Matrix multiplication performance, varying in different settings R

I have access to two clusters where R is installed. I've been programming and testing my stuff all this time. When I moved my code to a new cluster, suddenly all matrix multiplications became very slow. Here are a few numbers:

Cluster-1:
> a <- matrix(0, nrow=2000, ncol=2000)
> b <- matrix(0, nrow=2000, ncol=2000)
> system.time(c <- a %*% b)
   user  system elapsed 
   0.07    0.03    0.10

Cluster-2:
> a <- matrix(0, nrow=2000, ncol=2000)
> b <- matrix(0, nrow=2000, ncol=2000)
> system.time(c <- a%*% b)
   user  system elapsed 
 13.682   0.014  13.695

Please note that I do not use sparse matrices.

Cluster-1 uses R version 2.12.1, and Cluster-2 uses R version 2.15.0. Is there any special library that lacks a second cluster? How to find which one? Thank.

EDIT: Adding more details about clusters:

Cluster 1:

> sessionInfo()
R version 2.12.1 (2010-12-16)
Platform: x86_64-pc-linux-gnu (64-bit)

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8
 [5] LC_MONETARY=C              LC_MESSAGES=en_US.UTF-8
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C
 [9] LC_ADDRESS=C               LC_TELEPHONE=C
 [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base

Cluster 2:

> sessionInfo()
R version 2.15.0 (2012-03-30)
Platform: x86_64-unknown-linux-gnu (64-bit)

locale:
 [1] LC_CTYPE=en_US.iso885915       LC_NUMERIC=C                  
 [3] LC_TIME=en_US.iso885915        LC_COLLATE=en_US.iso885915    
 [5] LC_MONETARY=en_US.iso885915    LC_MESSAGES=en_US.iso885915   
 [7] LC_PAPER=C                     LC_NAME=C                     
 [9] LC_ADDRESS=C                   LC_TELEPHONE=C                
[11] LC_MEASUREMENT=en_US.iso885915 LC_IDENTIFICATION=C           

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base