{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:P6PWRGM4OBC42RVL4V723LMOCW","short_pith_number":"pith:P6PWRGM4","schema_version":"1.0","canonical_sha256":"7f9f68999c7045cd46abe57fadad8e15ae2de6c737911242db13010e7e87049b","source":{"kind":"arxiv","id":"2310.17408","version":2},"attestation_state":"computed","paper":{"title":"Tackling the Matrix Multiplication Micro-kernel Generation with Exo","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CL","cs.PF"],"primary_cat":"cs.MS","authors_text":"Adri\\'an Castell\\'o, Grace Dinh, H\\'ector Mart\\'inez, Julian Bellavita, Yuka Ikarashi","submitted_at":"2023-10-26T14:09:57Z","abstract_excerpt":"The optimization of the matrix multiplication (or GEMM) has been a need during the last decades. This operation is considered the flagship of current linear algebra libraries such as BLIS, OpenBLAS, or Intel OneAPI because of its widespread use in a large variety of scientific applications. The GEMM is usually implemented following the GotoBLAS philosophy, which tiles the GEMM operands and uses a series of nested loops for performance improvement. These approaches extract the maximum computational power of the architectures through small pieces of hardware-oriented, high-performance code calle"},"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":"2310.17408","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.MS","submitted_at":"2023-10-26T14:09:57Z","cross_cats_sorted":["cs.CL","cs.PF"],"title_canon_sha256":"16904b6a7fe95f57d55ae6f4c6a6ecf17d9567c7be73e7903a9d4716018cb503","abstract_canon_sha256":"20376b623db40ae0e4f20bc4d7f01449cab4a4e4c78e44e6880e96d079e80100"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:05:49.875459Z","signature_b64":"WD88Bpm71akWHf5kzp371FxNT0vvdMmGVm4HDelbXqg73MFUKge1Q5D0Pe4mN2hpyPt82WWSjBcmozWoa0fIDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7f9f68999c7045cd46abe57fadad8e15ae2de6c737911242db13010e7e87049b","last_reissued_at":"2026-07-05T07:05:49.874923Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:05:49.874923Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Tackling the Matrix Multiplication Micro-kernel Generation with Exo","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CL","cs.PF"],"primary_cat":"cs.MS","authors_text":"Adri\\'an Castell\\'o, Grace Dinh, H\\'ector Mart\\'inez, Julian Bellavita, Yuka Ikarashi","submitted_at":"2023-10-26T14:09:57Z","abstract_excerpt":"The optimization of the matrix multiplication (or GEMM) has been a need during the last decades. This operation is considered the flagship of current linear algebra libraries such as BLIS, OpenBLAS, or Intel OneAPI because of its widespread use in a large variety of scientific applications. The GEMM is usually implemented following the GotoBLAS philosophy, which tiles the GEMM operands and uses a series of nested loops for performance improvement. These approaches extract the maximum computational power of the architectures through small pieces of hardware-oriented, high-performance code calle"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.17408","kind":"arxiv","version":2},"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/2310.17408/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":"2310.17408","created_at":"2026-07-05T07:05:49.874978+00:00"},{"alias_kind":"arxiv_version","alias_value":"2310.17408v2","created_at":"2026-07-05T07:05:49.874978+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.17408","created_at":"2026-07-05T07:05:49.874978+00:00"},{"alias_kind":"pith_short_12","alias_value":"P6PWRGM4OBC4","created_at":"2026-07-05T07:05:49.874978+00:00"},{"alias_kind":"pith_short_16","alias_value":"P6PWRGM4OBC42RVL","created_at":"2026-07-05T07:05:49.874978+00:00"},{"alias_kind":"pith_short_8","alias_value":"P6PWRGM4","created_at":"2026-07-05T07:05:49.874978+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/P6PWRGM4OBC42RVL4V723LMOCW","json":"https://pith.science/pith/P6PWRGM4OBC42RVL4V723LMOCW.json","graph_json":"https://pith.science/api/pith-number/P6PWRGM4OBC42RVL4V723LMOCW/graph.json","events_json":"https://pith.science/api/pith-number/P6PWRGM4OBC42RVL4V723LMOCW/events.json","paper":"https://pith.science/paper/P6PWRGM4"},"agent_actions":{"view_html":"https://pith.science/pith/P6PWRGM4OBC42RVL4V723LMOCW","download_json":"https://pith.science/pith/P6PWRGM4OBC42RVL4V723LMOCW.json","view_paper":"https://pith.science/paper/P6PWRGM4","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2310.17408&json=true","fetch_graph":"https://pith.science/api/pith-number/P6PWRGM4OBC42RVL4V723LMOCW/graph.json","fetch_events":"https://pith.science/api/pith-number/P6PWRGM4OBC42RVL4V723LMOCW/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/P6PWRGM4OBC42RVL4V723LMOCW/action/timestamp_anchor","attest_storage":"https://pith.science/pith/P6PWRGM4OBC42RVL4V723LMOCW/action/storage_attestation","attest_author":"https://pith.science/pith/P6PWRGM4OBC42RVL4V723LMOCW/action/author_attestation","sign_citation":"https://pith.science/pith/P6PWRGM4OBC42RVL4V723LMOCW/action/citation_signature","submit_replication":"https://pith.science/pith/P6PWRGM4OBC42RVL4V723LMOCW/action/replication_record"}},"created_at":"2026-07-05T07:05:49.874978+00:00","updated_at":"2026-07-05T07:05:49.874978+00:00"}