1. By Mahmoud Moustafa Zidan Basic Sciences Department Faculty of Computer and Information Sciences Ain Shams University Under Supervision of Prof. Dr. Taymoor Nazmy Computer Science Department Faculty of Computer and Information Sciences Ain Shams University Prof. Dr. Mohamed Hashem Information Systems Department Faculty of Computer and Information Sciences Ain Shams University Dr. Haytham El-Messiry Computer Science Department Faculty of Computer and Information Sciences Ain Shams University

2.  Introduction to RT, GI, GPU  Previous Work (GI, Hierarchy Construction)  Proposed Approach for Hierarchal Tree Construction  Proposed Algorithm for Building Binned SAH BVH  Proposed Approach for Parallel Ray Tracing and Photon Mapping  Results  Conclusion

5.  Offline VS Interactive (Real-time) Rendering  Rasterization  Physically Based Rendering  Reyes Rendering  Precomputed Radiance Transfer  Parallel Hieratical Tree Construction  KD-Tree [Zhou et al. 2008]  SAH BVH, LBVH [Lauterbach et al. 2009]  Interactive (Real-time) GPU RT, GPU PM  Real-time RT [Zhou et al. 2008]  Interactive PM [Wang et al. 2009]

6.  Data parallel utilities  Data Parallel Primitive Algorithms (main building blocks for parallel algorithms)  Data parallel operator  Data parallel code fragment  Parallel extensions to math/logic operators on GPU A simple reformulation of previous parallel algorithms on GPU

7.  Pervious work  GPU SAH BVH [Lauterbach et al. 2009] (high quality tree, slow construction)  GPU LBVH [Lauterbach et al. 2009] (moderate (low) quality tree, fast construction)  HLBVH

8.  Evaluates SAH as (small) (variable) number of candidates (e.g. 32-4) is enough for good tree [instead of (large) (fixed) candidates in SAH BVH]  Divide triangles into fixed size chunks for better work load  Evaluates SAH at chunks and used parallel scans to share intermediate values of SAH (work efficiency)  Also use LBVH to build higher tree levels for faster algorithms

9.  Entire mapping of all rendering stages on GPU  A simple reformulation of previous approaches for both ray tracing and photon mapping  Evaluate proposed hierarchy for binned SAH BVH

11.  Ray tracing evaluation

12.  Witted ray tracing

13.  Photon mapping

15.  New approach for GPU parallel code which simplifies previous proposed algorithms  Proposed fast algorithm for building BVH

16.  New parallel template library (e.g. thrust)  Use the LBVH appraoch for fast point-based KD-tree  Enhance ray tracer for distributed effects  Enhance photon mapping for area light