  Many scientific high performance codes that simulate e.g. black holes,
coastal waves, climate and weather, etc. rely on block-structured meshes and
use finite differencing methods to iteratively solve the appropriate systems of
differential equations. In this paper we investigate implementations of an
extremely simple simulation of this type using various programming systems and
languages. We focus on a shared memory, parallelized algorithm that simulates a
1D heat diffusion using asynchronous queues for the ghost zone exchange. We
discuss the advantages of the various platforms and explore the performance of
this model code on different computing architectures: Intel, AMD, and ARM64FX.
As a result, Python was the slowest of the set we compared. Java, Go, Swift,
and Julia were the intermediate performers. The higher performing platforms
were C++, Rust, Chapel, Charm++, and HPX.
