Indico is back online after maintenance on Tuesday, April 30, 2024.
Please visit Jefferson Lab Event Policies and Guidance before planning your next event: https://www.jlab.org/conference_planning.

May 8 – 12, 2023
Norfolk Waterside Marriott
US/Eastern timezone

Accelerated demonstrator of electromagnetic Particle Transport (AdePT) status and plans

May 9, 2023, 5:15 PM
15m
Hampton Roads Ballroom VI (Norfolk Waterside Marriott)

Hampton Roads Ballroom VI

Norfolk Waterside Marriott

235 East Main Street Norfolk, VA 23510
Oral Track 3 - Offline Computing Track 3 - Offline Computing

Speaker

Gheata, Andrei (CERN)

Description

Motivated by the need to have large Monte Carlo data statistics to be able to perform the physics analysis for the coming runs of HEP experiments, particularly for HL-LHC, there are a number of efforts exploring different avenues for speeding up particle transport simulation. In particular, one of the possibilities is to re-implement the simulation code to run efficiently on GPUs. This could allow future large Monte Carlo productions to utilise GPU resources, as well as traditional CPUs.

We present the status and plans of the Accelerated demonstrator of electromagnetic Particle Transport (AdePT) R&D project. The goal of this development is to provide a realistic demonstrator of electromagnetic calorimeter simulation on GPUs, with the geometry as complex as the LHC experiments’ detectors, complete electromagnetic physics, and all the required energy scoring infrastructure. We will discuss the GPU-specific workflow of this prototype, and describe the implementation of its different components.
We will also look into the aspect of integrating the new GPU-based simulation module with the existing CPU-based ones, namely the interfacing with the Geant4 toolkit. We will show a possible scenario of running the existing Geant4 simulations with their calorimeter part delegated to AdePT on GPUs.
We will present the performance both in the standalone mode as well as when integrated into Geant4, discuss the identified bottlenecks and propose a plan of possible further optimizations.

Consider for long presentation No

Primary authors

Presentation materials