Better speedups using simpler parallel programming for graph connectivity and biconnectivity

Speedups demonstrated for finding the biconnected components of a graph: 9x to 33x on the Explicit Multi-Threading (XMT) many-core computing platform relative to the best serial algorithm using a relatively modest silicon budget. Further evidence suggests that speedups of 21x to 48x are possible. For graph connectivity, we demonstrate that XMT outperforms two recent NVIDIA GPUs of similar or greater silicon area. Previous studies of parallel biconnectivity algorithms achieved at most a 4x speedup, but we could not find biconnectivity code for GPUs to compare biconnectivity against them. Ease-of-programming: The paper suggests that parallel programming for the XMT platform is considerably simpler than for the SMP and GPU ones. Unlike the quantitative speedup results, the ease-of-programming comparison is more qualitative. Productivity of parallel programming is a central interest of PMAM/PPoPP strongly favoring ease-ofprogramming. We believe that the discussion is on par with the sta...

• Type: Journal
• Year: 2012
• Where: PPOPP
• Authors: James A. Edwards, Uzi Vishkin
• Keywords: Distributed And Parallel Computing, Graph Connectivity, PPOPP 2012, Pram Algorithm, Serial Algorithm