Stackless KD-Tree traversal for high performance GPU ray tracing

被引:113
|
作者
Popov, Stefan [1 ]
Guenther, Johannes
Seidel, Hans-Peter
Slusallek, Philipp
机构
[1] Univ Saarland, D-6600 Saarbrucken, Germany
[2] MPI Informat, Saarbrucken, Germany
关键词
D O I
10.1111/j.1467-8659.2007.01064.x
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Significant advances have been achieved for realtime ray tracing recently, but realtime performance for complex scenes still requires large computational resources not yet available from the CPUs in standard PCs. Incidentally, most of these PCs also contain modern GPUs that do offer much larger raw compute power However limitations in the programming and memory model have so far kept the performance of GPU ray tracers well below that of their CPU counterparts. In this paper we present a novel packet ray traversal implementation that completely eliminates the need for maintaining a stack during kd-tree traversal and that reduces the number of traversal steps per ray. While CPUs benefit moderately from the stackless approach, it improves GPU performance significantly. We achieve a peak performance of over 16 million rays per second,for reasonably complex scenes, including complex shading and secondary rays. Several examples show that with this new technique GPUs can actually outperform equivalent CPU based ray tracers.
引用
收藏
页码:415 / 424
页数:10
相关论文
共 50 条
  • [31] Algorithms and performance evaluation of join processing on KD-tree indexed relations
    Kitsuregawa, Masaru, 1600, Publ by Scripta Technica Inc, New York, NY, United States (25):
  • [32] ALGORITHMS AND PERFORMANCE EVALUATION OF JOIN PROCESSING ON KD-TREE INDEXED RELATIONS
    KITSUREGAWA, M
    TAKAGI, M
    HARADA, L
    SYSTEMS AND COMPUTERS IN JAPAN, 1994, 25 (03) : 78 - 90
  • [33] High performance computing applied to the false nearest neighbors method: Box-assisted and kd-tree approaches
    Águila J.J.
    Marín I.
    Arias E.
    Del Mar Artigao M.
    Miralles J.J.
    Lecture Notes in Electrical Engineering, 2011, 90 LNEE : 323 - 336
  • [34] 一种基于GPU虚拟栈的光线跟踪KD-Tree遍历算法
    魏辉
    龚光红
    李妮
    中国体视学与图像分析, 2015, 20 (03) : 260 - 266
  • [35] Kd-tree Based Shooting and Bouncing Ray Method for Fast Computation of Near Field Scattering
    Gao, P. C.
    Liang, Z. C.
    Gao, W.
    PIERS 2014 GUANGZHOU: PROGRESS IN ELECTROMAGNETICS RESEARCH SYMPOSIUM, 2014, : 1304 - 1308
  • [36] A Novel 3D Ray-tracing Acceleration Technique Based on Kd-tree Algorithm for Radio Propagation Predictionin Complex Indoor Environment
    Mei, Xiaowei
    Zhang, Yong
    Lin, Hai
    PIERS 2014 GUANGZHOU: PROGRESS IN ELECTROMAGNETICS RESEARCH SYMPOSIUM, 2014, : 2164 - 2168
  • [37] Improving High-Performance GPU Graph Traversal with Compression
    Kaczmarski, Krzysztof
    Przymus, Piotr
    Rzazewski, Pawel
    NEW TRENDS IN DATABASE AND INFORMATION SYSTEMS II, 2015, 312 : 201 - 214
  • [38] Method Study of Point Model Fast High Quality Rendering Based on KD-Tree
    Lv Hong-wei
    PROCEEDINGS OF THE 2017 2ND INTERNATIONAL CONFERENCE ON ADVANCES IN MATERIALS, MECHATRONICS AND CIVIL ENGINEERING (ICAMMCE 2017), 2017, 121 : 240 - 243
  • [39] K-Means Algorithm Performance Analysis With Determining The Value Of Starting Centroid With Random And KD-Tree Method
    Sirait, Kamson
    Tulus
    Nababan, Erna Budhiarti
    INTERNATIONAL CONFERENCE ON INFORMATION AND COMMUNICATION TECHNOLOGY (ICONICT), 2017, 930
  • [40] Fast Point-Based KD-Tree Construction Method for Hybrid High Frequency Method in Electromagnetic Scattering
    Huang, Yuan
    Zhao, Zhiqin
    Ql, Conghui
    Nie, Zaiping
    Liu, Qing Huo
    IEEE ACCESS, 2018, 6 : 38348 - 38355