The GeantV project: preparing the future of simulation

Abstract

Abstract. Detector simulation is consuming at least half of the HEP computing cycles, and even so, experiments have to take hard decisions on what to simulate, as their needs greatly surpass the availability of computing resources. New experiments still in the design phase such as FCC, CLIC and ILC as well as upgraded versions of the existing LHC detectors will push further the simulation requirements. Since the increase in computing resources is not likely to keep pace with our needs, it is therefore necessary to explore innovative ways of speeding up simulation in order to sustain the progress of High Energy Physics. The GeantV project aims at developing a high performance detector simulation system integrating fast and full simulation that can be ported on different computing architectures, including CPU accelerators. After more than two years of R&D the project has produced a prototype capable of transporting particles in complex geometries exploiting micro-parallelism, SIMD and multithreading. Portability is obtained via C++ template techniques that allow the development of machineindependent computational kernels. A set of tables derived from Geant4 for cross sections and final states provides a realistic shower development and, having been ported into a Geant4 physics list, can be used as a basis for a direct performance comparison.

Opticks : GPU Optical Photon Simulation for Particle Physics using NVIDIA® OptiX™

“…The GeantV [17] (Geant-Vector) project aims to develop an all-particle transport simulation package that is several times faster than Geant4. The principal approach investigated is the application of SIMD operations across vectors of multiple tracks collected from multiple events according to locality criteria, requiring development of vectorised geometry algorithms.…”

Recent progress with the top to bottom approach to vectorization in GeantV

“…Particle transport simulation represent a very demanding HEP application having many non-SIMD friendly features like: sparse memory access over large data structures, deep embedded conditionals branching to a high number of algorithms per data unit (track). While exploring SIMD/SIMT optimization techniques in the context of GeantV R&D [1], many of our results can be extrapolated to other similar HEP workflows, including some areas of reconstruction or analysis.…”

Electromagnetic physics vectorization in the GeantV transport framework

“…The increase in the integrated luminosity, expected in the next decade of the future LHC runs (HL-LHC), and the consequent increase in the amount of experimental data to be analyzed, implies the need to simulate larger and more accurate samples to avoid that the systematic errors due to the simulations will become dominant. The GeantV R&D activity [1,2] is underway with the goal of speeding up the detector simulation by exploiting modern computing architecture platforms, in order to bring the HEP community a step forward towards accomplishing the goals posed by the compelling future physics programmes. The project investigates potential computational benefits of using a multiple track transportation approach instead of the classical single particle transportation flow.…”