  The use of Euler-Lagrange methods on unstructured grids extends their
application area to more versatile setups. However, the lack of a regular
topology limits the scalability of distributed parallel methods, especially for
routines that perform a physical search in space. One of the most prominent
slowdowns is the search for halo elements in physical space for the purpose of
runtime communication avoidance. In this work, we present a new
communication-free halo element search algorithm utilizing the MPI-3 shared
memory model. This novel method eliminates the severe performance bottleneck of
many-to-many communication during initialization compared to the distributed
parallelization approach and extends the possible applications beyond those
achievable with the previous approach. Building on these data structures, we
then present methods for efficient particle emission, scalable deposition
schemes for particle-field coupling, and latency hiding approaches. The scaling
performance of the proposed algorithms is validated through plasma dynamics
simulations of an open-source framework on a massively parallel system,
demonstrating an efficiency of up to 80% on 131000 cores.
