Taking a look at Nvidia's CUDA zone I found some recent additions - besides important ones that I already knew like the Smith-Waterman and the phylogenetic likelihood algoritihms. Here is a list of these new programs and libraries that take advantage of GPUs:
The last reference is just a two-page summary, and the 8th reference is behind a paywall - I couldn't access it myself - but the slides are available here.
- Expectation Maximization algorithm for Gaussian Mixture Models
- Multilevel algorithm for MDS (multidimensional scaling)
- Multiclass classifier based on SVMs (support vector machines)
- GPU computing in the R statistical environment (BLAS lowlevel routines and dist(), hclust(), cor(), and granger.test() functions)
- Smith-Waterman algorithm for sequence database search
- Quicksort library
- Feature finding algorithm for mass spectrometry
- Smith-Waterman algorithm for sequence alignment
- MDR (multifactor dimensionality reduction) algorithm for detecting genetic epistatic interactions (white paper)
The last reference is just a two-page summary, and the 8th reference is behind a paywall - I couldn't access it myself - but the slides are available here.
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