You don't need to post all your code, just a small example that 
demonstrates the problem you are experiencing.

If your computation is using half the memory on the machine, the solution 
is likely going to be to find a way to make it use less memory or to get a 
machine with more memory. 

The behaviour you've described so far seems wholly consistent with how 
Python handles objects, how garbage collectors work and how various 
libraries used by Sage handle memory. So far it doesn't sound like a bug to 
me.

Bill.

On Wednesday, 28 September 2016 14:08:09 UTC+2, Denis wrote:
>
>
> Jonathan, thank you for this thoughtful analysis. With a really simple 
> function, I get the output
>
> 0
> 1066.03125
> 0
> 1066.03125
> 0
> 1066.1640625
> 0
> 1066.1640625
> 0
> 1066.29296875
> 0
> 1066.29296875
> 0
> 1066.29296875
> 0
> 1066.29296875
> 0
> 1066.421875
> 0
> 1066.421875
> 0
> 1066.421875
> 0
> 1066.421875
> 0
> 1066.421875
> 0
> 1066.421875
> 0
> 1066.421875
> 0
> 1066.5546875
> 0
> 1066.5546875
> 0
> 1066.5546875
>
> .... and constant afterwards.
>
> I do not know whether the initial rise is a problem but I suspect not. I get 
> the same
> behavior on the small (4G) machine, only with different numbers of course.
>
> The output of overcommit_memory is zero, so that's not it.
>
> I am quite willing to share my code with you and others who think they can 
> help at a
> similar level of commitment, but would prefer not to publish the code where 
> anyone else
> could read it. Please suggest a private channel if you are interested - I 
> could open
> a dedicated gmail address and post it here, unless you have a better idea.
>
>
> Denis
>
>

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