Michael Barber <[EMAIL PROTECTED]> writes: > I have been using Python for scientific computing on a variety of > systems, Mac and otherwise, with a recent focus on properties of > interaction networks. Until now, I have not needed to use more than > roughly 1 GB of RAM at a time. Thanks to some fairly straightforward > scaling properties, it is clear that the next version of the > interaction networks we're exploring will require more than 2GB of > RAM without some serious reworking of the programs. > > The simplest and most cost-effective solution appears to be just to > buy a 64 bit computer and load it up with 8 GB or so of RAM, and so > far a PowerMac G5 looks like a good solution. However, while I have a > lot of experience with Python on Macs, I've never used Python on one > of the G5s (or any other 64 bit machine), so would like to hear about > others' experiences with such a setup. The impression I have is that > it should be completely straightforward; is that so? Are there any > issues with compiling and running a 64-bit Python on a G5 that I > should be aware of? How about with Numeric or (better) numarray?
I don't know specifically about the G5, but Numeric, numarray, and numpy are routinely compiled and run on 64-bit Athlon machines, so a lot of the bugs and such have already been shaken out. If possible, you should move from Numeric to numpy; one of the goals for numpy was better 64-bit handling. But numarray may still be better for extremely large arrays; haven't checked recently. -- |>|\/|< /--------------------------------------------------------------------------\ |David M. Cooke http://arbutus.physics.mcmaster.ca/dmc/ |[EMAIL PROTECTED] _______________________________________________ Pythonmac-SIG maillist - Pythonmac-SIG@python.org http://mail.python.org/mailman/listinfo/pythonmac-sig
