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A current trend for partitioning huge (hyper)graphs using low computational resources are streaming algorithms. In this work, we propose FREIGHT: a Fast stREamInG Hypergraph parTitioning algorithm which is an adaptation of the widely-known graph-based algorithm Fennel. By using an efficient data structure, we make the overall running of FREIGHT linearly dependent on the pin-count of the hypergraph and the memory consumption linearly dependent on the numbers of nets and blocks. The results of our extensive experimentation showcase the promising performance of FREIGHT as a highly efficient and effective solution for streaming hypergraph partitioning. Our algorithm demonstrates competitive running time with the Hashing algorithm, with a geometric mean runtime within a factor of four compared to the Hashing algorithm. Significantly, our findings highlight the superiority of FREIGHT over all existing (buffered) streaming algorithms and even the in-memory algorithm HYPE, with respect to both cut-net and connectivity measures. This indicates that our proposed algorithm is a promising hypergraph partitioning tool to tackle the challenge posed by large-scale and dynamic data processing.<\/jats:p>","DOI":"10.1007\/s00453-024-01291-8","type":"journal-article","created":{"date-parts":[[2025,1,3]],"date-time":"2025-01-03T21:45:52Z","timestamp":1735940752000},"page":"405-428","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["FREIGHT: Fast Streaming Hypergraph Partitioning"],"prefix":"10.1007","volume":"87","author":[{"given":"Kamal","family":"Eyubov","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marcelo","family":"Fonseca Faraj","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christian","family":"Schulz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,1,3]]},"reference":[{"issue":"4","key":"1291_CR1","doi-asserted-by":"publisher","first-page":"313","DOI":"10.1038\/s41567-019-0459-y","volume":"15","author":"R Lambiotte","year":"2019","unstructured":"Lambiotte, R., Rosvall, M., Scholtes, I.: From networks to optimal higher-order models of complex systems. 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