Implementation of algorithms with a fine-grained parallelism on GPUs

The efficiency of implementations of algorithms with a fine-grained parallelism on GPUs that support the CUDA architecture is studied. For testing, cellular automata and differential schemes are used. We offer several versions of implementations and analyze their productivity. An example of the GPU application for modeling the process of carbon dioxide oxidation on the catalyst surface is given.