Did anybody actually compare the performance among phenix.refine, CNS and refmac5? I am trying the phenix.refine from the latest CCI bundle for my refinement. I have a relative large structure (800 kD unique) and unit cell (140, 160, 550, 90, 90, 90). The data is at low resolution ( 3.8 A) with experimental phases. My impression is that phenix.refine takes a much longer time to finish the jobs, say rigid body refinement or SA refinement, and it also takes a lot more memories ( in my case, phenix.refine uses more than 700 MB, but other programs use less than 200 MB).

We have been concentrating on features and a high level of automation much more than raw speed and memory efficiency. Given that memory is so cheap these days (ca. $80/GB) there isn't much incentive for us to trade developer time for a smaller memory footprint. Speed optimizations are a bit higher up on the list.

Is this because the python code in phenix.refine? CNS and refmac5 are written in FROTRAN, I think. Just curious.

phenix.refine doesn't spend much time in the Python code. It is a long while ago I did careful timings, but I'd guess it is significantly less than 10% of the time. C++ is intrinsically almost as fast as FORTRAN if the same development time is invested in the code. I.e. what you see is not a language issue, just a tradeoff features vs. optimization. We'll work on making phenix.refine a bit faster in the future, but at the minute more features are still our focus. Ralf