R devel - Sep 2012 - Possible page inefficiency in do_matrix in array.c

In do_matrix in src/array.c there is a type switch containing :

case LGLSXP :
    for (i = 0; i < nr; i++)
    for (j = 0; j < nc; j++)
        LOGICAL(ans)[i + j * NR] = NA_LOGICAL;

That seems page inefficient, iiuc. Think it should be :

case LGLSXP :
    for (j = 0; j < nc; j++)
    for (i = 0; i < nr; i++)
        LOGICAL(ans)[i + j * NR] = NA_LOGICAL;

or more simply :

case LGLSXP :
    for (i = 0; i < nc*nr; i++)
        LOGICAL(ans)[i] = NA_LOGICAL;

( with some fine tuning required since NR is type R_xlen_t whilst i, nc
and nr are type int ).

Same goes for all the other types in that switch.

This came up on Stack Overflow here :
http://stackoverflow.com/questions/12220128/reason-for-faster-matrix-allocation-in-r

Matthew

On Sep 2, 2012, at 10:04 PM, Matthew Dowle wrote:
> 
> In do_matrix in src/array.c there is a type switch containing :
> 
> case LGLSXP :
>    for (i = 0; i < nr; i++)
>    for (j = 0; j < nc; j++)
>        LOGICAL(ans)[i + j * NR] = NA_LOGICAL;
> 
> That seems page inefficient, iiuc. Think it should be :
> 
> case LGLSXP :
>    for (j = 0; j < nc; j++)
>    for (i = 0; i < nr; i++)
>        LOGICAL(ans)[i + j * NR] = NA_LOGICAL;
> 
> or more simply :
> 
> case LGLSXP :
>    for (i = 0; i < nc*nr; i++)
>        LOGICAL(ans)[i] = NA_LOGICAL;
> 
> ( with some fine tuning required since NR is type R_xlen_t whilst i, nc
> and nr are type int ).
> 
> Same goes for all the other types in that switch.
> 
> This came up on Stack Overflow here :
>
http://stackoverflow.com/questions/12220128/reason-for-faster-matrix-allocation-in-r
> 
That is completely irrelevant - modern compilers will optimize the loops
accordingly and there is no difference in speed. If you don't believe it,
run benchmarks ;)

original
> microbenchmark(matrix(nrow=10000, ncol=9999), times=10)
Unit: milliseconds
                               expr      min       lq  median       uq      max
1 matrix(nrow = 10000, ncol = 9999) 940.5519 940.6644 941.136 954.7196 1409.901


swapped
> microbenchmark(matrix(nrow=10000, ncol=9999), times=10)
Unit: milliseconds
                               expr      min       lq   median      uq      max
1 matrix(nrow = 10000, ncol = 9999) 949.9638 950.6642 952.7497 961.001 1246.573

Cheers,
Simon

> Matthew
> 
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