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Many scientific high performance codes that simulate e.g. black holes,coastal waves, climate and weather, etc. rely on block-structured meshes anduse finite differencing methods to iteratively solve the appropriate systems ofdifferential equations. In this paper we investigate implementations of anextremely simple simulation of this type using various programming systems andlanguages. We focus on a shared memory, parallelized algorithm that simulates a1D heat diffusion using asynchronous queues for the ghost zone exchange. Wediscuss the advantages of the various platforms and explore the performance ofthis 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 platformswere C++, Rust, Chapel, Charm++, and HPX.

Benchmarking the Parallel 1D Heat Equation Solver in Chapel, Charm++, C++, HPX, Go, Julia, Python, Rust, Swift, and Java