Parallel linear model

The WideLM package was developed to deal specifically with this type  
of problem.  It computes regression coefficients and performs a  
limited amount of ANOVA using a GPU.

Models are currently limited to a small number of main effects and  
interactions.  The design matrix is also limited by the GPU's memory  
size - typically several GB.  Execution time scales nicely with the  
number of models tested, i.e., your 'n' below.

We developed it specifically to look for evidence of epistasis in  
genomic data, but would like to make it more generally accessible.   
Constructive criticism is most welcome.

  - Mark Seligman

 I wonder if someone has experience with efficient ways of implicit  
parallel execution of (repeated) linear models (as in the  
non-parallel example below)? Any suggestions on which way to go?

Patrik Waldmann

pval<-c(1:n)
for (i in 1:n){
mod <- lm(y ~ x[,i])
pval[i] <- summary(mod)$coefficients[2,4]
}