Musselman, Eli D wrote:
This works great but ***here’s the problem*** : *the simulations run exceedingly slow when I use such a high number of defined ‘energygrps’*. Without using the user defined potential functions I was getting roughly 25 ns/day (which, as always with GROMACS, is amazingly fast!). With the applied potential functions and ‘energygrps’ however I am only getting 1.5 ns/day. I thought one problem might be the number of times that ‘mdrun’ spends writing to the energy (.edr) file, but I have ruled this out as a possibility because when I increased my ‘nstenergy’ in my *.mdp file by 100 fold ‘mdrun’ still runs at the same slow rate. The slowdown therefore appears to be directly related to the number of ‘energygrps.’. To confirm this, I decreased the number of ‘energygrps’ to 3 (by lumping all ‘C1’ and ‘C2’ atoms together into one ‘energygrp’ and all ‘O1’ and ‘O2’ atoms into another ‘energygrp’) and this accelerated the simulations dramatically; however, the same user defined potential functions are then applied to both **intra** and **inter**molecular interactions, which is not what I want!
Good diagnostics and description, thanks. It seems quite likely to me that this slowdown will be related to cache misses. 95 tables actually uses an appreciable amount of memory. More salient for the inner loops, however is that each time a new table is being used in each integration step, the code will have to go and fetch locations from main memory, and when these hit the caches they won't be reused much.
The only simple work-around I can suggest is to decrease the density of data points in the table. That will degrade the accuracy, but possibly lead to fewer cache misses.
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