Large-Scale Bioinformatics Data Mining with Parallel Genetic Programming on Graphics Processing Units

The NCBI GEO GSE3494 breast cancer dataset contains hundreds of Affymetrix HG-U133A and HG-U133B GeneChip biopsies each with a million variables. Multiple genetic programming (GP) runs on a graphics processing unit (GPU) hardware, each with a population of five million programs both winnows (selects) useful variables from the chaff and evolves small (three inputs) data models. The SPMD CUDA interpreter exploits the GPU’s single instruction multiple data (SIMD) mode of parallel computing, even though the GP populations contain different programs. A 448 node nVidia Fermi C2050 Tesla graphics card delivers 8.5 giga GPops per second. In addition to describing our implementation, we survey current GPGPU work in bioinformatics and genetic programming.

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