[Rcpp-devel] How to increase the coding efficiency

Yes, the main issue for my coding is the allocation of memory.  And I have
fixed one of the biggest memory allocation issue: 4000 by 4000 diagonal
matrix. And since I am not familiar with Rcpp and RcppArmadillo, I have no
idea how to reuse the memory. I hope I can have some materials to learn
this. Thanks.

What exactly do these timings show?  A single call you your function?
How many calls?

Here I called my function for 100 times.

Building on Romain's point: -- a portion of your function's runtime is
in memory allocation
(and you have a lot of allocations here).
If you're calling your function thousands or millions of times, then
it might pay to closely
examine your memory allocation strategies and figure out what's
temporary, for example.
It looks like you're already using  copy_aux_mem = false in a number
of places, but you're
allocating a lot of objects -- of approx what size?

For example, wouldn't this work just as well with one less allocation?
arma::vec kk = t;
arma::uvec q1 = arma::find(arma::abs(tp)<h);
kk.elem(q1) = ((1-arma::pow(tp.elem(q1)/h,2))/h)*0.75;
// done with q1.  let's reuse it.
q1 = arma::find(arma::abs(tp)>=h);
// was q2
kk.elem(q1).zeros();

You could potentially allocate memory for temporary working space in
R, grab it with copy_aux_mem = false, write your temp results there,
and reuse these objects in subsequent function calls.  It doesn't make
sense to go to this trouble, though, if your core algorithm consumes
the bulk of runtime.

Have you looked on the armadillo notes r.e. inv?  Matrix inversion has
O(>n^2).  You may be aided by pencil-and-paper math here.
http://arma.sourceforge.net/docs.html#inv

Here my matrix for inverse is only 4 by 4, so I think it's ok.

best,
Christian

Dear All,
I have tried out the first example by using RcppArmadillo, but I am not
sure whether the code is efficient or not. And I did the comparison of
the
computation time.

1) R code using for loop in R: 87.22s
2) R code using apply: 77.86s
3) RcppArmadillo by using for loop in C++: 53.102s
4) RcppArmadillo together with apply in R: 47.310s

It is kind of not so big increase. I am wondering whether I used an
inefficient way for the C++ coding:

--
A man, a plan, a cat, a ham, a yak, a yam, a hat, a canal ? Panama!