reconstruction_benchmarks issueshttps://eicweb.phy.anl.gov/EIC/benchmarks/reconstruction_benchmarks/-/issues2021-10-06T22:32:04Zhttps://eicweb.phy.anl.gov/EIC/benchmarks/reconstruction_benchmarks/-/issues/75Use mcparticles instead of mcparticles22021-10-06T22:32:04ZSylvester JoostenUse mcparticles instead of mcparticles2No need for the MCCopier anymore with recent versions of Juggler, better to just propagate the input structure.No need for the MCCopier anymore with recent versions of Juggler, better to just propagate the input structure.https://eicweb.phy.anl.gov/EIC/benchmarks/reconstruction_benchmarks/-/issues/65Python anti-pattern in benchmark CI2023-09-21T20:50:49ZWhitney ArmstrongPython anti-pattern in benchmark CIFor many reasons, we want the benchmark `config.yml` to be a simple bash script. Using python here is a bit heavy handed and out of place.
For example here:
https://eicweb.phy.anl.gov/EIC/benchmarks/reconstruction_benchmarks/-/blob/mast...For many reasons, we want the benchmark `config.yml` to be a simple bash script. Using python here is a bit heavy handed and out of place.
For example here:
https://eicweb.phy.anl.gov/EIC/benchmarks/reconstruction_benchmarks/-/blob/master/benchmarks/tracking/config.yml#L29
This just repeats the bash script.https://eicweb.phy.anl.gov/EIC/benchmarks/reconstruction_benchmarks/-/issues/31HCal clustering benchmark2021-08-24T03:17:13ZChao PengHCal clustering benchmarkCreate a working clustering benchmark for HCal.
There probably needs to be proper energy reconstruction before this including compensation.Create a working clustering benchmark for HCal.
There probably needs to be proper energy reconstruction before this including compensation.Miguel ArratiaMiguel Arratiahttps://eicweb.phy.anl.gov/EIC/benchmarks/reconstruction_benchmarks/-/issues/4Triggering large simulations2021-10-06T23:52:35ZWhitney ArmstrongTriggering large simulationsHow do we trigger these computing and storage heavy jobs?How do we trigger these computing and storage heavy jobs?Full simulation data flow