Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Workplan (December 2022) towards a first alpha release #576

Closed
valassi opened this issue Dec 18, 2022 · 2 comments
Closed

Workplan (December 2022) towards a first alpha release #576

valassi opened this issue Dec 18, 2022 · 2 comments

Comments

@valassi
Copy link
Member

valassi commented Dec 18, 2022

I have now completed the random choice of helicity #403 and color #402, which means that the cudacpp version is now functionally complete (at least for the simple processes we tested...).

I am listing here my understanding of what we still miss towards a first alpha release for the experiments

  1. (For Olivier) Check that the color numbering used in coloramps.inc (and copied as-is in coloramps.h) is the correct one. This is needed even if we give to the experiments some pre-generated gridpacks rather than a code generation framework.

  2. Backport to mg5amcnlo all code generation patches that are presently in madgraph4gpu. This includes amongst other things:

  1. Clean up the build and runtime environment and options so that the experiments can use this out of the box. The aim (assuming point 2 is also done) is that you run a "launch" command from the MG5aMC prompt and everything works. This includes (possibly non-exhaustive list).
  • as suggested by Olivier, make sure that the madevent input files have the same format as they have always had: this means removing the two first extra arguments I added, for Fortran/Cudacpp/BothDebug and for VECSIZE_MEMMAX... a quick and dirty workaround may be to use environment variables instead
  • clean up the executable names and define a mechanism to choose one: now I have madevent, cmadevent_cudacpp, gmadevent_cudacpp, we need a mechanism to choose one
  • similarly, define mechanisms for which build to use (float/double, avx/avx512, etc)... we now have environment variables (or make variables) for this, this could be ok
  • when the points above are done, in particular the madevent input files, these software changes must be backported to code generation (in my scripts and - point 2 - in mg5amcnlo upstream)
  1. Cross check what we are doing with parameter choices. Keep a parameter card to read at runtime, or use the uopstream mg5amcnlo mechanism to transform the parameter card into code that must be built? Again, once this is sorted out, it must be backported to code generation in my scripts and/or better (point 2) upstream

  2. TEST! As mentioned above, we should be able to just "launch" a MG production from the existing infrastructure, i.e. no change in user interface for the experiments. If we already manage to do this for one of our current processes like ggtt, this is great. Check that the results (cross sectiond and LHE files) are the same in Firtran and cudacpp. This will require some tweaking of event numbers, esepcially in cuda. This test should, in particular, include the autoamtic running of madevent in the different integration channels, the creation of G subdirectories, the launching of a web browser with autoupdated results etc.

  3. New processes. Until point 5 above we can even just use gg to tt. We need more things including

  • make sure the whole infrastructure works with protons and pdf, eg pp to tt
  • check also processes with more than one P1 subdirectory
  • if needed, check processes with nprocesses>1 inside the code
  • try the susy processes suggested by ATLAS and CMS... these are BSM processes and code generation may have other surprises

Comments welcome!
Andrea

@valassi
Copy link
Member Author

valassi commented Mar 29, 2023

Note: one large and essential part of point 3 (actually, it comes before point 3 and even before point 2) is the need to make all process directories relocatable (ie it must be possible to build them standalone outide madgraph4gpu), in particular see the tests and common random numbers

@valassi
Copy link
Member Author

valassi commented May 26, 2023

I have created an updated workplan #671, mentioning an dupfdaing most issues above - this issue #576 can be closed

@valassi valassi closed this as completed May 26, 2023
@valassi valassi unpinned this issue May 26, 2023
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

1 participant