From romain.francois at dbmail.com  Tue Mar  3 17:23:36 2009
From: romain.francois at dbmail.com (Romain Francois)
Date: Tue, 03 Mar 2009 17:23:36 +0100
Subject: [Rd] profiler and loops
In-Reply-To: <49AD238A.1060502@dbmail.com>
References: <49AD238A.1060502@dbmail.com>
Message-ID: <49AD5988.4060104@dbmail.com>


Hello,

Please find attached a patch against svn implementing this proposal.

The part I don't fully understand is the part involving the function  
loopWithContect, so I've put "[loop]" in there instead of "[for]", 
"[while]" or "[repeat]" because I don't really know how to extract the 
information.

With the script1 from my previous post, summaryRprof produces this:

[]$ /home/romain/workspace/R-trunk/bin/Rscript script1.R
$by.self
        self.time self.pct total.time total.pct
"[for]"      5.32     98.9       5.38     100.0
"rnorm"      0.06      1.1       0.06       1.1

$by.total
        total.time total.pct self.time self.pct
"[for]"       5.38     100.0      5.32     98.9
"rnorm"       0.06       1.1      0.06      1.1

$sampling.time
[1] 5.38

Romain


Romain Francois wrote:
> Hello,
>
> (This is follow up from this thread: 
> http://www.nabble.com/execution-time-of-.packages-td22304833.html but 
> with a different focus)
>
> I am often confused by the result of the profiler, when a loop is 
> involved. Consider these two scripts:
>
> script1:
>
> Rprof( )
> x <- numeric( )
>   for( i in 1:10000){
>     x <- c( x, rnorm(10) )
>   }
> Rprof( NULL )
> print( summaryRprof( ) )
>
>
> script2:
>
> Rprof( )
> ffor <- function(){
>   x <- numeric( )
>   for( i in 1:10000){
>     x <- c( x, rnorm(10) )
>   }
> }
> ffor()
> Rprof( NULL )
> print( summaryRprof( ) )
>
>
> []$ time Rscript --vanilla script1.R
> $by.self
>       self.time self.pct total.time total.pct
> "rnorm"      0.22      100       0.22       100
>
> $by.total
>       total.time total.pct self.time self.pct
> "rnorm"       0.22       100      0.22      100
>
> $sampling.time
> [1] 0.22
>
> real    0m7.786s
> user    0m5.192s
> sys     0m0.735s
>
> []$$ time Rscript --vanilla script2.R
> $by.self
>       self.time self.pct total.time total.pct
> "ffor"       4.94     92.5       5.34     100.0
> "rnorm"      0.40      7.5       0.40       7.5
>
> $by.total
>       total.time total.pct self.time self.pct
> "ffor"        5.34     100.0      4.94     92.5
> "rnorm"       0.40       7.5      0.40      7.5
>
> $sampling.time
> [1] 5.34
>
>
> real    0m7.841s
> user    0m5.152s
> sys     0m0.712s
>
>
>
> In the first one, I call a for loop from the top level and in the 
> second one, the loop is wrapped in a function call. This shows the 
> inability of the profiler to point loops as responsible for 
> bottlenecks. The coder of script1 would not know what to do to improve 
> on the script.
>
> I have had a quick look in the code, and here are a few thoughts:
>
> in the function "doprof" in eval.c,  this loop write the call stack on 
> the profiler file:
>
> for (cptr = R_GlobalContext; cptr; cptr = cptr->nextcontext) {
>   if ((cptr->callflag & (CTXT_FUNCTION | CTXT_BUILTIN))
>       && TYPEOF(cptr->call) == LANGSXP) {
>       SEXP fun = CAR(cptr->call);
>       if (!newline) newline = 1;
>       fprintf(R_ProfileOutfile, "\"%s\" ",
>           TYPEOF(fun) == SYMSXP ? CHAR(PRINTNAME(fun)) :
>           "<Anonymous>");
>   }
>   }
>  so we can see it only cares about context CTXT_FUNCTION and 
> CTXT_BUILTIN, when for loops play with CTXT_LOOP (this is again in 
> eval.c within the do_for function)
>
> begincontext(&cntxt, CTXT_LOOP, R_NilValue, rho, R_BaseEnv, R_NilValue,
>        R_NilValue);
>
> which as the name implies, begins the context of the for loop. The 
> begincontext function looks like this :
>
> void begincontext(RCNTXT * cptr, int flags,
>         SEXP syscall, SEXP env, SEXP sysp,
>         SEXP promargs, SEXP callfun)
> {
>   cptr->nextcontext = R_GlobalContext;
>   cptr->cstacktop = R_PPStackTop;
>   cptr->evaldepth = R_EvalDepth;
>   cptr->callflag = flags;
>   cptr->call = syscall;
>   cptr->cloenv = env;
>   cptr->sysparent = sysp;
>   cptr->conexit = R_NilValue;
>   cptr->cend = NULL;
>   cptr->promargs = promargs;
>   cptr->callfun = callfun;
>   cptr->vmax = vmaxget();
>   cptr->intsusp = R_interrupts_suspended;
>   cptr->handlerstack = R_HandlerStack;
>   cptr->restartstack = R_RestartStack;
>   cptr->prstack = R_PendingPromises;
> #ifdef BYTECODE
>   cptr->nodestack = R_BCNodeStackTop;
> # ifdef BC_INT_STACK
>   cptr->intstack = R_BCIntStackTop;
> # endif
> #endif
>   R_GlobalContext = cptr;
> }
>
>
> So it could be possible to set the last argument of the begincontext 
> function to "for" and use this code in the doprof function:
>
>
> for (cptr = R_GlobalContext; cptr; cptr = cptr->nextcontext) {
> if ( ( cptr->callflag & (CTXT_FUNCTION | CTXT_BUILTIN ) )
>       && TYPEOF(cptr->call) == LANGSXP) {
>       SEXP fun = CAR(cptr->call);
>       if (!newline) newline = 1;
>       fprintf(R_ProfileOutfile, "\"%s\" ",
>           TYPEOF(fun) == SYMSXP ? CHAR(PRINTNAME(fun)) :
>           "<Anonymous>");
>   } else if( cptr->callflag & CTXT_LOOP){
>     SEXP fun = CAR(cptr->syscall);
>     if (!newline) newline = 1;
>     fprintf(R_ProfileOutfile, "\"%s\" ", CHAR(PRINTNAME(fun)) );
>   }
> }
>
> so that we see for in the list of "functions" that appear in the 
> profiler file.
>
> Obviously I am taking some shortcuts here, because of the other loops, 
> but I would like to make a formal patch with this. Before I do that, 
> I'd like to know :
> - is this has a chance of breaking something else (does the CTXT_LOOP 
> being R_NilValue is used elsewhere)
> - would this feature be welcome.
> - Should I differentiate real functions with loops in the output file, 
> maybe I can write "[for]" instead of for to emphacize this is not a 
> function.
>
> Romain
>


-- 
Romain Francois
Independent R Consultant
+33(0) 6 28 91 30 30
http://romainfrancois.blog.free.fr


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[Rd] profiler and loops
Romain Francois