Daniel Russel wrote:
i have just tried - it is much faster now. plus daniel discovered a bug in my script.By optimized, I meant tweaked grid sizes and amount particles can move and things like that. He thinks he did some work messing with it, I haven't checked :-)I think that's a little generous! It's just a standard cell-based algorithm. The only optimization I see in the code is on the hash function, and that's still a very simple function.Such helps, but I don't think it is the main source of speedup. I have the MaxChangeScoreStates which play the same role (less efficiently), but it doesn't look like they are a major time sync. I can easily put in an l2 version of that (the current is l_1) which would tighten the movement bounds a bit.The Modeller code probably gets most of its performance from having optimizers that are cooperative. In order to tell whether a nonbondupdate is required, a simple heuristic is used: has any atom moved morethan some cutoff distance since the last update? This is easy to testfor because all of the optimizers update this atom shift value wheneverthey move an atom. In IMP there is no such guarantee - the optimizerswrite back new values for the optimizable attributes whenever they feellike it (plus, of course, we have attributes other than xyz).One problem I was running in to when running some of my code was that the nonbonded lists would become quite huge and take up really large amounts of memory. I haven't yet found a good system for keeping the slack large enough so that we don't have to rebuild too often and not having the nbls be too big. The problem is that some things move quite far under my optimization scheme, but most things do not. I have some ideas in terms of only updating some of the pairs, but I haven't implemented them yet.Anyway, I haven't heard back from Frido about whether he was building with NDEBUG defined or not. If not, that would be the primary problem.
so the non-bonded list seems to be sufficiently fast, at least for my apps. best frido
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