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A discussion meeting on examining common ground on software and computing challenges between the High-Energy, Nuclear, Neutrino and Astroparticle Physics community. A few short talks will introduce the main issues for each community, followed by time for discussion and the identification of common topics that multiple communities would like to tackle.
This meeting is organised as a splinter meeting after the main JENAS 2019 seminar and all delegates and interested parties are welcome to join.
This meeting is organised through the HEP Software Foundation.
▾ Graeme Stewart - HSF
▾ Points from the talk
• HSF created to face the computing & software challenges for HL-LHC in light of needs ramping up faster than technology
• Idea: bottom up effort, do-ocracy
▾ Foundation (no profit/funding only from host universities in terms of members time)
• Does not have funding / commercialize software, but helps members apply for funding (e.g. IRIS-HEP)
• Has grown from roadmap whitepaper to a more organized working group structure
▾ Points from Q&A
• Computing is also an interest of the HSF, we have joint yearly meetings with the WLCG and are in touch regularly
• Good synergies with nuclear physics (ALICE, FAIR), disussions on data management (DOMA) in WLCG
• All software from collaborations is open source, licensing is also important
▾ Encouraging a modular approach to software, so it is not all ready at once
• Projects that follow that idea and are rather mature: Rucio, DD4hep, ACTS [add links]
• Projects that could be useful: EM shower generation
▾ HSF does not mean to write code for the experiments, but aims to be a great help
• e.g. by making sure experiments can find and take off-the-shelf pieces that are useful for their software
• Work on approximate statistical methods in event generation may be happening in some groups, not aware of official efforts yet though
• Role of ML: significant contributions in analysis (including object identification) - simulation and reconstruction are harder
▾ Carlos Munoz Camacho - AGATA and EIC
▾ Points from the talk
• Experiments covered: AGATA, EIC
• Some unique challenges, in terms of reconstruction and physics space
▾ (Actual) real-time analysis, using streaming readout
• Difference wrt LHC real-time analysis: timescales, LHC is a few hours and the data is stored in a buffer for as long as it’s necessary for the calibration, here one wants to avoid writing raw data altogether
• A key challenge of real time analysis is fast calibration / self-calibration
▾ Rates: like LHCb, so not immense, and can think outside the box
• Exascale computing brings accelerators and that's a real challenge for software writers
• There is an EIC software group, HSF is in contact with them
▾ Points from Q&A
• Do you share code with lattice QCD calculations (main consumers of HPC)
▾ Giovanni Lamanna - ESCAPE
▾ Points from discussion
• Data lake being co-developed with HEP
• Idea of a virtual research environment, with connections to HSF
• Economy of scale: choose to use existing building blocks, rather than rederive everything
▾ Since there will be many more communities, propose a modular workflow (with containers) that different collaborations can adapt to
• Build those example workflows around science cases
• Researchers become software writers, not only data users
• Teams are more diverse, including computing scientists, physicists and data scientists (more professionals needed)
• European Open Science Cloud infrastructure can provide funding, including for people
▾ Investment in training is very important as students have diverse backgrounds (computer science, physics, data science)
• HSF could contribute to the ASTERICS school in LAPP by extending to HEP as well
• This would be a way to start collaborating straight away, HSF will email responsible from ESCAPE
▾ Chris Tunnell - Experience from Direct Detection community
▾ Points from discussion
• DD is a large but more heterogeneous community wrt HEP
▾ Nevertheless, bottom-up effort has started, community-building stage
• First identify the needs, then the solutions
• Idea of short-term, limited-scope inter-collaboration efforts - could extend beyond DD?
• DANCE workshop @ RICE: https://dance.rice.edu
▾ Paschal Coyle - KM3NeT/ANTARES
▾ Points from the talk
Data is quite managable
Simulation is very expensive, especially with large detectors (ML, GPU interesting?)
Accelerated photon transport - JUNO experiment simulations
▾ Event-like data, like HEP
• Machine learning is having a big impact
▾ Data still manageable, total of 995 TB * 3 building blocks
• Possibly the time to start thinking about archiving and opening data
• Starting to try DIRAC for MC generation / data analysis, thinking about using Grid
▾ Points from Q&A
▾ Challenge: large detector —> big simulation overhead
• Same as CTA, only a few days of data taking
• This is an issue for machine learning, as training data is limited
• Could look into accelerated photon transport from JUNO (plenary at CHEP)
▾ Plugged into a real-time alert system sensitive to supernovas
• Even in that case, event rate does not go up significantly
▾ Final discussion and outcomes
▾ Strengthen links between HSF and ESCAPE
• Opportunity for further funding through this cluster, also for recruitment
• Could raining (some urgency on this - school is in June)
▾ Software catalogs
• Many communities would benefit from a classification of useful/supported/documented software e.g. on peak finders, filtering, compression
▾ Trying a physics case: dark matter?
• The know-how exists (and it is actively building up in direct detection), we could use dark matter searches as a prototype
▾ What next
• Advertise workshops interesting
• Possibly put in an Expression Of Interest to APPEC-NuPECC-ECFA for support towards continuing this discussion