment performance comparison Profiling Ray tracing Rendering space-partitioning Studies
Title	Performance Comparison of Bounding Volume Hierarchies and Kd-Trees for GPU Ray Tracing
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