This paper highlights on-going research to effectively utilize a commercially available spatially reconfigurable platform and the OpenCL framework to improve the run-time performance and reduce the overall energy consumption of an existing 2.5D Electrostatic Particle-in-Cell type plasma simulation. This problem is constrained by the finite internal FPGA resources and the performance mandate that all main OpenCL kernels for this application reside in a single FPGA image. The paper focuses on solving the particle-to-grid space interpolation phase of the simulation because of its inherent nondeterministic global memory access pattern. The implementation that is presented adheres closely to the original CPU-based model while employing local memory, task level pipelining, and replication of kernel resources to provide a much more deterministic and coalesced access pattern. The overall simulation has been shown to have an approximately 2.5-fold improvement in performance and a eight-fold improvement in energy consumption over the life of the simulation when compared to the reference single core CPU implementation.