Please note that the problem was caused by a lack of memory on my computer.
I modified the SWAP file to be about 10G, and the build has worked well
since then. The build takes about 3 1/2 hours.
regs, Kev
On Monday 16 September 2024 at 06:12:03 UTC+10 dim...@gmail.com wrote:
> Curiously, this
Curiously, this might be a regression in meson 1.3.2 (or perhaps your
OS mangles it somehow), as Sage carries 1.3.1.
Anyhow, the current meson version is 1.5.1, so both of these are old.
On Sun, Sep 15, 2024 at 2:17 PM Kevin Youren wrote:
>
> Dima,
>
> well done and thank you!
>
> I started the
Dima,
well done and thank you!
I started the rebuild very soon after your suggestion. The build is doing
the html doc stage, well passed the scipy.
I think I did 5 or 6 builds that failed.
There was no freeze.
Thank you very much,
regards, Kevin
On Sunday 15 September 2024 at 20:37:59 UT
That's unfortunate, and it might be a bug in the meson/meson-python/ninja
versions installed on your machine. (that's a curse of LTS versions, they
often remain with old buggy versions).
You can check if using instead versions vendored by Sage would work.
Run
./configure --with-system-meson=no --
Thanks for your suggestions, but the run still stops in the scipy steps.
# Sep 15 - no luck, stopped at 10:01
export NINJA_ARGS="-j1"
export JOBS=1
make
This time slightly earlier.
[scipy-1.12.0] [spkg-install] [1001/1610] Compiling C object
scipy/io/matlab/_streams.cpython-312-x86_64-linux-gn
On Sat, Sep 14, 2024 at 7:00 AM Kevin Youren wrote:
>
> Dima,
>
> thanks for the hint,
>
> but
>
> export NINJA_ARGS="-j4"
> make
>
> didn't work. It still 'froze' .
Could you try -j1 rather than -j4 ?
And also
export JOBS=1
>
>
> Restarting
>
> using
> export NINJA_ARGS="-j4"
> make
>
> is wor
Dima,
thanks for the hint,
but
export NINJA_ARGS="-j4"
make
didn't work. It still 'froze' .
Restarting
using
export NINJA_ARGS="-j4"
make
is working using the export and the make, but the scipy steps still had the
12 cpus at 100% together with the fan noise.
When scipy finished , the m
On 13 September 2024 14:20:01 BST, Kevin Youren wrote:
>Thanks Oscar,
>
>If I can work out how to do the pip install, I will try the -j1.
Did you try my suggestion, with exporting variables?
These export statements can be put into
build/pkgs/scipy/spkg-install.in
Oscar's hack can also be done
Thanks Oscar,
If I can work out how to do the pip install, I will try the -j1.
The simple thing is, make by itself is supposed to NOT have multiple
instances running.
At the moment, I run make, it uses multiple cpus, but not all 12. When it
gets to scipy , it uses all 12 cpus, then "overheats
On Thu, 12 Sept 2024 at 14:25, Dima Pasechnik wrote:
>
> Sage merely invokes pip to build scipy from source.
>
> Indeed, apart from ninja paralellism there is meson parallelism,
> which is controlled by JOBS env. variable (?).
> Note that JOBS should be just a number.
I think meson just delegates
Sage merely invokes pip to build scipy from source.
Indeed, apart from ninja paralellism there is meson parallelism,
which is controlled by JOBS env. variable (?).
Note that JOBS should be just a number.
On Thursday, September 12, 2024 at 10:29:10 AM UTC+1 oscar.j@gmail.com
wrote:
> On
On Thu, 12 Sept 2024 at 09:31, Dima Pasechnik wrote:
>
> scipy itself is not built with configure/make, it's built with meson,
...
> There is no direct way to specify a non-default "-j" value, however it
> appears to be possible to do this via meson,
> which invokes ninja via "meson compile".
Ho
scipy itself is not built with configure/make, it's built with meson, which
invokes ninja (a faster replacement for make, in particular
it parallelizes the tasks much better - but in your case it goes overboard
with it).
You can see it in your log:
[spkg-install] Found ninja-1.11.1 at /usr/bin/nin
Thanks for replying, Eric
I did precisely what you suggested, tried make -j4, but no luck.
I even opened and read my paper book "GNU Make" by Stallman.
So, I tried "make" by itself, and it did slow it down a bit.
However scipy simply took over all 12 cpus, at lightning speed.
The advantage of
Hi,
>From the log file:
[spkg-install] g++: fatal error: Killed signal terminated program cc1plus
This points towards a maximum memory reached. You may decrease the number
of threads in the parallel build, e.g. using make -j4 instead of make -j8.
Best regards,
Eric.
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