Paul K. Romano

Data decomposition of Monte Carlo particle transport simulations via tally servers

United States. Dept. of Energy. Naval Reactors Division. Rickover Fellowship Program in Nuclear Engineering

Parallel Fission Bank Algorithms in Monte Carlo Criticality Calculations

Abstract 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.

Improved cache performance in Monte Carlo transport calculations using energy banding

Abstract 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.

Optimal Run Strategies in Monte Carlo Iterated Fission Source Simulations

Abstract The method of successive generations used in Monte Carlo simulations of nuclear reactor models is known to suffer from intergenerational correlation between the spatial locations of fission sites. One consequence of the spatial correlation is that the convergence rate of the variance of the mean for a tally becomes worse than O(N–1). In this work, we consider how the true variance can be minimized given a total amount of work available as a function of the number of source particles per generation, the number of active/discarded generations, and the number of independent simulations. We demonstrate through both analysis and simulation that under certain conditions the solution time for highly correlated reactor problems may be significantly reduced either by running an ensemble of multiple independent simulations or simply by increasing the generation size to the extent that it is practical. However, if too many simulations or too large a generation size is used, the large fraction of source particles discarded can result in an increase in variance. We also show that there is a strong incentive to reduce the number of generations discarded through some source convergence acceleration technique. Furthermore, we discuss the efficient execution of large simulations on a parallel computer; we argue that several practical considerations favor using an ensemble of independent simulations over a single simulation with very large generation size.

An algorithm for generating random variates from the Madland-Nix fission energy spectrum

Abstract An algorithm for generating random variates from the Madland–Nix fission energy spectrum assuming a constant compound nucleus cross section is given based on physics considerations. A program was written to generate variates using the algorithm developed, and it was shown that the generated variates match the probability density function. This algorithm can be used by Monte Carlo particle transport codes to sample secondary energies for neutrons born from fission when the underlying data is given as parameters to a Madland–Nix energy spectrum.