Photon mapping is a global illumination algorithm which is composed of two steps： photon tracing and photon searching. During photon searching step, each shading point needs to search the photon-tree to find k-neighb...Photon mapping is a global illumination algorithm which is composed of two steps： photon tracing and photon searching. During photon searching step, each shading point needs to search the photon-tree to find k-neighbouring photons for reflected radiance estimation. As the number of shading points and the size of photon-tree are dramatically large, the photon searching step is time consuming. We propose a parallel photon searching algorithm by using radiance estimation approach for coherent shading points on the Intel Many Integrated Core （MIC） Architecture. In order to efficiently use single instruction multiple data （SIMD） units, shading points are clustered by similarity first （every cluster contains 16 shading-points）, and an initial neighbouring scope is searched from the photon-tree for each cluster. Then we use 16-wide SIMD units by performing k-NN searching from the initial neighbouring scope for those 16 shading-points in a cluster in parallel. We use the method to simulate some global illumination scenes on Intel Xeon processors and Intel Xeon Phi^TM coprocessors. The comparison results with existing photon mapping techniques indicate that our method gives significant improvement in speed with the same accuracy.展开更多
基金This work was partly supported by the National Natural Science Foundation of China under Grant Nos. 61472224, 61472225,the National High Technology Research and Development 863 Program of China under Grant No. 2012AA01A306, the National Key Technology Research and Development Prograxn of China under Grant No. 2013BAH39F02, the Special Funding of Independent Innovation and Transformation of Achievements in Shandong Province of China under Grant No. 2014ZZCX08201, and the Special Funds of Taishan Scholar Construction Project of China.
文摘Photon mapping is a global illumination algorithm which is composed of two steps： photon tracing and photon searching. During photon searching step, each shading point needs to search the photon-tree to find k-neighbouring photons for reflected radiance estimation. As the number of shading points and the size of photon-tree are dramatically large, the photon searching step is time consuming. We propose a parallel photon searching algorithm by using radiance estimation approach for coherent shading points on the Intel Many Integrated Core （MIC） Architecture. In order to efficiently use single instruction multiple data （SIMD） units, shading points are clustered by similarity first （every cluster contains 16 shading-points）, and an initial neighbouring scope is searched from the photon-tree for each cluster. Then we use 16-wide SIMD units by performing k-NN searching from the initial neighbouring scope for those 16 shading-points in a cluster in parallel. We use the method to simulate some global illumination scenes on Intel Xeon processors and Intel Xeon Phi^TM coprocessors. The comparison results with existing photon mapping techniques indicate that our method gives significant improvement in speed with the same accuracy.
