On 20 December 2012 at 13:25, Alon Honig wrote:
| Thank you for providing a point of reference with regards to speed. Dirk's
| examples have ratios of 60:1 causing me to rethink my approach.
That is __obviously__ problem dependent.
We have seen anything from more than 10k (for somewhat degenerate cases and
our sugar "quit quickly" approach; see the Rcpp-introduction and paper) to
several hundred (recursive function calls in Fibonacci) to these 60-some for
looping examples (MCMCC Gibbs, VAR(2) model, ...) to just two or less
(previous email).
What you compare against matters.
Very sage advice by Hoa below.
Dirk
| On Thu, Dec 20, 2012 at 1:18 PM, H Xiong <haoxiong.u...@gmail.com> wrote:
|
| Hi Alon,
|
| I am only a user, not a developer, of Rcpp, so I will offer some
| observations only.
|
| On Thu, Dec 20, 2012 at 9:35 AM, Alon Honig <honey...@gmail.com> wrote:
|
| My current RCPP program is only 4 times faster than its R byte code
| compiled equivalent. I am trying to speed up my code and from what I
| understand using pointers prevents an external function from copying
| the entire object when executing its methods. I am having difficulty
| finding salient examples that use points and NumericVectors. Please
| tell me how in this same code I could get the functions "get_sum" and
| "get_var" to point to the NumericVector object "v" rather than copy
the
| whole thing.
|
|
| Many of R commands have C or Fortran implementation so it is not always
the
| case that Rcpp program will be many times faster. I once translated an R
| loop into C and I roughly doubled the speed, so 4 times speedup isn't
| bad. Your examples are very simple functions that R has built-in commands
| for and it is unlikely you can surpass R implementation in overall
| robustness and numeric stability.
|
| I don't recommend messing with raw pointers. Even if you are familiar with
| C interface of R's garbage collector, it is better to let Rcpp take care
of
| the low level details for you. You can use constant reference to pass
| objects around and there is no copy involved (see below). You just need to
| be careful that objects are held by some variables and not garbage
| collected by R's garbage collector.
|
|
|
|
| library(inline)
| library(Rcpp)
| a=1:1000000
| Rcpp.var = cxxfunction(signature(input="numeric"), plugin="Rcpp",
| body="
|
| NumericVector v = input;
|
| Here there is no copy, because the constructor for NumericVector taking
| SEXP knows how to use pointers. Note that this no-copy behavior only
| applies when SEXP is holding an object of the same type as the
| constructor's type.
|
|
| int n = v.size();
|
| double v_mean = get_sum(v,n)/n;
|
| double v_var = get_var(v,v_mean,n);
|
| return wrap(v_var);
|
|
| ",includes="
|
|
| double get_var(NumericVector v,double m,int l)
|
| double get_var(const NumericVector& v, double m, int l)
|
|
| {double a = 0;
|
| for (int i = 0; i <l;i++)
|
| {a += (v[i]-m)*(v[i]-m);}
|
| return(a/l);
|
| }
|
|
|
| double get_sum(NumericVector v,int l)
|
| double get_sum(const NumericVector& v, int l)
|
| Hao
|
|
| { double s = 0;
|
| for (int i = 0; i <l;i++)
|
| {s += v[i];}
|
| return(s);
|
| }
|
| ")
|
| b=system.time(for (i in 1:100)Rcpp.var (a))
| c= system.time(for (i in 1:100)var (a))
|
|
|
| Thank you Alon.
|
| P.S. I am aware that the "get_var" function provides the population
| variance and not the sample variance.
|
|
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|
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|
|
|
|
|
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--
Dirk Eddelbuettel | e...@debian.org | http://dirk.eddelbuettel.com
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