On Wed, Jul 11, 2018 at 7:11 AM, Julian Rüth <julian.ru...@fsfe.org> wrote:
> Thanks for the feedback so far. It seems that there are pros and cons to all
> of the options.
>
> What about the following: We go with the somewhat random min(8, number of
> threads) and print a warning once if "number of threads" > 8 (telling the
> user to export SAGE_NUM_THREADS)? Note that this won't affect doctests as
> SAGE_NUM_THREADS=2 in that context.
>
> That way, we provide a good experience for the typical laptop/desktop user
> and don't risk angry emails from admins after somebody convinced them to
> install Sage on their shiny server.
>
> What do you think?
Does anything in our codebase (the sage library) use a "naked" @parallel?
sage: search_src("@parallel")
I ask because in any interactive or external code I write, I'm happy
to just be explicit and pass a parameter
to @parallel with the number of cpus I want it to use. However, if
there is code deep in Sage itself that just
uses @parallel, then this design choice we are talking about greatly
impacts how that code runs.
Looking.... there are a bunch of places in SageManifolds that use
@parallel automatically. It looks like
they explicitly set ncpus, and they even provide a cool whole new
framework for setting such defaults!
sage-8.2/src/sage/parallel$ cat parallelism.py
...
class Parallelism(Singleton, SageObject):
r"""
Singleton class for managing the number of processes used in parallel
computations involved in various fields.
EXAMPLES:
The number of processes is initialized to 1 (no parallelization) for
each field (only tensor computations are implemented at the moment)::
sage: Parallelism()
Number of processes for parallelization:
- tensor computations: 1
...
Anyway, having a framework for configuring how Sage uses multiple cpus
is a really good idea, and possibly relevant to people reading this
thread. Also, please be sure to use this framework in other code that
uses @parallel.
E.g., I long ago wrote some such code:
lfunctions/zero_sums.pyx:1339: @parallel(ncpus=NCPUS)
and of course it doesn't use this framework at all... and this code
also doesn't:
schemes/curves/zariski_vankampen.py:293:@parallel
...
@parallel
def braid_in_segment(f, x0, x1):
"""
Return the braid formed by the `y` roots of ``f`` when `x` moves
from ``x0`` to ``x1``.
...
What will it do? Is there any way to even impact how it runs?
William
>
> julian
>
> PS: I am also fine with "number of threads" as a default. But I am opposed
> to "1" as that provides a poor experience for the casual user who won't dig
> into the documentation to find out what's going on.
>
> On Monday, July 9, 2018 at 6:35:22 PM UTC+2, Julian Rüth wrote:
>>
>> Hello.
>>
>> since Sage 8.2 sage.parallel.ncpus.ncpus() returns 1 if you have no
>> environment variables such as MAKE, SAGE_NUM_THREADS, MAKEOPTS set.
>>
>> This number is used by the @parallel decorator and similar constructions
>> to determine the number of processes to run in parallel. (Unless during
>> doctests, then it's set to 2 I think.)
>>
>> The question is: What is a good default for things such as @parallel when
>> SAGE_NUM_THREADS has not been set? I think that 1 is not a good one. The
>> actual number of cores/threads on a system probably isn't either on servers
>> with lots of cores. At some point we had `min(8, number of threads)` which
>> appears reasonable to me.
>>
>> Please join the discussion at https://trac.sagemath.org/ticket/24937 :)
>>
>> julian
>
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William (http://wstein.org)
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