Shared Memory and Distributed Memory Parallel Ray Tracer Dmitriy Bespalov

Overview What is Ray Tracer Implemented Features of Ray Tracer Parallel Implementation Experimental Results Conclusions

What is Ray Tracer Ray Tracer – generate realistic images

Trivial Ray Tracer

Hierarchical Modeling

Phong’s shading model and supersampling

Acceleration Technique Prune rays earlier Use axis-aligned bounding boxes Divide bounding boxes into buckets

Shadows and Reflection Phong’s shading model and supersampling

Parallel Implementation Shared Memory Create job list Threads remove jobs from the list Distributed Memory Send scene to every work node Work nodes request jobs from supervisor

Experimental Results Render same scene using both ray tracers 4 reflective spheres 3 meshes (~20000 faces)

Running Times Shared Memory Distributed Memory 1 thread: 682.3 seconds 2 threads: 349.6 seconds Distributed Memory 1 thread on ws79: 792.3 seconds

Running Times

Speed-Up

Efficiency

Conclusions Good parallel performance Shared Memory Almost twice as fast with 2 threads Distributed Memory: Linear speed-up Constant efficiency Run time is independent of the job size

Thank You! Questions?