Domain Decomposition for Next-Generation Monte Carlo Transport Code TRIPOLI-5 H/F

Domain Decomposition for Next-Generation Monte Carlo Transport Code TRIPOLI-5 H/F

IRSN has started, in collaboration with CEA, the development of the new Monte Carlo particle transport code TRIPOLI-5, for the French nuclear industry and for its own safety needs. Monte Carlo simulation is the “golden standard” for neutron transport simulations.
The goal of this new generation code is to achieve multi-physics calculations coupling the transport equation solver for the neutron density, thermal and thermohydraulic solvers, as well as a Bateman solver for the isotopic evolution of the nuclear fuel. These calculations, still unfeasible a few years ago, can nowadays be in our reach thanks to the dramatic increase in computing power. This however involves new challenges in order to overcome the issues related to the memory burden induced by the huge number of temperature and tallies that are required in multi-physics simulations.
The post-doctoral work will explore novel strategies aimed at considerably reducing memory occupation and thus making viable these simulations.

Proposed work

From the above discussion, we conclude that Monte Carlo burnup calculations are actually memory-bound, and the solution to this limitation lies in some sort of Domain Decomposition in order to distribute the memory requirements of a single simulation over several compute nodes. The problem of domain decomposition does not present the same challenges nor the same approaches for deterministic methods and for Monte-Carlo simulations. A number of domain-decomposition methods adapted to neutron transport criticality calculations have been suggested in the literature, and a few codes, both production and research type, have tested some implementations.
A first bibliographic step of the work will allow to collect the ensemble of the already proposed methods and to perform a first analysis of advantages and disadvantages. Out of this analysis two competing methods will be proposed for actual implementation in the TRIPOLI-5 code.
These implementations will need to work smoothly with the multi-level parallelism already defined in TRIPOLI-5: shared-memory, distributed-memory and independent simulations. Another important point is that TRIPOLI-5 is supposed to work with both CPU and GPU architecture, and consequently with history-based and event-based algorithms. The point in choosing two algorithms is to ensure that the architecture of the implementations respect the founding principle of T5, that the code must be able to support multiple algorithms for similar functionalities.
Performances will be tested for several problems of varying scale and assessed for the two hardware targets: CPU and GPU.
The work will be proposed for publication in a peer-reviewed journal.

Scientific goals
The proposed work fills a gap in the TRIPOLI-5 development plan. The critical problem of memory needs in full core Monte-Carlo detailed burnup simulations is nowadays the limiting factor in actual calculations. Domain decomposition methods should be used with parsimony, but some systems cannot be simulated without it. Some teams around the world have been able to make headways on the subject, and we hope to be able to build and improve upon those success.

Job description
The IRSN Neutronics Laboratory has a long experience of Monte-Carlo neutron transport code development through the criticality code MORET, matched by the also long experience of CEA with the code TRIPOLI. The people who will supervise the work cumulate many years of R&D in Monte-Carlo methods, as attested by the number of publications in the field.
Work will be performed in collaboration with the TRIPOLI-5 team, composed of a number of developers with advanced skills in physics, mathematics, and computer science, coming from both IRSN and CEA.

Computer clusters

The candidate will have access to his own workstation plus the local cluster Farux at IRSN plus TGCC HPC resources for both CPUs and GPUs.

PhD in engineering or applied mathematics, especially in the field of numerical simulations and Monte Carlo methods