A Method of Accelerating LDA Program with GPU

Abstract

LDA (Latent Dirichlet Allocation) is a text modeling algorithm based on a generative probabilistic model. It is widely used to discover latent topics among a set of documents. Mahout has implemented LDA algorithm, however, the execution time of the LDA program is very long when processing a large amount of documents, because the documents are processed in sequence. This paper introduces a method to modify this program with CUDA toolkit provided by NVIDIA, in order that a group of documents could be processed in parallel on GPU. Using this method, the LDA program could be accelerated greatly.