Parallel Fission Bank Algorithms in Monte Carlo Criticality Calculations

In this work we describe a new method for parallelizing the source iterations in a Monte Carlo criticality calculation. Instead of having one global fission bank that needs to be synchronized, as is traditionally done, our method has each processor keep track of a local fission bank while still preserving reproducibility. In doing so, it is required to send only a limited set of fission bank sites between processors, thereby drastically reducing the total amount of data sent through the network. The algorithm was implemented in a simple Monte Carlo code and shown to scale up to hundreds of processors and furthermore outperforms traditional algorithms by at least two orders of magnitude in wall-clock time

The OpenMC Monte Carlo particle transport code

A new Monte Carlo code called OpenMC is currently under development at the Massachusetts Institute of Technology as a tool for simulation on high-performance computing platforms. Given that many legacy codes do not scale well on existing and future parallel computer architectures, OpenMC has been developed from scratch with a focus on high performance scalable algorithms as well as modern software design practices. The present work describes the methods used in the OpenMC code and demonstrates the performance and accuracy of the code on a variety of problems.United States. Department of Energy (DE-AC05-00OR22725

Developing fuel management capabilities based on coupled Monte Carlo depletion in support of the MIT Research Reactor (MITR) conversion

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Nuclear Science and Engineering, 2009.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student submitted PDF version of thesis.Includes bibliographical references (p. 99-101).Pursuant to a 1986 NRC ruling, the MIT Reactor (MITR) is planning on converting from the use of highly enriched uranium (HEU) to low enriched uranium (LEU) for fuel. Prior studies have shown that the MITR will be able to operate using monolithic U-Mo LEU fuel while achieving neutron fluxes close to that of an HEU core. However, to date, detailed studies on fuel management and burnup while using LEU fuel have not been performed. In this work, a code package is developed for performing detailed fuel management studies at the MITR that is easy to use and is based on state-of-the-art computational methodologies. A wrapper was written that enables fuel management operations to be modeled using MCODE, a code developed at MIT that couples MCNP to the point-depletion code ORIGEN. To explicitly model the movement of the control blades in the MITR as the core is being depleted, a criticality search algorithm was implemented to determine the critical position of the control blades at each depletion timestep. Additionally, a graphical user interface (GUI) was developed to automate the creation of model input files. The fuel management wrapper and GUI were developed in Python, with the PyQt4 extension being used for GUI-specific features. The MCODE fuel management wrapper has been shown to perform reliably based on a number of studies. An LEU equilibrium core was modeled and burned for 640 days with the fuel being moved in the same pattern every 80 days. The control blade movement and nuclide concentrations were shown to be in agreement with what one would intuitively predict. The fuel management capabilities of REBUS-PC and the MCODE fuel management wrapper were compared by modeling the same refueling scheme using an HEU core. The element power peaking factors for the two models showed remarkable agreement. Together, the fuel management wrapper and graphical user interface will help the staff at the MITR perform in-core fuel management calculations quickly and with a higher level of detail than that previously possible.by Paul K. Romano.S.M

Parallel algorithms for Monte Carlo particle transport simulation on exascale computing architectures

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Nuclear Science and Engineering, 2013.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (p. 191-199).Monte Carlo particle transport methods are being considered as a viable option for high-fidelity simulation of nuclear reactors. While Monte Carlo methods offer several potential advantages over deterministic methods, there are a number of algorithmic shortcomings that would prevent their immediate adoption for full-core analyses. In this thesis, algorithms are proposed both to ameliorate the degradation in parallal efficiency typically observed for large numbers of processors and to offer a means of decomposing large tally data that will be needed for reactor analysis. A nearest-neighbor fission bank algorithm was proposed and subsequently implemented in the OpenMC Monte Carlo code. A theoretical analysis of the communication pattern shows that the expected cost is O([square root]N) whereas traditional fission bank algorithms are O(N) at best. The algorithm was tested on two supercomputers, the Intrepid Blue Gene/P and the Titan Cray XK7, and demonstrated nearly linear parallel scaling up to 163,840 processor cores on a full-core benchmark problem. An algorithm for reducing network communication arising from tally reduction was analyzed and implemented in OpenMC. The proposed algorithm groups only particle histories on a single processor into batches for tally purposes - in doing so it prevents all network communication for tallies until the very end of the simulation. The algorithm was tested, again on a full-core benchmark, and shown to reduce network communication substantially. A model was developed to predict the impact of load imbalances on the performance of domain decomposed simulations. The analysis demonstrated that load imbalances in domain decomposed simulations arise from two distinct phenomena: non-uniform particle densities and non-uniform spatial leakage. The dominant performance penalty for domain decomposition was shown to come from these physical effects rather than insufficient network bandwidth or high latency. The model predictions were verified with measured data from simulations in OpenMC on a full-core benchmark problem. Finally, a novel algorithm for decomposing large tally data was proposed, analyzed, and implemented/tested in OpenMC. The algorithm relies on disjoint sets of compute processes and tally servers. The analysis showed that for a range of parameters relevant to LWR analysis, the tally server algorithm should perform with minimal overhead. Tests were performed on Intrepid and Titan and demonstrated that the algorithm did indeed perform well over a wide range of parameters.by Paul Kollath Romano.Ph.D

