Speakers
Description
Gaudi is a common software framework underlying event processing in multiple experiments like ATLAS, LHCb and FCC. In addition, the simulation framework Gaussino (used by LHCb and FCC) is another user of Gaudi. As machine learning becomes increasingly central to real-time data processing, simulation and physics analysis, integrating diverse ML software stacks into Gaudi in a sustainable and reproducible way is a key challenge. Multiple experiment-specific implementations already exist of interfaces to both external and internal inference libraries, but are either partially duplicative or cover different ground. Therefore the goal is to have a unified interface such that all experiments gain in the developments on this front and reduce the maintenance burden, taking into account the various heterogeneous computing setups across experiments.
References:
for ATLAS (https://indico.cern.ch/event/1565886/#7-ml-inference-in-atlas)
for LHCb (https://indico.cern.ch/event/1565886/#5-ml-inference-in-lhcb)
CERN group/ Experiment
LHCb
| Working area | Area 5: Infrastructure for AI Deployment |
|---|---|
| If Other, please specify | Area 2 |
| Project goals | Factorize ML inference interfaces from project specific stacks to Gaudi. Improve maintainability and share development on ML inference infrastructure across experiments. |
| Timeline | 1 year |
| Available person power | 0.1 FTE |
| Additional person power request | 1-2 FTE |
| Is this an already ongoing activity? | No |
| Indicative hardware resources needs | Existing infrastructure sufficient (e.g. within LHCb) |