Fast minimum spanning tree for large graphs on the gpu

Graphics Processor Units are used for many general purpose pro-cessing due to high compute power available on them. Regular, data-parallel algorithms map well to the SIMD architecture of cur-rent GPU. Irregular algorithms on discrete structures like graphs are harder to map to them. Efficient data-mapping primitives can play crucial role in mapping such algorithms onto the GPU. In this paper, we present a minimum spanning tree algorithm on Nvidia GPUs under CUDA, as a recursive formulation of Borůvka’s approach for undirected graphs. We implement it using scalable primitives such as scan, segmented scan and split. The irregular steps of superver-tex formation and recursive graph construction are mapped to prim-itives like split to categories involving vertex ids and edge weights. We obtain 30 to 50 times speedup over the CPU implementation on most graphs and 3 to 10 times speedup over our previous GPU implementation. We construct the minimum spanning tree on a 5 million node and 30 million edge graph in under 1 second on one quarter of the Tesla S1070 GPU.