Re: CCL:New linear scaling method

[jmmckel { *at * } attglobal.net]

Hello,
 My comments were in fact related to optimization of geometries for systems
 having 10**5 atoms, i.e. very large systems.  This being made feasable because
 of  MOPAC's extremely fast LocalSCF procedure.
 John McKelvey
 Victor Anisimov wrote:
 > Dear CCLers,
 >
 > John McKelvey has asked me a question regarding the local minimum
 > problem. I believe the problem is very important to be discussed on the
 > list. Therefore I post my answer to the list.
 >
 > ----- Original Message -----
 > From: <jmmckel { *at * } attglobal.net>
 >
 > > Victor,
 > >
 > > How would the problem of local minima be handled if the program were
 to do
 > a
 > > geometry optimizatopn on 10**5 atoms?
 > >
 > > Regards!
 > >
 > > John McKelvey
 >
 > Dear John,
 >
 > Perhaps you agree, that the local minimum problem is a separate one to
 > the linear scaling solution of the diagonalization of Fock matrix. LocalSCF
 > method itself resolves just the diagonalization problem. The same do other
 > respected linear scaling methods, e.g. MOZYME, D&C, CG-DMS.
 >
 > However I agree that the local minimum problem has to be addressed if one
 > is serious about protein modeling. This requires molecular dynamics
 > averaging
 > applied after some preliminary structure refinement done by geometry
 > optimization.
 >
 > Taking the present program code one can do full geometry optimization
 > for 100,000+ real protein on a single-CPU PC. I bet QM MD for about
 > 1,000 atoms protein is a feasible job for a 10 CPUs Linux cluster nowadays.
 > Although this has to be implemented first.
 >
 > Full QM MD modeling of proteins is not a long future. The present LocalSCF
 > code
 > works just on 1 CPU. Being parallelized it could utilize about 1000 CPUs
 > quite
 > effectively. This unusual level of parallelization is not just my
 > imagination.
 > This capability comes from extremely  high localization level of the
 > LocalSCF
 > method. As the LocalSCF preprint shows, LMOs expanded just on 30 atomic
 > centers are enough to get 0.001 RMS error on atomic charges. This level of
 > localization is extremely favorable for parallelization.
 >
 > We already made some tests on 1 CPU machine applying D&C technique on
 > the top of LALM, which is a similar to the LocalSCF engine. 1,000,000 atoms
 > irregular linear peptide built from random combination of 14 different
 amino
 > acids
 > was divided on 300 fragments. Calculating each fragment sequentially on the
 > one CPU gave the energy converged in 7 hours. Of course, the convergence
 > criterion was quite loose but this was enough to show a feasibility of the
 > D&C / LocalSCF concept.
 >
 > I believe the publishing of the LocalSCF paper makes a valuable
 contribution
 > for
 > the wide dissemination of the idea. As I mentioned in my previous posting
 > the
 > preprint is available from the Chemistry Preprint Server by URL
 > http://preprint.chemweb.com/physchem/0304005
 > The server requires registration, but the registration is free.
 >
 > Hope, I answered your question.
 >
 > With kind regards,
 > Victor
 >
 > --
 > Victor Anisimov
 > FQS Poland