The Implicit Monte Carlo (IMC) method has been a standard method for thermal radiative transfer for the past 40 years. In this time, the hydrodynamics methods that are coupled to IMC have evolved and improved, as have the supercomputers used to run large simulations with IMC. Several modern hydrodynamics methods use unstructured non-orthogonal meshes and high-order spatial discretizations. The IMC method has been used primarily with simple Cartesian meshes and always has a first order spatial discretization. Supercomputers are now made up of compute nodes that have a large number of cores. Current IMC parallel methods have significant problems with load imbalance. To utilize many core systems, algorithms must move beyond simple spatial decomposition parallel algorithms. To make IMC better suited for large scale multiphysics simulations in high energy density physics, new spatial discretizations and parallel strategies are needed. Several modifications are made to the IMC method to facilitate running on node-centered, unstructured tetrahedral meshes. These modifications produce results that converge to the expected solution under mesh refinement. A new finite element IMC method is also explored on these meshes, which offer a simulation runtime benefit but does not perform correctly in the diffusion limit. A parallel algorithm that utilizes on-node parallelism and respects memory hierarchies is studied. This method scales almost linearly when using physical cores on a node and benefits from multiple threads per core. A multicompute node algorithm for domain decomposed IMC that passes mesh data instead of particles is explored as a means to solve load balance issues. This method scales better than the particle passing method on highly scattering problems with short time steps
