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Computer Science > Distributed, Parallel, and Cluster Computing

arXiv:2307.01117 (cs)
[Submitted on 18 May 2023 (v1), last revised 10 Jul 2023 (this version, v3)]

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

Authors:Patrick Diehl, Steven R. Brandt, Max Morris, Nikunj Gupta, Hartmut Kaiser
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Abstract: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.
Subjects: Distributed, Parallel, and Cluster Computing (cs.DC)
Cite as: arXiv:2307.01117 [cs.DC]
  (or arXiv:2307.01117v3 [cs.DC] for this version)
  https://doi.org/10.48550/arXiv.2307.01117
Related DOI: https://doi.org/10.1007/978-3-031-48803-0_11

Submission history

From: Patrick Diehl [view email]
[v1] Thu, 18 May 2023 14:00:23 UTC (68 KB)
[v2] Tue, 4 Jul 2023 02:07:34 UTC (69 KB)
[v3] Mon, 10 Jul 2023 17:06:26 UTC (69 KB)
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