View difference between Paste ID: X4jnRn4A and AHEwSTZ5

 library(kernlab)
 N = 10000
 p = 5
 b = 1000
 X = matrix(rnorm(N*p), ncol = p)
 center = X[sample(1:N, b),]
 sigma = 1
 kernel_X <- kernelMatrix(rbfdot(sigma=1/(2*sigma^2)), X, center)
 
 library(Rcpp)
 library(RcppArmadillo)
 library(inline)
 settings <- getPlugin("Rcpp")
 settings$env$PKG_CXXFLAGS <- paste('-fopenmp', settings$env$PKG_CXXFLAGS)
 settings$env$PKG_LIBS <- paste('-fopenmp -lgomp', settings$env$PKG_LIBS)
 do.call(Sys.setenv, settings$env)
 sourceCpp(code = '
 // [[Rcpp::depends(RcppArmadillo)]]
 #include <RcppArmadillo.h>
 #include <omp.h>
 using namespace Rcpp;
 using namespace arma;
 // [[Rcpp::export]]
 
 NumericMatrix kernelMatrix_cpp(NumericMatrix Xr, NumericMatrix Centerr, double sigma) {
 	omp_set_num_threads(omp_get_max_threads());
 	uword n = Xr.nrow(), b = Centerr.nrow(), row_index, col_index;
 	mat X(Xr.begin(), n, Xr.ncol(), false);
 	mat Center(Centerr.begin(), b, Centerr.ncol(), false);
 	mat KerX(n, b);
 	#pragma omp parallel private(row_index, col_index)
 	for (row_index = 0; row_index < n; row_index++)
 	{
 		#pragma omp for nowait
 		for (col_index = 0; col_index < b; col_index++)
 		{
 			KerX(row_index, col_index) = exp(sum(square(X.row(row_index) - Center.row(col_index))) / (-2.0 * sigma * sigma));
 		}
 	}
     return wrap(KerX);
 }')
 kernel_X_cpp = kernelMatrix_cpp(X, center, sigma)
 all.equal([email protected], kernel_X_cpp)
 sum(abs([email protected] - kernel_X_cpp) < 1e-12)
 
 library(rbenchmark)
 benchmark(kernelMatrix_cpp(X, center, sigma), kernelMatrix(rbfdot(sigma=1/(2*sigma^2)), X, center), columns=c("test", "replications","elapsed", "relative"), replications=50, order="relative")