# Simulatin speed: GNU R vs Julia

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Recently there is a lot of noise about Julia. I have decided to test its speed in simulation tasks on my toy Cont model. I thought I had vectorized my GNU R code pretty well, but Julia is much faster.**R snippets**, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

The model was described in my earlier posts so let us go down to a comparison:

Here is my GNU R code:

library

**(**e1071**)**cont.run

**<-****function****(**burn.in, reps, n, d, l, s**)****{** tr

**<-**rep**(**0, n**)** r

**<-**rep**(**0, reps**)****for**

**(**i

**in**1

**:**reps

**)**

**{**

sig

**<-**rnorm**(**1, 0, d**)** mul

**<-**1**if**

**(**sig

**<**0

**)**

**{**

sig

**<-****–**sig mul

**<-****–**1**}**

r

**[**i**]****<-**mul*****sum**(**sig**>**tr**)****/****(**l*****n**)** tr

**[**runif**(**n**)****<**s**]****<-**abs**(**r**[**i**])****}**

return

**(**kurtosis**(**r**[**burn.in**:**reps**]))****}**

system.time

cont.run**(**replicate**(**10,**(**1000, 10000, 1000, 0.005, 10.0, 0.01

**)))**

It’s execution time is a bit below 10 seconds on my laptop.

An equivalent Julia code is the following:

**using**Distributions

**function**cont_run

**(**burn_in

**,**reps

**,**n

**,**d

**,**l

**,**s

**)**

tr

**=****Array****(**Float64**,**n**)** r

**=****Array****(**Float64**,**reps**)****for**i

**in**1

**:**reps

aris

**=**0 sig

**=**randn**()*******d mul

**=**1**if**sig

**<**0

sig

**=****–**sig mul

**=****–**1**end**

**for**k

**in**1

**:**n

**if**sig

**>**tr

**[**k

**]**

aris

**+=**1**end**

**end**

ari

**=**aris**/****(**l*****n**)** r

**[**i**]****=**mul*****ari**for**j

**in**1

**:**n

**if**rand

**()**

**<**s

tr

**[**j**]****=**ari**end**

**end**

**end**

kurtosis

**(**r**[**burn_in**:**reps**])****end**

n

**=**10t_start

**=**time**()**k

**=****Array****(**Float64**,**n**)****for**i

**in**1

**:**n

k

**[**i**]****=**cont_run**(**1000**,**10000**,**1000**,**0.005**,**10.0**,**0.01**)****end**

**(**time

**()**

**–**t_start

**)**

And on my machine it takes a bit less than 0.7 seconds to run.

So we get over tenfold speedup. This is a significant difference for simulation experiments.

I will have to dig more into Julia in the future.

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