benchmark-addition.R

library(Rcpp)
library(microbenchmark)

vectorized <- function() {
  a <- c(1, 1)
  b <- c(2, 2)
  
  for (i in 1:1000000) {
    x <- a + b
  }
  
  return()
}

devectorized <- function() {
  a <- c(1, 1)
  b <- c(2, 2)
  
  for (i in 1:1000000) {
    for (index in 1:2) {
      x[index] <- a[index] + b[index]
    }
  }
  
  return()
}

cppFunction('
  void rcpp_devectorised() {
    NumericVector a = NumericVector::create(1, 1);
    NumericVector b = NumericVector::create(2, 2);
    NumericVector x(2);
    
    for (int j = 0; j < 1e6; ++j) {
      for (int i = 0; i < 2; ++i) {
        x[i] = a[i] + b[i];
      }
    }
    
  }
')

cppFunction('
  void rcpp_vectorised() {
    NumericVector a = NumericVector::create(1, 1);
    NumericVector b = NumericVector::create(2, 2);
    NumericVector x(2);
    
    for (int j = 0; j < 1e6; ++j) {
      x = a + b;
    }
    
  }
')

system.time(vectorized())
#  user  system elapsed 
# 0.526   0.006   0.532 
system.time(devectorized())
#  user  system elapsed 
# 8.511   0.012   8.520 

microbenchmark(
  rcpp_vectorised(),
  rcpp_devectorised(), 
  unit = "s")
# Unit: seconds
#               expr       min       lq   median       uq     max neval
#   rcpp_vectorised() 0.012043 0.012308 0.012453 0.012580 0.01319   100
# rcpp_devectorised() 0.000837 0.000848 0.000865 0.000887 0.00101   100

Found what the problem is. See http://blog.r-enthusiasts.com/2014/05/24/vectorized-vs-devectorized/