Dear R users,
we are trying to do some parallel computing using library(snow).
In particular we have a cluster with 3 nodes
>cl <- makeCluster(3, type = "MPI")
3 slaves are spawned successfully. 0 failed.
and we want to compute the function op_mat (see below) first with the
master and then with the cluster using system.time for checking the
computational performance.
op_mat = function(mat) {
+ inv = solve(mat)
+ det_inv = det(inversa)
+ tr_inv = sum(diag(inversa))
+ return(list(c(det=det_inv,tr=tr_inv)))
+ }
>nn = 3000
>XX = matrix(rnorm(nn*nn),nn,nn)
# with the master
> system.time(op_matrici(XX))
[1] 42.283 1.883 44.168 0.000 0.000
# with the cluster
> system.time(clusterCall(cl,op_matrici,XX))
[1] 11.523 12.612 71.562 0.000 0.000
You can see that using the master it takes 44.168 seconds for computing
the function on matrix XX while it takes 71.562 seconds (more time!!!)
with the cluster. Can you give us some advice in order to understand why
the cluster is slower than the master?
Thank you very much in advance,
bye
Michela and Marco
Ps: we have a gigabit ethernet between the master and the nodes
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