{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:WF7X5RZGA5NKX7OINSBJSNOLRP","short_pith_number":"pith:WF7X5RZG","schema_version":"1.0","canonical_sha256":"b17f7ec726075aabfdc86c829935cb8be5492ad31c2dd50967fc4e6173da1a50","source":{"kind":"arxiv","id":"2604.11139","version":2},"attestation_state":"computed","paper":{"title":"GPU acceleration of plane-wave density functional theory calculations in Abinit","license":"http://creativecommons.org/licenses/by/4.0/","headline":"Abinit achieves GPU speedups for plane-wave DFT by revising the Kohn-Sham iterative diagonalizer.","cross_cats":[],"primary_cat":"cond-mat.mtrl-sci","authors_text":"Ioanna-Maria Lygatsika, Lucas Baguet, Marc Sarraute, Marc Torrent, Pierre Kestener","submitted_at":"2026-04-13T07:54:17Z","abstract_excerpt":"We report on the GPU port of the Abinit high-performance simulation code for plane-wave DFT calculations. Large-scale electronic structure calculations require computing the electronic wave function by solving the Kohn-Sham equations discretized over a large number of plane waves. Porting such calculations to GPU nodes relies not only on extensive usage of vendor libraries from a development perspective, but also on algorithmic revisions of the iterative diagonalization procedure in the resolution of the Kohn-Sham equations to identify GPU-efficient mathematical operations (linear algebra, FFT"},"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":"2604.11139","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cond-mat.mtrl-sci","submitted_at":"2026-04-13T07:54:17Z","cross_cats_sorted":[],"title_canon_sha256":"36353f10c2239fb738dcfc693699eaf794d793fd5919ff9fee42a47f421b47bd","abstract_canon_sha256":"022d5ab9ada1f0a8e40af2c20448ead0d7d26cdee3c1eeb13c35b661e332efb0"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-28T02:04:47.575584Z","signature_b64":"FCQHYTvEOyZJ6OsVea7zyB85dqX7RnDZ2zzu3qgQUZFXb3QHVLYT+kioMGJ6uI8gBxOViMbL81xBHZWmEXPKCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b17f7ec726075aabfdc86c829935cb8be5492ad31c2dd50967fc4e6173da1a50","last_reissued_at":"2026-05-28T02:04:47.575082Z","signature_status":"signed_v1","first_computed_at":"2026-05-28T02:04:47.575082Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"GPU acceleration of plane-wave density functional theory calculations in Abinit","license":"http://creativecommons.org/licenses/by/4.0/","headline":"Abinit achieves GPU speedups for plane-wave DFT by revising the Kohn-Sham iterative diagonalizer.","cross_cats":[],"primary_cat":"cond-mat.mtrl-sci","authors_text":"Ioanna-Maria Lygatsika, Lucas Baguet, Marc Sarraute, Marc Torrent, Pierre Kestener","submitted_at":"2026-04-13T07:54:17Z","abstract_excerpt":"We report on the GPU port of the Abinit high-performance simulation code for plane-wave DFT calculations. Large-scale electronic structure calculations require computing the electronic wave function by solving the Kohn-Sham equations discretized over a large number of plane waves. Porting such calculations to GPU nodes relies not only on extensive usage of vendor libraries from a development perspective, but also on algorithmic revisions of the iterative diagonalization procedure in the resolution of the Kohn-Sham equations to identify GPU-efficient mathematical operations (linear algebra, FFT"},"claims":{"count":4,"items":[{"kind":"strongest_claim","text":"The Abinit implementation on multi-GPU architectures provides detailed performance results to compare CPU nodes versus heterogeneous CPU-GPU nodes, with particular attention given to the comparison of LOBPCG and Chebyshev polynomial filtering in terms of their GPU efficiency.","source":"verdict.strongest_claim","status":"machine_extracted","claim_id":"C1","attestation":"unclaimed"},{"kind":"weakest_assumption","text":"That the algorithmic revisions to the iterative diagonalization procedure preserve the numerical accuracy and convergence properties of the original CPU implementation while achieving the reported GPU