Accelerating Large Graph Algorithms on the GPU Using CUDA

Abstract. Large graphs involving millions of vertices are common in many practical applications and are challenging to process. Practical-time implementations using high-end computers are reported but are accessible only to a few. Graphics Processing Units (GPUs) of today have high computation power and low price. They have a restrictive programming model and are tricky to use. The G80 line of Nvidia GPUs can be treated as a SIMD processor array using the CUDA programming model. We present a few fundamental algorithms – including breadth first search, single source shortest path, and all-pairs shortest path – using CUDA on large graphs. We can compute the single source shortest path on a 10 million

• Type: Conference
• Year: 2007
• Where: HIPC
• Authors: Pawan Harish, P. J. Narayanan
• Keywords: Distributed And Parallel Computing, HIPC 2007, Large Graphs, Shortest Path, Source Shortest Path