{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2020:7QFH7WSHVNZTED2452VWMKSCKO","short_pith_number":"pith:7QFH7WSH","schema_version":"1.0","canonical_sha256":"fc0a7fda47ab73320f5ceeab662a425390cb4f41f8b61852cd37440a45e907ac","source":{"kind":"arxiv","id":"2001.05234","version":3},"attestation_state":"computed","paper":{"title":"GPU acceleration of CaNS for massively-parallel direct numerical simulations of canonical fluid flows","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CE","physics.comp-ph"],"primary_cat":"physics.flu-dyn","authors_text":"Everett Phillips, Luca Brandt, Massimiliano Fatica, Pedro Costa","submitted_at":"2020-01-15T11:06:25Z","abstract_excerpt":"This work presents the GPU acceleration of the open-source code CaNS for very fast massively-parallel simulations of canonical fluid flows. The distinct feature of the many-CPU Navier-Stokes solver in CaNS is its fast direct solver for the second-order finite-difference Poisson equation, based on the method of eigenfunction expansions. The solver implements all the boundary conditions valid for this type of problems in a unified framework. Here, we extend the solver for GPU-accelerated clusters using CUDA Fortran. The porting makes extensive use of CUF kernels and has been greatly simplified b"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2001.05234","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"physics.flu-dyn","submitted_at":"2020-01-15T11:06:25Z","cross_cats_sorted":["cs.CE","physics.comp-ph"],"title_canon_sha256":"99e0d5ced8c4999005cb7ab420cad56c5d34411a0ac83c6b43408a0996aa4594","abstract_canon_sha256":"ea72de3d727c80eb051fb6166222c5a670841bb9e7412249e6425bc3df5e9e45"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:14:40.910599Z","signature_b64":"DWWQGZkPW0SIpD9Klab/nlTe9lk+rMn6AfLRlBcxtuD3Ytk1F3w1Cxa1jvZ+9nq9R5Mq/+nvUpRkoBfUsWvUDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fc0a7fda47ab73320f5ceeab662a425390cb4f41f8b61852cd37440a45e907ac","last_reissued_at":"2026-07-05T02:14:40.910149Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:14:40.910149Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"GPU acceleration of CaNS for massively-parallel direct numerical simulations of canonical fluid flows","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CE","physics.comp-ph"],"primary_cat":"physics.flu-dyn","authors_text":"Everett Phillips, Luca Brandt, Massimiliano Fatica, Pedro Costa","submitted_at":"2020-01-15T11:06:25Z","abstract_excerpt":"This work presents the GPU acceleration of the open-source code CaNS for very fast massively-parallel simulations of canonical fluid flows. The distinct feature of the many-CPU Navier-Stokes solver in CaNS is its fast direct solver for the second-order finite-difference Poisson equation, based on the method of eigenfunction expansions. The solver implements all the boundary conditions valid for this type of problems in a unified framework. Here, we extend the solver for GPU-accelerated clusters using CUDA Fortran. The porting makes extensive use of CUF kernels and has been greatly simplified b"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2001.05234","kind":"arxiv","version":3},"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/2001.05234/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2001.05234","created_at":"2026-07-05T02:14:40.910207+00:00"},{"alias_kind":"arxiv_version","alias_value":"2001.05234v3","created_at":"2026-07-05T02:14:40.910207+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2001.05234","created_at":"2026-07-05T02:14:40.910207+00:00"},{"alias_kind":"pith_short_12","alias_value":"7QFH7WSHVNZT","created_at":"2026-07-05T02:14:40.910207+00:00"},{"alias_kind":"pith_short_16","alias_value":"7QFH7WSHVNZTED24","created_at":"2026-07-05T02:14:40.910207+00:00"},{"alias_kind":"pith_short_8","alias_value":"7QFH7WSH","created_at":"2026-07-05T02:14:40.910207+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/7QFH7WSHVNZTED2452VWMKSCKO","json":"https://pith.science/pith/7QFH7WSHVNZTED2452VWMKSCKO.json","graph_json":"https://pith.science/api/pith-number/7QFH7WSHVNZTED2452VWMKSCKO/graph.json","events_json":"https://pith.science/api/pith-number/7QFH7WSHVNZTED2452VWMKSCKO/events.json","paper":"https://pith.science/paper/7QFH7WSH"},"agent_actions":{"view_html":"https://pith.science/pith/7QFH7WSHVNZTED2452VWMKSCKO","download_json":"https://pith.science/pith/7QFH7WSHVNZTED2452VWMKSCKO.json","view_paper":"https://pith.science/paper/7QFH7WSH","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2001.05234&json=true","fetch_graph":"https://pith.science/api/pith-number/7QFH7WSHVNZTED2452VWMKSCKO/graph.json","fetch_events":"https://pith.science/api/pith-number/7QFH7WSHVNZTED2452VWMKSCKO/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/7QFH7WSHVNZTED2452VWMKSCKO/action/timestamp_anchor","attest_storage":"https://pith.science/pith/7QFH7WSHVNZTED2452VWMKSCKO/action/storage_attestation","attest_author":"https://pith.science/pith/7QFH7WSHVNZTED2452VWMKSCKO/action/author_attestation","sign_citation":"https://pith.science/pith/7QFH7WSHVNZTED2452VWMKSCKO/action/citation_signature","submit_replication":"https://pith.science/pith/7QFH7WSHVNZTED2452VWMKSCKO/action/replication_record"}},"created_at":"2026-07-05T02:14:40.910207+00:00","updated_at":"2026-07-05T02:14:40.910207+00:00"}