On Tue, Aug 7, 2012 at 6:33 AM, Armin Rigo wrote:
> If you can come up with a more precise scheme, you're welcome. The
> issue is to know when it's ok to reserve from that pool and when we
> should raise an RPython MemoryError instead. A possible answer would
I'm not convinced this MemoryErr
On Tue, Aug 7, 2012 at 6:33 AM, Armin Rigo wrote:
> If you can come up with a more precise scheme, you're welcome. The
> issue is to know when it's ok to reserve from that pool and when we
> should raise an RPython MemoryError instead. A possible answer would
> look like "when allocating interna
Hi Ronny,
On Tue, Aug 7, 2012 at 1:56 PM, Ronny Pfannschmidt
wrote:
> However in some cases (like the example) the memory error is caused by
> accumulating more and more smaller objects,
> in which case the memory one would use for a Stack-trace is used up and the
> extra pool would be used.
I'm
Hi Armin, Harald,
On 08/07/2012 11:28 AM, Armin Rigo wrote:
Hi Harald,
On Tue, Aug 7, 2012 at 10:23 AM, Massa, Harald Armin wrote:
outside of programming there is the concept of having a secret backup
("nest egg"). Would'nt it be a solution to preallocate some bytes on
startup for really, rea
Hi Harald,
On Tue, Aug 7, 2012 at 10:23 AM, Massa, Harald Armin wrote:
> outside of programming there is the concept of having a secret backup
> ("nest egg"). Would'nt it be a solution to preallocate some bytes on
> startup for really, really bad times?
It might help in general, but not in this
Tuesday 07 August 2012 you wrote:
> Re-hi,
>
> I tried to debug it more precisely, and it seems that the problem is
> even more basic than I thought. It is very hard to solve in general.
> The issue is that when we are really out of memory, then *every*
> single allocation is going to fail. The
> What occurs then in PyPy is that when we are out of memory, we can
> really not allocate any single object at more.
outside of programming there is the concept of having a secret backup
("nest egg"). Would'nt it be a solution to preallocate some bytes on
startup for really, really bad times?
As
Re-hi,
I tried to debug it more precisely, and it seems that the problem is
even more basic than I thought. It is very hard to solve in general.
The issue is that when we are really out of memory, then *every*
single allocation is going to fail. The difference with CPython is
that in the same si
Hi Roger,
On Tue, Aug 7, 2012 at 7:41 AM, Roger Flores wrote:
> Can someone else at least confirm this?
Yes, I can reproduce it easily running in a 32-bit chroot on a machine
with more than 4GB of RAM.
The problem is the same, and is still not solved: we run out of memory
when doing a minor cyc
