The level 2 is a heuristic meant to help with certain kinds of
programming idioms. It isn't always going to work. In this case
trace(cmpfun) will show three functions being compiled each time
through. Not sure why -- I'll try to find out and see if it can be
avoided.
luke
On Thu, 12 Apr 2012, Tal Galili wrote:
Hello,
Due to exploration of the JIT capabilities offered through the {compiler}
package, I came by the fact that using enableJIT(2) can *slow* the rpart
function (from the {rpart} package) by a magnitude of about 10 times.
Here is an example code to run:
library(rpart)
require(compiler)
enableJIT(0) # just making sure that JIT is off # We could also use
enableJIT(1) and it would be fine
fo <- function() {rpart(Kyphosis ~ Age + Number + Start, data=kyphosis)}
system.time(fo())
# user system elapsed
# 0 0 0 # this can also be 0.01 sometimes.
enableJIT(2) # also happens for enableJIT(3)
system.time(fo())
# user system elapsed
# 0.12 0.00 0.12
Which brings me to my *questions*:
1) Is this a bug or a feature?
2) If this is a feature, what is causing it? (or put another way, can one
predict ahead of time the implications of using enableJIT(2) or
enableJIT(3) on his code?)
*Links*:
A post I recently wrote about my exploration of JIT -
www.r-statistics.com/2012/04/speed-up-your-r-code-using-a-just-in-time-jit-compiler/
The question asked on SO regarding the limitations of JIT:
http://stackoverflow.com/questions/10106736/possible-shortcomings-for-using-jit-with-r
Thanks,
Tal
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