You did not specify the corresponding :RKM values, which lists the
actual matrix size in your calculations.
Two remarks: the quoted numbers are typical averages with "sensible
RMTs and close-packed structures.
I do not understand / believe the supercell sizes. What is a supercell
with 17 atoms ? How do you create from 10 atoms --> 17 atoms ??
What are your RMT values ???
PS: k-parallel means you are using n lapw1 runs, and each of them
requires the same memory. So of course, when running on a single cpu n
k-parallel jobs, you need n times the memory of a single calculation.
Am 05.07.2018 um 16:32 schrieb Luc Fruchter:
[ ... I apolodgize for having not responded yet to a pending discussion
that I already have for another subject - and probably to this one also
for a while, but the mail archive webmaster agrees than one cannot
answer with 'reply button' until this is fixed ...]
Here is my problem,
I am running cases of supercells of different sizes, using the
k-parallel method. To make it simple, I only consider a 10 cores machine
running these cores locally.
The machine has 32 Gb memory, and NTMATMAX was set according to the
installation suggestion:
NTMATMAX = 19000 (2 Gb)
NUME = 6000
The cases I have run presently are from group 26 (no inversion), with
number of atoms ranging from 10 to 22, depending on the supercell size.
I find the following memory requirements, using k-parallel method, fixed
k grid and default RKMAX:
Number of atoms / memory per CPU used
10 / 1.7 Gb
12 / 2
15 / 2.7
17 / 3.1
22 / 4.3
So, this exceeds what I expected to be the maximum limit (from manual p.
255 ~ 2 Go / CPU) and precludes the computation of larger cells, using
reasonable memory (3-6 Gb / CPU). Increasing the number of CPU will not
solve the problem, as the memory per CPU needed appears proportional to
the number of these CPUs.
Could someone recall the general principles for memory usage estimate in
the k-parallel method, and how I could be able to run larger cells
within these principles ?
Thanks
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