Hi Jon,
Last night, I compiled and tried Trilinos 11.10 from the Trilinos git
repo, I am still getting the memory leak. I see it in both RSS and
VSIZE. Looking back at your memory numbers from your previous email,
they seem too small for even storing the float data for all the cells.
The slow convergence that Trevor is seeing is normal. I did some more
testing and found that using initial_solver_iterations_per_step = 20
will improve convergence relative to the number of self-consistent
iterations in this example. The total energy should go to about -316.xx
eV when it is converged. In the terminal output, it looks like this:
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Step 24 Total Energy -315.957897784 dE 1.86055284542 dE/|toten|
0.00588861002833 max_rel_error 0.125229938669
Also, the script will read previous calculations as starting conditions,
to prevent this, delete the psi_e_*.txt files.
I am running these calculations on Ubuntu 14.04 64bit. /Trevor,/ what
are you running on? I might be able to help with compilation.
What is the oldest version of Trilinos that FiPy has used? I could try
that and see if my problem persists.
Thanks again!
-Mike Waters
On 3/30/16 11:52 AM, Guyer, Jonathan E. Dr. (Fed) wrote:
It looked to me like steps and accuracy were the way to do it, but my
runs finish in one step, so I was confused. When I change to accuracy
= 10.0**-6, it takes 15 steps, but still no leak (note, the hiccup in
RSS and in ELAPSED time is because I put my laptop to sleep for
awhile, but VSIZE is rock-steady).
The fact that things never (or slowly) converge for you and Trevor, in
addition to the leak, makes me wonder if Trilinos seriously broke
something between 11.x and 12.x. Trevor's been struggling to build
12.4. I'll try to find time to do the same.
In case it matters, I'm running on OS X. What's your system?
- Jon
On Mar 29, 2016, at 3:59 PM, Michael Waters <[email protected]
<mailto:[email protected]>> wrote:
When I did my testing and made those graphs, I ran Trilinos in serial.
Syrupy didn't seem to track the other processes memory. I watched in
real time as the parallel version ate all my ram though.
To make the program run longer while not changing the memory:
steps = 100 # increase this, (limits the number of self-consistent
iterations)
accuracy = 10.0**-5 # make this number smaller, (relative energy
eigenvalue change for being considered converged )
initial_solver_iterations_per_step = 7 # reduce this to 1, (number of
solver iterations per self-consistent iteration, to small and it's slow,
to high and the solutions are not stable)
I did those tests on a machine with 128 GB of ram so I wasn't expecting
any swapping.
Thanks,
-mike
On 3/29/16 3:38 PM, Guyer, Jonathan E. Dr. (Fed) wrote:
I guess I spoke too soon. FWIW, I'm running Trilinos version: 11.10.2.
On Mar 29, 2016, at 3:34 PM, Guyer, Jonathan E. Dr. (Fed)
<[email protected] <mailto:[email protected]>> wrote:
I'm not seeing a leak. The below is for trilinos. VSIZE grows to
about 11 MiB and saturates and RSS saturates at around 5 MiB. VSIZE
is more relevant for tracking leaks, as RSS is deeply tied to your
system's swapping architecture and what else is running; either
way, neither seems to be leaking, but this problem does use a lot
of memory.
What do I need to do to get it to run longer?
On Mar 25, 2016, at 7:16 PM, Michael Waters
<[email protected] <mailto:[email protected]>> wrote:
Hello,
I still have a large memory leak when using Trilinos. I am not
sure where to start looking so I made an example code that
produces my problem in hopes that someone can help me.
But! my example is cool. I implemented Density Functional Theory
in FiPy!
My code is slow, but runs in parallel and is simple (relative to
most DFT codes). The example I have attached is just a lithium and
hydrogen atom. The electrostatic boundary conditions are goofy but
work well enough for demonstration purposes. If you
set use_trilinos to True, the code will slowly use more memory. If
not, it will try to use Pysparse.
Thanks,
-Michael Waters
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