Event reconstruction is the process of interpreting the electronic signals produced in a high-energy physics (HEP) experiment’s detector to determine what original particles passed through the detector and their characteristics.
The goal of the 3-year SciDAC project, HEP Event Reconstruction with Cutting Edge Computing Architectures, is to boost the utilization of new computing architectures in high-energy physics (HEP) event reconstruction, particularly, for LHC experiments and neutrino experiments using Liquid Argon Time-Projection Chamber (LArTPC) detectors.
The leading institution, Fermilab, led by Principal Investigator Giuseppe Cerati, nd the University of Oregon, led by Principal Investigator Boyana Norris, will collaborate to identify key algorithms in the experiments’ reconstruction workflows and optimize them for execution on parallel architectures. The choice of the algorithms will be based on their importance for the physics outcome of the experiment and on their leading contribution in terms of computing time, such as the track reconstruction for collision experiments. With the use of advanced profiling tools and development techniques, including autotuning, the throughput of the algorithms on the leading parallel architectures will be maximized and portable implementations for usage at supercomputers and with heterogenous platforms will be explored. The optimized version will finally be deployed in the experiments’ reconstruction software. This project will give a key input to the process of defining the computing needs for the reconstruction software of the next-generation HEP experiment such as the High Luminosity Large Hadron Collider (HL-LHC) and Deep Underground Neutrino Experiment (DUNE).