Dynamic parallelism for simple and efficient GPU graph algorithms

Abstract

Dynamic parallelism allows GPU kernels to launch additional kernels at runtime directly from the GPU. In this paper we show that dynamic parallelism enables relatively simple high-performance graph algorithms for GPUs. We present breadth-first search (BFS) and single-source shortest paths (SSSP) algorithms that use dynamic parallelism to adapt to the irregular and data-driven nature of these problems. Our approach results in simple code that closely follows the high-level description of the algorithms but yields performance competitive with the current state of the art.