  A Monte Carlo fluence estimator has been designed to take advantage of the
computational power of graphical processing units (GPUs). This new estimator,
termed the volumetric-ray-casting estimator, is an extension of the
expected-value estimator. It can be used as a replacement of the track-length
estimator for the estimation of global fluence. Calculations for this estimator
are performed on the GPU while the Monte Carlo random walk is performed on the
central processing unit (CPU). This method lowers the implementation cost for
GPU acceleration of existing Monte Carlo particle transport codes as there is
little modification of the particle history logic flow. Three test problems
have been evaluated to assess the performance of the volumetric-ray-casting
estimator for neutron transport on GPU hardware in comparison to the standard
track-length estimator on CPU hardware. Evaluation of neutron transport through
air in a criticality accident scenario showed that the volumetric-ray-casting
estimator achieved 23 times the performance of the track-length estimator using
a single core CPU paired with a GPU and 15 times the performance of the
track-length estimator using an eight core CPU paired with a GPU. Simulation of
a pressurized water reactor fuel assembly showed that the performance
improvement was 6 times within the fuel and 7 times within the control rods
using an eight core CPU paired with a single GPU.
