Programs of Connected Component Labeling (CCL) on CPU / GPU Objective: To solve the problem of the CUDA programming contest (TopCoder/NVIDIA CUDA Superhero Challenge 1; http://community.topcoder.com/longcontest/?module=ViewProblemStatement&rd=13957&pm=10644). To compile source files: $ make Create below files: ccl_np_cpu # Neighbour Propagation on CPU ccl_np_gpu # Neighbour Propagation on CPU ccl_dpl_cpu # Directional Propagation Labelling on CPU ccl_dpl_gpu # Directional Propagation Labelling on GPU ccl_le_cpu # Label Equivalence on CPU ccl_le_gpu # Label Equivalence on GPU To create input data from image files: Usage: image2input.py input_image output_text [degree_of_connectivity=4 threashold=0] Example) $ ./image2input.py image.jpg input.dat 8 10 $ ./ccl_le_cpu input.dat > result.txt References: 1. K. Hawick, A. Leist and D. Playne, Parallel graph component labelling with GPUs and CUDA, Parallel Computing 36 (12) 655-678 (2010) 2. O. Kalentev, A. Rai, S. Kemnitz and R. Schneider, Connected component labeling on a 2D grid using CUDA, J. Parallel Distrib. Comput. 71 (4) 615-620 (2011) 3. V. M. A. Oliveira and R. A. Lotufo, A study on connected components labeling algorithms using GPUs, SIBGRAPI (2010)