Accelerating finding euler circuit on CPU-GPGPU heterogeneous architecture

GPU (Graphic Processing Unit) provides a large computational performance at a very low price. Algorithms with regular data access map well to the SIMD architecture of current GPU, while irregular algorithms on discrete data structures like graphs are hard to map. In this paper, we transform the prior algorithm, design special data structures, and present an optimized CPU-GPU implementation for finding Euler circuit on a randomly generated Eulerian graph. It can deal with a graph of 4096 vertices and 1.7 million edges in about 1 second, which has a speed up of about 50 times over the best sequential CPU implementation.