<hkaiser>
K-ballo: that's using bind_front, why placeholders?
<K-ballo>
further down, the _1s and _2s
<hkaiser>
ahh, funny that it works anyways
<hkaiser>
thanks
<K-ballo>
probably resolving to boost.bind globals
<K-ballo>
no longer works with 1.73, although the globals are still on by default
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<hkaiser>
ok, I'll fix it
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<hkaiser>
K-ballo: see #4581
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<weilewei>
hkaiser surprise, multi-threaded ring G algorithm seems generating correct results now, by 1) newly knowing a new parameter that can set G4 deterministic and 2) fixing broken default arguments related to thread_id and n_threads in DCA++. More verification will be followed
<hkaiser>
weilewei: nice!
<weilewei>
then using HPX to get rid of MPi_wait
<weilewei>
hkaiser yea!!
<hkaiser>
good job!
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<nikunj97>
heller1, what platform do we use for the call?
<heller1>
I don't care
<heller1>
Zoom is fine
<heller1>
Or whereby
<nikunj97>
I don't have zoom account? Can you create a link?
<weilewei>
diehlpk_work_ do you know where can I find the list of accepted workshops in SC?
<diehlpk_work_>
weilewei, On the submission form
<diehlpk_work_>
I had to login, make a new submission, and I could see the list of accepted workshops
<diehlpk_work_>
I found PAW-AMT and PMBS for my paper
<weilewei>
diehlpk_work_ thanks I see now. I didn't find one on SC webpage, but now in submission page
<diehlpk_work_>
Same here, I could nto find them on the SC page
<bita>
hkaiser, I apologize I couldn't test this: https://github.com/STEllAR-GROUP/hpx/pull/4561 the problem does not occur in windows and on docker starting from the hpx image it is not possible (or I am not aware how) to use a branch
<bita>
I'll try to test it on Rostam later
<hkaiser>
bita: sure, no worries
<heller1>
diehlpk_work_: where did you login and is our workshop accepted?
<diehlpk_work_>
heller1, Our workshop was rejected with the same old reason
<hkaiser>
please let me know if you can't access it etc
<rtohid>
hkaiser: thanks! sure.
<K-ballo>
what's phyfleaux?
<hkaiser>
ask rtohid
<diehlpk_work_>
sounds French
<rtohid>
K-ballo: in its infancy, but the goal is to analyze decorated python functions and map them to appropriate backends- including code generation, scheduling, ...
<rtohid>
for now we are focusing on nested loops that can be modeled as polyhedral, and use tiramisu to apply transformations.