{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:5JRQWOZQXH7OEUKGFRUN7KAKCG","short_pith_number":"pith:5JRQWOZQ","schema_version":"1.0","canonical_sha256":"ea630b3b30b9fee251462c68dfa80a11b6695c5b95eaf415f9da88b8b1aa508e","source":{"kind":"arxiv","id":"2308.07654","version":1},"attestation_state":"computed","paper":{"title":"SEER: Super-Optimization Explorer for HLS using E-graph Rewriting with MLIR","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AR","cs.CL"],"primary_cat":"cs.PL","authors_text":"Jianyi Cheng, Lorenzo Chelini, Rafael Barbalho, Samuel Coward, Theo Drane","submitted_at":"2023-08-15T09:05:27Z","abstract_excerpt":"High-level synthesis (HLS) is a process that automatically translates a software program in a high-level language into a low-level hardware description. However, the hardware designs produced by HLS tools still suffer from a significant performance gap compared to manual implementations. This is because the input HLS programs must still be written using hardware design principles.\n  Existing techniques either leave the program source unchanged or perform a fixed sequence of source transformation passes, potentially missing opportunities to find the optimal design. We propose a super-optimizati"},"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":"2308.07654","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.PL","submitted_at":"2023-08-15T09:05:27Z","cross_cats_sorted":["cs.AR","cs.CL"],"title_canon_sha256":"b1569211dd8c0b2a2afc5cd9199c0a5ae19bb33a269a97f12cc1e12c53d712c9","abstract_canon_sha256":"ec42b5447a1d46a6876c296745511fc78e59dbd7b3e18f46020c13071820d323"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:41:29.148078Z","signature_b64":"k8n1emoIAgURiQHTydEy+IE0Kbzo4yxi/TdyqVxdJK2HEY8XFUYAv0AucdGuiOA3ez6fZKuYTRjCwbcyPRO7Dw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ea630b3b30b9fee251462c68dfa80a11b6695c5b95eaf415f9da88b8b1aa508e","last_reissued_at":"2026-07-05T06:41:29.147634Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:41:29.147634Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"SEER: Super-Optimization Explorer for HLS using E-graph Rewriting with MLIR","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AR","cs.CL"],"primary_cat":"cs.PL","authors_text":"Jianyi Cheng, Lorenzo Chelini, Rafael Barbalho, Samuel Coward, Theo Drane","submitted_at":"2023-08-15T09:05:27Z","abstract_excerpt":"High-level synthesis (HLS) is a process that automatically translates a software program in a high-level language into a low-level hardware description. However, the hardware designs produced by HLS tools still suffer from a significant performance gap compared to manual implementations. This is because the input HLS programs must still be written using hardware design principles.\n  Existing techniques either leave the program source unchanged or perform a fixed sequence of source transformation passes, potentially missing opportunities to find the optimal design. We propose a super-optimizati"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.07654","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/2308.07654/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":"2308.07654","created_at":"2026-07-05T06:41:29.147693+00:00"},{"alias_kind":"arxiv_version","alias_value":"2308.07654v1","created_at":"2026-07-05T06:41:29.147693+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.07654","created_at":"2026-07-05T06:41:29.147693+00:00"},{"alias_kind":"pith_short_12","alias_value":"5JRQWOZQXH7O","created_at":"2026-07-05T06:41:29.147693+00:00"},{"alias_kind":"pith_short_16","alias_value":"5JRQWOZQXH7OEUKG","created_at":"2026-07-05T06:41:29.147693+00:00"},{"alias_kind":"pith_short_8","alias_value":"5JRQWOZQ","created_at":"2026-07-05T06:41:29.147693+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/5JRQWOZQXH7OEUKGFRUN7KAKCG","json":"https://pith.science/pith/5JRQWOZQXH7OEUKGFRUN7KAKCG.json","graph_json":"https://pith.science/api/pith-number/5JRQWOZQXH7OEUKGFRUN7KAKCG/graph.json","events_json":"https://pith.science/api/pith-number/5JRQWOZQXH7OEUKGFRUN7KAKCG/events.json","paper":"https://pith.science/paper/5JRQWOZQ"},"agent_actions":{"view_html":"https://pith.science/pith/5JRQWOZQXH7OEUKGFRUN7KAKCG","download_json":"https://pith.science/pith/5JRQWOZQXH7OEUKGFRUN7KAKCG.json","view_paper":"https://pith.science/paper/5JRQWOZQ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2308.07654&json=true","fetch_graph":"https://pith.science/api/pith-number/5JRQWOZQXH7OEUKGFRUN7KAKCG/graph.json","fetch_events":"https://pith.science/api/pith-number/5JRQWOZQXH7OEUKGFRUN7KAKCG/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/5JRQWOZQXH7OEUKGFRUN7KAKCG/action/timestamp_anchor","attest_storage":"https://pith.science/pith/5JRQWOZQXH7OEUKGFRUN7KAKCG/action/storage_attestation","attest_author":"https://pith.science/pith/5JRQWOZQXH7OEUKGFRUN7KAKCG/action/author_attestation","sign_citation":"https://pith.science/pith/5JRQWOZQXH7OEUKGFRUN7KAKCG/action/citation_signature","submit_replication":"https://pith.science/pith/5JRQWOZQXH7OEUKGFRUN7KAKCG/action/replication_record"}},"created_at":"2026-07-05T06:41:29.147693+00:00","updated_at":"2026-07-05T06:41:29.147693+00:00"}