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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Yanjun Jiang Hualong Wen Zhanchun Gao |
| Copyright Year | 2012 |
| 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. |
| Starting Page | 26 |
| Ending Page | 29 |
| File Size | 156019 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781467328586 |
| ISSN | 21655006 |
| e-ISBN | 9781467328586 |
| DOI | 10.1109/ICNDC.2012.14 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-10-21 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | CUDA Instruction sets Graphics processing units Estimation Mahout Parallel processing LDA Vectors Acceleration Kernel GPU |
| Content Type | Text |
| Resource Type | Article |
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