Hi Mike,
Thanks for your reply. I just tried the garbage collection and it seems did
not help very much with the leak issue for trilinos. My Pysparse throw me
Segmentation fault, which I don't really understand why.
For the check point approach, just to make sure that I understand it
correctly, are you using dump from Fipy.tools to store the solution
variable, and read them back ? I guess I also need to re-declare my
equation formulations, and boundary conditions each time I read them back.
Also, I wonder how to delete/remove all the previous object so that I could
have a "fresh" start after each check point iteration ?
Thanks,
Zhekai
On Tue, Jun 20, 2017 at 4:51 PM, Michael J. Waters
wrote:
> Hi Zhekai Deng,
>
> I had a similar problem. In the end, I just created check point files and
> restarted frequently.
>
> I did find that garbage collecting helped slow the leak and,
> interestingly, also sped up code execution for me.
>
> Best,
>
> -Mike
>
> On 6/20/17 10:39 AM, Zhekai Deng wrote:
>
> HI All,
>
> I think I run into some memory leak issues using trilinos as my solver
> both for serial and parallel case. The total memory goes up from initial
> around 300 MB to the my system memory limit (like 29 GB), and program
> stops. I have attached my example code below.
>
> Somethings I am not sure if I implement it correctly:
> 1. in the example code, I basically solve multiple equations at the same
> time. I use list, and append my CellVarible together
>
> 2. Similar, I use list and append my equation together
>
> 3. Create coupled equation by looping through the list element, and solve
> this coupled equation.
>
> 4. During the solution step, I loop through the list element, and do
> updateOld()
>
> The results of the numerical calculation looks correct to me, I just have
> this memory issue that prevent me from going longer time steps because I
> run out of memory.
>
> I wonder is there any workaround/fix to this problem ?
>
> I am using the build from Anaconda repository, default trillions solver,
> and my OS is Ubuntu 16.04.
>
>
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