Comparing Distributed-Memory Programming Frameworks with Radix Sort

doi:https://doi.org/10.1145/3731599.3767500

Open AccessArticle10.1145/3731599.3767500

Comparing Distributed-Memory Programming Frameworks with Radix Sort

Michael P. Ferguson,Ryan Friese,Shreyas Khandekar,Matt Drozt-2025-11-07

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TL;DRAbstract

Distributed-memory parallel processing addresses computational problems requiring significantly more memory or computational resources than can be found on one node. Software written for distributed-memory parallel processing typically uses a distributed-memory parallel programming framework to enhance productivity, scalability, and portability across supercomputers and cluster systems.

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Distributed-memory parallel processing addresses computational problems requiring significantly more memory or computational resources than can be found on one node. Software written for distributed-memory parallel processing typically uses a distributed-memory parallel programming framework to enhance productivity, scalability, and portability across supercomputers and cluster systems.

Keywords

Software portability sort Software Programming paradigm Parallel processing Computational complexity theory Software framework

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