Monte Carlo methods for parallel processing of diffusion equations
Massachusetts Institute of Technology. Department of Nuclear Science and Engineering.
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A Monte Carlo algorithm for solving simple linear systems using a random walk is demonstrated and analyzed. The described algorithm solves for each element in the solution vector independently. Furthermore, it is demonstrated that this algorithm is easily parallelized. To reduce error, each processor can compute data for an independent element of the solution, or part of the data for a given element for the solution, allowing for larger samples to decrease stochastic error. In addition to parallelization, it is also shown that a probabilistic chain termination can decrease the runtime of the algorithm while maintaining accuracy. Thirdly, a tighter lower bound for the required number of chains given a desired error is determined.
Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Nuclear Science and Engineering, 2013."June 2013." Cataloged from PDF version of thesis.Includes bibliographical references (page 14).
DepartmentMassachusetts Institute of Technology. Department of Nuclear Science and Engineering.; Massachusetts Institute of Technology. Department of Nuclear Science and Engineering
Massachusetts Institute of Technology
Nuclear Science and Engineering.