The theoretical development of a new high speed solution for Monte Carlo radiation transport computations

Advancements in parallel and cluster computing have made many complex Monte Carlo simulations possible in the past several years. Unfortunately, cluster computers are large, expensive, and still not fast enough to make the Monte Carlo technique useful for calculations requiring a near real-time evaluation period. For Monte Carlo simulations, a small computational unit called a Field Programmable Gate Array (FPGA) is capable of bringing the power of a large cluster computer into any personal computer (PC). Because an FPGA is capable of executing Monte Carlo simulations with a high degree of parallelism, a simulation run on a large FPGA can be executed at a much higher rate than an equivalent simulation on a modern single-processor desktop PC. In this thesis, a simple radiation transport problem involving moderate energy photons incident on a three-dimensional target is discussed. By comparing the theoretical evaluation speed of this transport problem on a large FPGA to the evaluation speed of the same transport problem using standard computing techniques, it is shown that it is possible to accelerate Monte Carlo computations significantly using FPGAs. In fact, we have found that our simple photon transport test case can be evaluated in excess of 650 times faster on a large FPGA than on a 3.2 GHz Pentium-4 desktop PC running MCNP5âÂÂan acceleration factor that we predict will be largely preserved for most Monte Carlo simulations

The development of a high speed solution for the evaluation of track structure Monte Carlo electron transport problems using field programmable gate arrays

There are two principal techniques for performing Monte Carlo electron transport computations. The first, and least common, is the full track-structure method. This method individually models all physical electron interactions including elastic scatter, electron impact ionization, radiative losses and excitations. However, because of the near infinite size of electron interaction cross-sections and highly anisotropic scattering behavior, this method requires an enormous amount of computation time. Alternatively, the Condensed History (CH) method for electron transport lumps the average effects of multiple energy loss and scattering events into one single pseudo-event, or step. Because of this approximation, the CH method can be orders of magnitude faster than the trackstructure method. While the CH method is reasonably accurate in many situations, it can be inaccurate for simulations involving microscopic site sizes such as those often found in radiation biology. For radiation biology and other microdosimetry applications, a computational device called a Field Programmable Gate Array (FPGA) is capable of executing track-structure Monte Carlo electron transport simulations as fast as, or faster than a standard computer performing transport via the CH method—and, it does so with the additional accuracy and level of detail provided by the track-structure method. In this dissertation, data from FPGA based track-structure electron transport computations are presented for five test cases, ranging in complexity from simple slab-style geometries to radiation biology applications involving electrons incident on endosteal bone surface cells. Even for the most complex test case presented, an FPGA is capable of evaluating track-structure electron transport problems more than 500 times faster than a standard computer can perform the same track-structure simulation, and with comparable accuracy