Parallelized JUNO simulation software based on SNiPER

Abstract

The Jiangmen Underground Neutrino Observatory (JUNO) is a neutrino experiment to determine the neutrino mass hierarchy. It has a central detector used for neutrino detection, which consists of a spherical acrylic vessel containing a 20 kt liquid scintillator (LS) and about 18,000 20-inch photomultiplier tubes (PMTs) to collect light from LS. Around the central detector, there is a water pool to provide shielding from background radioactivity. The outer water pool is also equipped with about 2000 PMTs to measure cosmic ray muons by detecting Cherenkov light.As one of the important parts in JUNO offline software, the serial simulation framework is developed based on SNiPER. It manages physics generator, detector simulation, event mixing and digitization. However, Geant4 based detector simulation of such a large detector is time-consuming and challenging. It is necessary to take full advantages of parallel computing to speed up simulation. Starting from version 10.0, Geant4 supports event-level parallelism. Even though this is based on pthread, it can be extended with other libraries such as Intel TBB and MPI. Therefore it is possible to parallelize JUNO simulation framework by integrating Geant4 and SNiPER.In this paper, our progress in developing parallelized simulation software is presented. The SNiPER framework can run in sequential mode, Intel TBB mode or other modes. The SNiPER task component is in charge of the event loop, which is like a simplified application manager. Two types of tasks are introduced in the simulation framework, one is a global task and another is a worker task. The global task will run only once to initialize detector geometry and physics processes before any other tasks spawned. Later it is accessed by other tasks passively. The worker tasks will be spawned after the global task is done. In each worker task, a Geant4 run manager is invoked to do the real simulation. In this way the simulation framework and the underlying TBB have been decoupled. Finally, the software performance of parallelized JUNO simulation software is also presented.