[gmx-developers] double precision minimization accuracy limits.

[David.Osguthorpe at UCHSC.edu]

Hi,

Im attempting to minimize a protein-solvent system (>10,000 waters) using the double precision program
to minimize structures dumped from a single precision dynamics run.

Ive switched off all constraints, including switching to flexible SPC waters, added switching functions to the
LJ and coulombic potentials to make a smooth cutoff.

However, all minimizations (conjugate gradients, l-bfgs)  all seem termate to terminate at what I consider
to be large derivatives for a double precision program.

e.g. 

Polak-Ribiere Conjugate Gradients converged to machine precision in 123 steps,
but did not reach the requested Fmax < 0.01.
Potential Energy  = -1.64197713818716e+06
Maximum force     =  2.32094495259875e+02 on atom 31761
Norm of force     =  6.19775726238427e+00


Low-Memory BFGS Minimizer did not converge to Fmax < 0.01 in 1501 steps.
Potential Energy  = -1.65198292382305e+06
Maximum force     =  2.70928575898524e+02 on atom 25485
Norm of force     =  6.58974288803592e+00

Is there some step size variable I should be making smaller to allow the minimizers to make even smaller
changes to the coordinates (Im assuming from the message its at 10-12 changes or less).

Am I expecting too much of the potentials, forces etc. to deliver lower forces?
In particular Id like to have the Maximum force under 10

By the way I made some modifications to the tpbconv program to allow me to pass full double precision coordinates
to the program as otherwise writing out to a .gro file jumps the max force and norm significantly and I dont
see a way to continue from steepest descent with conjugate gradients or l-bfgs without performing a new mdrun run.
- and lbfgs seemed to take forever to work on its own and get nowhere - cg was way below it in force/energy after
far fewer iterations.

Thanks

David




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