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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 Intelr Many Integrated Core (MIC) Architecture. In order to e?ciently 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 Intelr Xeonr processors and Intelr Xeonr PhiTM coprocessors. The comparison results with existing photon mapping techniques indicate that our method gives significant improvement in speed with the same accuracy.