CUDA-MEME is a motif discovery software based on MEME (version 3.5.4) algorithm for a single GPU device using CUDA programming model. mCUDA-MEME is an ultrafast scalable motif discovery algorithm based on MEME (version 4.4.0) algorithm for mutliple GPUs using a hybrid combination of CUDA, MPI and OpenMP parallel programming models. This algorithm is a further extension of CUDA-MEME with respect to accuracy and speed and has been tested on a GPU cluster with eight compute nodes and two Fermi-based Tesla S2050 (and Tesla-based Tesla S1070) quad-GPU computing systems, running the Linux OS with the MPICH2 library. The experimental results showed that our algorithm scales well with respect to both dataset sizes and the number of GPUs. At present, OOPS and ZOOPS models are supported, which are sufficient for most motif discovery applications. The source code is available for download.
Refer to the usage in the MCUDA-MEME page.
If you have any suggestion or question, please contact Liu Yongchao (Email: yliu860 (at) gatech (dot) edu).