Profiling SVM (e1071) in R

I am new to R and SVM and I am trying to profile a function svmfrom a package e1071. However, I cannot find any large dataset that allows me to get a good profiling range that resizes the input data. Does anyone know how to work svm? Which dataset should I use? Any specific options svmthat make it work harder?

I am copying some of the commands that I use to test performance. Perhaps the most useful and easier way to get what I'm trying here is:

#loading libraries
library(class)
library(e1071)
#I've been using golubEsets (more examples availables)
library(golubEsets)

#get the data: matrix 7129x38
data(Golub_Train)
n <- exprs(Golub_Train)

#duplicate rows(to make the dataset larger)
n<-rbind(n,n)

#take training samples as a vector
samplelabels <- as.vector(Golub_Train@phenoData@data$ALL.AML)

#calculate svm and profile it
Rprof('svm.out')
svmmodel1 <- svm(x=t(n), y=samplelabels, type='C', kernel="radial", cross=10)
Rprof(NULL)

I keep increasing the data set duplicating rows and columns, but I have reached the memory limit instead of making svmit harder ...