Development of a Graphical User Interface for In-Core Fuel Management Using MCODE

In the present work, a graphical user interface is developed to automate in-core fuel management using MCODE, an MCNP-ORIGEN linkage code. Data abstraction is achieved by means of five object classes that define the run, fuel assembly locations, fuel assemblies, fuel paths, and materials. The GUI and an associated fuel management wrapper were developed in Python, with the PyQt extension being used for GUI-specific features. To validate the fuel management wrapper, a model of the MIT Reactor core was used to run an equilibrium core. The results show that the wrapper performs reliably. Together, these tools will help the staff at the MITR perform in-core fuel management calculations quickly and with a higher level of detail than that previously possible

Data decomposition of Monte Carlo particle transport simulations via tally servers

An algorithm for decomposing large tally data in Monte Carlo particle transport simulations is developed, analyzed, and implemented in a continuous-energy Monte Carlo code, OpenMC. The algorithm is based on a non-overlapping decomposition of compute nodes into tracking processors and tally servers. The former are used to simulate the movement of particles through the domain while the latter continuously receive and update tally data. A performance model for this approach is developed, suggesting that, for a range of parameters relevant to LWR analysis, the tally server algorithm should perform with minimal overhead on contemporary supercomputers. An implementation of the algorithm in OpenMC is then tested on the Intrepid and Titan supercomputers, supporting the key predictions of the model over a wide range of parameters. We thus conclude that the tally server algorithm is a successful approach to circumventing classical on-node memory constraints en route to unprecedentedly detailed Monte Carlo reactor simulations.United States. Dept. of Energy. Naval Reactors Division. Rickover Fellowship Program in Nuclear EngineeringUnited States. Dept. of Energy. Office of Advanced Scientific Computing Research (Contract DE-AC02-06CH11357)United States. Dept. of Energy (Consortium for Advanced Simulation of Light Water Reactors. Contract DE-AC05-00OR22725

Improved cache performance in Monte Carlo transport calculations using energy banding

We present an energy banding algorithm for Monte Carlo (MC) neutral particle transport simulations which depend on large cross section lookup tables. In MC codes, read-only cross section data tables are accessed frequently, exhibit poor locality, and are typically too much large to fit in fast memory. Thus, performance is often limited by long latencies to RAM, or by off-node communication latencies when the data footprint is very large and must be decomposed on a distributed memory machine. The proposed energy banding algorithm allows maximal temporal reuse of data in band sizes that can flexibly accommodate different architectural features. The energy banding algorithm is general and has a number of benefits compared to the traditional approach. In the present analysis we explore its potential to achieve improvements in time-to-solution on modern cache-based architectures.United States. Department of Energy. Office of Science (Contract DE-AC02-06CH11357

Using Fractional Cascading to Accelerate Cross Section Lookups in Monte Carlo Neutron Transport Calculations

We describe and test a technique for carrying out energy grid searches in continuous-energy Monte Carlo (MC) neutron transport calculations that represents an optimal compromise between grid search performance and memory footprint. The method, based on the fractional cascading technique and referred to as the cascade grid, is tested within the OpenMC Monte Carlo code, and performance results comparing the method with existing approaches are presented for the Hoogenboom-Martin reactor benchmark. The cascade grid achieves significant speedups in calculation rate with negligible initialization overhead while not increasing the memory footprint by more than 2x.

Multi-core performance studies of a Monte Carlo neutron transport code

Performance results are presented for a multi-threaded version of the OpenMC Monte Carlo neutronics code using OpenMP in the context of nuclear reactor criticality calculations. Our main interest is production computing, and thus we limit our approach to threading strategies that both require reasonable levels of development effort and preserve the code features necessary for robust application to real-world reactor problems. Several approaches are developed and the results compared on several multi-core platforms using a popular reactor physics benchmark. A broad range of performance studies are distilled into a simple, consistent picture of the empirical performance characteristics of reactor Monte Carlo algorithms on current multi-core architectures.United States. Dept. of Energy. Office of Advanced Scientific Computing Research (Contract DEAC02-06CH11357

Progress and Status of the Openmc Monte Carlo Code

The present work describes the latest advances and progress in the development of the OpenMC Monte Carlo code, an open-source code originating from the Massachusetts Institute of Technology. First, an overview of the development workflow of OpenMC is given. Various enhancements to the code such as real-time XML input validation, state points, plotting, OpenMP threading, and coarse mesh finite difference acceleration are described.United States. Department of Energy. Naval Reactors Division (Rickover Fellowship Program in Nuclear Engineering)United States. Department of Energy (Consortium for Advanced Simulation of Light Water Reactors. Contract DE-AC05-00OR22725)United States. Department of Energy. Office of Advanced Scientific Computing Research (Contract DE-AC02-06CH11357