We've run the benchmark in.rhodo problem (replicated) on
2 billion atoms (64K procs), and PPPM does fine. What
yep. and for that system the heuristics seem to work in a
way that look reasonable to me.
params do you think it isn't going to estimate correctly?
the offending code is in src/KSPACE/pppm.cpp line 852:
since i'm doing a coarse grained MD with (some) charged particles,
i'm having a different relation between atom density and cutoff
(15 angstrom). as a result the term inside the logarithm is > 1.0
unless i use a precision parameter of 1.e-7 or lower.
in the the rhodo example one gets a (maximum?) g-vector of about 0.25
and one grid point per about 2.5 angstrom.
with (smooth) PME in other codes (i've never had to deal with PPPM
before) i'm getting pretty consistently good energy conservation
and reliable forces with the corresponding parameters set to 0.1
and about one grid point per angstrom. i have the feeling the PPPM
needs a little more system dependent tweaking, which is why i
was asking for some "rule of the thumb metrics".
for the sake of completeness. another property of the CG runs is
that there are very few charged particles and their charges are
scaled down, so i was hoping that i can get a good energy conservation
with a somewhat smaller grid than for a regular all-atom system...
if the in.rhodo example worked reliably up to that large a size,
i can probably just scale up those parameters and transfer them
to my system and then see how much i can tweak them to give good
throughput at an acceptable accuracy.