Here is a small c program that we used more than a year ago to confirm that tiger is really doing a 64-bit malloc (on G5).
<code: test64.c > #include <stdlib.h> #include <stdio.h> int main() { size_t n; void *p; double gb; for(gb=10;gb>.3;gb-=.5) { n= 1024L * 1024L * 1024L * gb; p = malloc( n ); printf("%12lu %4.1lfGb %p\n",n,n/1024./1024./1024.,p); free(p); } return 0; } </code> Hope this helps anyone. Sebastian On 2/1/07, Travis Oliphant <[EMAIL PROTECTED]> wrote: > Louis Wicker wrote: > > > Travis: > > > > yes it does. Its the Woodcrest server chip > > <http://www.intel.com/business/xeon/?cid=cim:ggl%7Cxeon_us_woodcrest%7Ck6913%7Cs> > > which > > supports 32 and 64 bit operations. For example the new Intel Fortran > > compiler can grab more than 2 GB of memory (its a beta10 version). I > > think gcc 4.x can as well. > > > Nice. I didn't know this. > > > However, Tiger (OS X 10.4.x) is not completely 64 bit compliant - > > Leopard is supposed to be pretty darn close. > > > > Is there a numpy flag I could try for compilation.... > > It's entirely compiler and system dependent. NumPy just uses the system > malloc. If you can compile it so that the system malloc supports 64-bit > then O.K. (but you will probably run into trouble unless Python is also > compiled as a 64-bit application). From Robert's answer, I guess it is > impossible under Tiger to compile with 64-bit support. > > -Travis > > _______________________________________________ > Numpy-discussion mailing list > Numpy-discussion@scipy.org > http://projects.scipy.org/mailman/listinfo/numpy-discussion > _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion