{"paper":{"title":"High-Level Big Integer Arithmetic in Futhark for GPUs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DC","cs.PL"],"primary_cat":"cs.SC","authors_text":"Cosmin E. Oancea, Stephen M. Watt","submitted_at":"2026-07-30T23:37:20Z","abstract_excerpt":"We report on GPU implementations of block-level addition, subtraction, multiplication and division for midsize integers, with operands of $2^{15}$ to $2^{19}$ bits using the high-level functional language Futhark. Comparing with hand-written C++/CUDA versions and CGBN, we identify which functional constructs compile well, where memory placement and sequentialization are effective, and what compiler support is needed. The results show that high-level code can express the algorithms compactly while approaching competitive performance after certain compiler improvements. In particular, we find th"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.28897","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2607.28897/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}