speedups.","source":"verdict.weakest_assumption","status":"machine_extracted","claim_id":"C2","attestation":"unclaimed"},{"kind":"one_line_summary","text":"Abinit's plane-wave DFT solver has been ported to multi-GPU architectures with performance benchmarks comparing CPU and CPU-GPU nodes for LOBPCG and Chebyshev filtering diagonalization methods.","source":"verdict.one_line_summary","status":"machine_extracted","claim_id":"C3","attestation":"unclaimed"},{"kind":"headline","text":"Abinit achieves GPU speedups for plane-wave DFT by revising the Kohn-Sham iterative diagonalizer.","source":"verdict.pith_extraction.headline","status":"machine_extracted","claim_id":"C4","attestation":"unclaimed"}],"snapshot_sha256":"95e2dee9dfeaddc696847923e8aa852b5c9d237ac73101859dcd5519a7e0a052"},"source":{"id":"2604.11139","kind":"arxiv","version":2},"verdict":{"id":"69ab9b7d-b087-4610-9fc6-314ff24a5503","model_set":{"reader":"grok-4.3"},"created_at":"2026-05-10T15:00:26.235557Z","strongest_claim":"The Abinit implementation on multi-GPU architectures provides detailed performance results to compare CPU nodes versus heterogeneous CPU-GPU nodes, with particular attention given to the comparison of LOBPCG and Chebyshev polynomial filtering in terms of their GPU efficiency.","one_line_summary":"Abinit's plane-wave DFT solver has been ported to multi-GPU architectures with performance benchmarks comparing CPU and CPU-GPU nodes for LOBPCG and Chebyshev filtering diagonalization methods.","pipeline_version":"pith-pipeline@v0.9.0","weakest_assumption":"That the algorithmic revisions to the iterative diagonalization procedure preserve the numerical accuracy and convergence properties of the original CPU implementation while achieving the reported GPU speedups.","pith_extraction_headline":"Abinit achieves GPU speedups for plane-wave DFT by revising the Kohn-Sham iterative diagonalizer."},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2604.11139/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":"2604.11139","created_at":"2026-05-28T02:04:47.575172+00:00"},{"alias_kind":"arxiv_version","alias_value":"2604.11139v2","created_at":"2026-05-28T02:04:47.575172+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2604.11139","created_at":"2026-05-28T02:04:47.575172+00:00"},{"alias_kind":"pith_short_12","alias_value":"WF7X5RZGA5NK","created_at":"2026-05-28T02:04:47.575172+00:00"},{"alias_kind":"pith_short_16","alias_value":"WF7X5RZGA5NKX7OI","created_at":"2026-05-28T02:04:47.575172+00:00"},{"alias_kind":"pith_short_8","alias_value":"WF7X5RZG","created_at":"2026-05-28T02:04:47.575172+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/WF7X5RZGA5NKX7OINSBJSNOLRP","json":"https://pith.science/pith/WF7X5RZGA5NKX7OINSBJSNOLRP.json","graph_json":"https://pith.science/api/pith-number/WF7X5RZGA5NKX7OINSBJSNOLRP/graph.json","events_json":"https://pith.science/api/pith-number/WF7X5RZGA5NKX7OINSBJSNOLRP/events.json","paper":"https://pith.science/paper/WF7X5RZG"},"agent_actions":{"view_html":"https://pith.science/pith/WF7X5RZGA5NKX7OINSBJSNOLRP","download_json":"https://pith.science/pith/WF7X5RZGA5NKX7OINSBJSNOLRP.json","view_paper":"https://pith.science/paper/WF7X5RZG","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2604.11139&json=true","fetch_graph":"https://pith.science/api/pith-number/WF7X5RZGA5NKX7OINSBJSNOLRP/graph.json","fetch_events":"https://pith.science/api/pith-number/WF7X5RZGA5NKX7OINSBJSNOLRP/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/WF7X5RZGA5NKX7OINSBJSNOLRP/action/timestamp_anchor","attest_storage":"https://pith.science/pith/WF7X5RZGA5NKX7OINSBJSNOLRP/action/storage_attestation","attest_author":"https://pith.science/pith/WF7X5RZGA5NKX7OINSBJSNOLRP/action/author_attestation","sign_citation":"https://pith.science/pith/WF7X5RZGA5NKX7OINSBJSNOLRP/action/citation_signature","submit_replication":"https://pith.science/pith/WF7X5RZGA5NKX7OINSBJSNOLRP/action/replication_record"}},"created_at":"2026-05-28T02:04:47.575172+00:00","updated_at":"2026-05-28T02:04:47.575172+00:00"}