Sebastian is right. Since Matlab r2007 (i think that's the version) it has included support for multi-core architecture. On my core2 Quad here at the office, r2008b has no problem utilizing 100% cpu for large matrix multiplications.
If you download and build atlas and lapack from source and enable parrallel threads in atlas, then compile numpy against these libraries, you should achieve similar if not better performance (since the atlas routines will be tuned to your system). If you're on Windows, you need to do some trickery to get threading to work (the instructions are on the atlas website). Chris
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