{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:W54OB4VGGYMGMMNXLM5HJCBP57","short_pith_number":"pith:W54OB4VG","schema_version":"1.0","canonical_sha256":"b778e0f2a636186631b75b3a74882fefc010683285ab145406ab8206fb040e64","source":{"kind":"arxiv","id":"2309.06418","version":1},"attestation_state":"computed","paper":{"title":"C4CAM: A Compiler for CAM-based In-memory Accelerators","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AR","authors_text":"Asif Ali Khan, Hamid Farzaneh, Jeronimo Castrillon, Jo\\~ao Paulo Cardoso de Lima, Mengyuan Li, Xiaobo Sharon Hu","submitted_at":"2023-09-12T17:30:34Z","abstract_excerpt":"Machine learning and data analytics applications increasingly suffer from the high latency and energy consumption of conventional von Neumann architectures. Recently, several in-memory and near-memory systems have been proposed to remove this von Neumann bottleneck. Platforms based on content-addressable memories (CAMs) are particularly interesting due to their efficient support for the search-based operations that form the foundation for many applications, including K-nearest neighbors (KNN), high-dimensional computing (HDC), recommender systems, and one-shot learning among others. Today, the"},"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":"2309.06418","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AR","submitted_at":"2023-09-12T17:30:34Z","cross_cats_sorted":[],"title_canon_sha256":"1b4e825fe6ff412eaa95f93e4d27f192ef19c6dcf74a548f9b3695d4d56a2d98","abstract_canon_sha256":"f385f7cb6639ef72ef9fb851970f590fc5eb46cb34291b982e2101802ee08224"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:50:07.658752Z","signature_b64":"C3u7em9pi4seg2t8UR9KlcyEBRLUsmgNoyu65VK303doNR5fvZLlaTvWvS34NFWVn4NM5ZGhbeZK6lxrNTErAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b778e0f2a636186631b75b3a74882fefc010683285ab145406ab8206fb040e64","last_reissued_at":"2026-07-05T06:50:07.658348Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:50:07.658348Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"C4CAM: A Compiler for CAM-based In-memory Accelerators","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AR","authors_text":"Asif Ali Khan, Hamid Farzaneh, Jeronimo Castrillon, Jo\\~ao Paulo Cardoso de Lima, Mengyuan Li, Xiaobo Sharon Hu","submitted_at":"2023-09-12T17:30:34Z","abstract_excerpt":"Machine learning and data analytics applications increasingly suffer from the high latency and energy consumption of conventional von Neumann architectures. Recently, several in-memory and near-memory systems have been proposed to remove this von Neumann bottleneck. Platforms based on content-addressable memories (CAMs) are particularly interesting due to their efficient support for the search-based operations that form the foundation for many applications, including K-nearest neighbors (KNN), high-dimensional computing (HDC), recommender systems, and one-shot learning among others. Today, the"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2309.06418","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/2309.06418/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":"2309.06418","created_at":"2026-07-05T06:50:07.658407+00:00"},{"alias_kind":"arxiv_version","alias_value":"2309.06418v1","created_at":"2026-07-05T06:50:07.658407+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2309.06418","created_at":"2026-07-05T06:50:07.658407+00:00"},{"alias_kind":"pith_short_12","alias_value":"W54OB4VGGYMG","created_at":"2026-07-05T06:50:07.658407+00:00"},{"alias_kind":"pith_short_16","alias_value":"W54OB4VGGYMGMMNX","created_at":"2026-07-05T06:50:07.658407+00:00"},{"alias_kind":"pith_short_8","alias_value":"W54OB4VG","created_at":"2026-07-05T06:50:07.658407+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/W54OB4VGGYMGMMNXLM5HJCBP57","json":"https://pith.science/pith/W54OB4VGGYMGMMNXLM5HJCBP57.json","graph_json":"https://pith.science/api/pith-number/W54OB4VGGYMGMMNXLM5HJCBP57/graph.json","events_json":"https://pith.science/api/pith-number/W54OB4VGGYMGMMNXLM5HJCBP57/events.json","paper":"https://pith.science/paper/W54OB4VG"},"agent_actions":{"view_html":"https://pith.science/pith/W54OB4VGGYMGMMNXLM5HJCBP57","download_json":"https://pith.science/pith/W54OB4VGGYMGMMNXLM5HJCBP57.json","view_paper":"https://pith.science/paper/W54OB4VG","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2309.06418&json=true","fetch_graph":"https://pith.science/api/pith-number/W54OB4VGGYMGMMNXLM5HJCBP57/graph.json","fetch_events":"https://pith.science/api/pith-number/W54OB4VGGYMGMMNXLM5HJCBP57/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/W54OB4VGGYMGMMNXLM5HJCBP57/action/timestamp_anchor","attest_storage":"https://pith.science/pith/W54OB4VGGYMGMMNXLM5HJCBP57/action/storage_attestation","attest_author":"https://pith.science/pith/W54OB4VGGYMGMMNXLM5HJCBP57/action/author_attestation","sign_citation":"https://pith.science/pith/W54OB4VGGYMGMMNXLM5HJCBP57/action/citation_signature","submit_replication":"https://pith.science/pith/W54OB4VGGYMGMMNXLM5HJCBP57/action/replication_record"}},"created_at":"2026-07-05T06:50:07.658407+00:00","updated_at":"2026-07-05T06:50:07.658407+00:00"}