Parsing in Parallel on Multiple Cores and GPUs
Centre for Language Sciences and Department of Computing, Macquarie University, Sydney, Australia
Proceedings of Australasian Language Technology Association Workshop, pages 29-37, 2011
This paper examines the ways in which parallelism can be used to speed the parsing of dense PCFGs. We focus on two kinds of parallelism here: Symmetric Multi-Processing (SMP) parallelism on shared-memory multicore CPUs, and Single-Instruction MultipleThread (SIMT) parallelism on GPUs. We describe how to achieve speed-ups over an already very efficient baseline parser using both kinds of technology. For our dense PCFG parsing task we obtained a 60x speed-up using SMP and SSE parallelism coupled with a cache-sensitive algorithm design, parsing section 24 of the Penn WSJ treebank in a little over 2 secs.
December 20, 2011 by hgpu
