On Friday, January 13, 2017 at 5:30:04 PM UTC, Enrique Artal wrote:
>
> Putting limits in /etc/security/limits.conf (or in files in limits.d) 
> works right up to Sage 7.3. Namely, if a user performs a strong computation 
> (memory or CPU time), the system stops the computation when the limit is 
> reached; usually one needs to quit the worksheet, but it is possible to 
> reuse the notebook. With 7.4 and 7.5, when the limit is reached the 
> notebook becomes unusable and the only possibility to work is to kill and 
> restart it. Some change between 7.3 and 7.4 may cause it.
>

"the notebook"? Which one? sagenb, or jupyter?
 

>
>
> El domingo, 27 de noviembre de 2016, 21:55:06 (UTC+1), Enrique Artal 
> escribió:
>>
>> It seems to work now with the ulimits for the server_pool users. If they 
>> become too strict, we (maybe more precisely MIguel Marco) will try the 
>> worker user approach. We will let know. Thanks for the help!
>>
>> El domingo, 27 de noviembre de 2016, 21:23:33 (UTC+1), Nils Bruin 
>> escribió:
>>>
>>> On Sunday, November 27, 2016 at 3:04:48 AM UTC-8, Enrique Artal wrote:
>>>>
>>>> Thanks, As you say, it would be better something more direct, but your 
>>>> approach is a strong improvement for my needs. 
>>>> By the way, I changed in our experimental notebook 7.4 -> 7.3 and the 
>>>> limits work: they stop the process and the notebook is still running.
>>>>
>>>
>>> for sage 7.5beta(?) setting ulimits does have effect: with
>>>
>>> sh$ ulimit  -v 10000000
>>> sh$ sage -c 'L=[1]
>>> for i in [1..1000]:
>>>   L = L+L
>>>   print i'
>>>
>>> I get a memory error after "28" has been printed (and without it, it 
>>> continues longer), and if I take the bound much lower sage will not even 
>>> start.
>>>
>>> So if you configure the "worker" user to have such a ulimit, I'd expect 
>>> memory problems to be significantly reduced. People who try to use more 
>>> memory should see their kernel die before it's causing problems for other 
>>> people.
>>>
>>> Given that there's no way of controling which notebook user gets mapped 
>>> to which worker uid, I don't think there's much mileage to be had from 
>>> configuring multiple worker uids (other than having them on multiple 
>>> machines to load-balance a little bit).
>>>
>>>

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