[hyperbovine]

Funny, I do a lot of stuff with Monte-Carlo* as well and I have reached the opposite conclusion. It's soooo much easier (and more pleasurable) to prototype in Python versus chasing down null pointer violations all afternoon. At least for my simulations I have always found that 90+% of the execution time is spent in one or two routines which can then be factored out into C (or FORTRAN, which is faster.) Also, it's much easier to inspect and graph your data in Python; when I develop in C I tend to skip these things because they're such a PITA. I can't help but wonder what I'm missing.

Although, at a 100x productivity increase, I might have to give it another look; I'd be out of grad school by Halloween.

*For the uninitiated, Monte Carlo is a fancy way of saying "for loops."

[chasingsparks]

I think you misinterpreted what I said. I prototyped formerly in Python, and now with Ruby. I also do not chase down null pointer violations most of the time (except when debugging any CUDA exported functions that need speed).

[hyperbovine]

Ahh, righto, sure did! Well then we agree. How do you like CUDA? We just took delivery on a 4xTesla C1060 box which I can't wait to check out. Sadly it's sitting in a closet right now because of departmental squabbling over who must foot the air-con bill when it gets plugged in :-)

[chasingsparks]

I have a single C1060 on my desktop system -- it is the single greatest investment I have ever made. Granted, debugging CUDA is not great, but the for many things Thrust alone (http://gpgpu.org/2009/05/31/thrust) can make demolish any bottlenecks so you can get closer to your idea rather than spending all your time on metal. However, I have to play with OpenCL...especially now that OSX has built in support!