JCOGIN: a programming framework for particle transport on combinatorial geometry

Domain-specific programming frameworks are usually effective to simplify the development of large-scale applications on supercomputers. This paper introduces a parallel programming framework named JCOGIN for particle transport on combinatorial geometry. JCOGIN provides a combinatorial geometry data model and a patch-based parallel computing model to manage the data distribution in parallel computing and implements the hybrid parallelism of the domain decomposition and the particle parallelism on MPI/OpenMP to overcome the bottleneck of huge memory demand and long computational time. The application programming interface of JCOGIN can support users to quickly develop their parallel particle transport applications. Based on this framework, users only need to write serial codes for large-scale numerical simulations on modern supercomputers. The parallel efficiency of applications based on JCOGIN can reach up to 80% on hundreds of thousands of CPU cores.

[1]  Jaakko Leppänen,et al.  Validation of the Serpent-ARES code sequence using the MIT BEAVRS benchmark – HFP conditions and fuel cycle 1 simulations , 2016 .

[2]  Kord Smith,et al.  Full core 3D simulation of the BEAVRS benchmark with OpenMOC , 2019 .

[3]  Bojan. Petrovic,et al.  MONTE CARLO PERFORMANCE BENCHMARK FOR DETAILED POWER DENSITY CALCULATION IN A FULL SIZE REACTOR CORE Benchmark specifications Revision 1 , 2010 .

[4]  James R. Stewart,et al.  The SIERRA Framework for Developing Advanced Parallel Mechanics Applications , 2003 .

[5]  Aiqing Zhang,et al.  A Programming Framework for Large Scale Numerical Simulations on Unstructured Mesh , 2016, 2016 IEEE 2nd International Conference on Big Data Security on Cloud (BigDataSecurity), IEEE International Conference on High Performance and Smart Computing (HPSC), and IEEE International Conference on Intelligent Data and Security (IDS).

[6]  Ho Jin Park,et al.  Real variance analysis of Monte Carlo eigenvalue calculation by McCARD for BEAVRS benchmark , 2016 .

[7]  Jeffrey C. Carver,et al.  Workshop on Software Productivity for Extreme-scale Science, January 13-14, 2014, Hilton Hotel, Rockville, MD , 2014 .

[8]  S. Incerti,et al.  Geant4 developments and applications , 2006, IEEE Transactions on Nuclear Science.

[9]  Z. Hu,et al.  Simulation of the full-core pin-model by JMCT Monte Carlo neutron-photon transport code , 2013 .

[10]  Ph Canal,et al.  The GeantV project: preparing the future of simulation , 2015 .

[11]  Zeyao Mo,et al.  Parallel algorithm and parallel programming: from specialty to generality as well as software reuse , 2016 .

[12]  Li Deng,et al.  Application of a global variance reduction method to HBR-2 benchmark , 2018 .

[13]  Mo Zeyao,et al.  An adaptive AMG preconditioning strategy for solving large-scale sparse linear systems , 2016 .

[15]  Brian van Straalen,et al.  A survey of high level frameworks in block-structured adaptive mesh refinement packages , 2014, J. Parallel Distributed Comput..

[16]  Vicent Giménez Alventosa,et al.  PenRed: An extensible and parallel Monte-Carlo framework for radiation transport based on PENELOPE , 2020, Comput. Phys. Commun..

[17]  Ma Yan,et al.  JMCT Monte Carlo Simulation Analysis of BEAVRS and SG-III Shielding , 2017 .

[18]  Kan Wang,et al.  BEAVRS full core burnup calculation in hot full power condition by RMC code , 2017 .

[19]  Xiaolin Cao,et al.  JASMIN: a parallel software infrastructure for scientific computing , 2010, Frontiers of Computer Science in China.

[20]  F.B.K. Kam,et al.  H.B. Robinson-2 pressure vessel benchmark , 1998 .

[21]  J. Sempau,et al.  PENELOPE-2006: A Code System for Monte Carlo Simulation of Electron and Photon Transport , 2009 .

[22]  李. L. Gang,et al.  Development of Monte Carlo particle transport code JMCT , 2013 .

[23]  Andrew Siegel,et al.  Monte Carlo domain decomposition for robust nuclear reactor analysis , 2014, Parallel Comput..

[24]  Dermott E. Cullen,et al.  NEW CAPABILITIES IN MERCURY: A MODERN, MONTE CARLO PARTICLE TRANSPORT CODE , 2007 .