R code to generate random pairs of rows and do simulation

I have a data matrix in R having 45 rows. Each row represents a value of a individual sample. I need to do to a trial simulation; I want to pair up samples randomly and calculate their differences. I want a large sampling (maybe 10000) from all the possible permutations and combinations. This is how I managed to do it till now:- My data matrix ("data") has 45 rows and 2 columns. I selected 45 rows randomly and subtracted from another randomly generated 45 rows.

n1<-(data[sample(nrow(data),size=45,replace=F),])-(data[sample(nrow(data),size=45,replace=F),])

This gave me a random set of differences of size 45. I made 50 such vectors (n1 to n50) and did rbind, which gave me a big data matrix containing random differences. Of course, many rows between first random set and second random set were same and cancelled out. I removed it with a code as follows:

row_sub = apply(new, 1, function(row) all(row !=0 ))
new.remove.zero<-new[row_sub,]

BUT, is there a cleaner way to do this? A simpler way to generate all possible random pairs of rows, calculate their difference as bind it together as a new matrix? Thanks in advance.