{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:WPGWB5SE2DPRLPNX7SWKE2MSDS","short_pith_number":"pith:WPGWB5SE","schema_version":"1.0","canonical_sha256":"b3cd60f644d0df15bdb7fcaca269921c9cacb35006988f4679a096faed98283e","source":{"kind":"arxiv","id":"2102.07952","version":2},"attestation_state":"computed","paper":{"title":"A Survey of Machine Learning for Computer Architecture and Systems","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.AR"],"primary_cat":"cs.LG","authors_text":"Nan Wu, Yuan Xie","submitted_at":"2021-02-16T04:09:57Z","abstract_excerpt":"It has been a long time that computer architecture and systems are optimized for efficient execution of machine learning (ML) models. Now, it is time to reconsider the relationship between ML and systems, and let ML transform the way that computer architecture and systems are designed. This embraces a twofold meaning: improvement of designers' productivity, and completion of the virtuous cycle. In this paper, we present a comprehensive review of the work that applies ML for computer architecture and system design. First, we perform a high-level taxonomy by considering the typical role that ML "},"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":"2102.07952","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2021-02-16T04:09:57Z","cross_cats_sorted":["cs.AR"],"title_canon_sha256":"5e87000b9457301323b7f533c27df22707af37379573b6a0138c810e102a5f82","abstract_canon_sha256":"45fb8a6b1f99493e67f91130d9d953e1feb9f8fb2fbdd493f5221476ad51a92b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:59:37.987427Z","signature_b64":"rOFnd+GYO7eAp89uSR6joB0JXEzGkZZO2sxwkLOuRC01rjqwXnGYNyqWSpyYpu2dsU30Gj5VZRdwaueIvQRQAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b3cd60f644d0df15bdb7fcaca269921c9cacb35006988f4679a096faed98283e","last_reissued_at":"2026-07-05T03:59:37.987003Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:59:37.987003Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Survey of Machine Learning for Computer Architecture and Systems","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.AR"],"primary_cat":"cs.LG","authors_text":"Nan Wu, Yuan Xie","submitted_at":"2021-02-16T04:09:57Z","abstract_excerpt":"It has been a long time that computer architecture and systems are optimized for efficient execution of machine learning (ML) models. Now, it is time to reconsider the relationship between ML and systems, and let ML transform the way that computer architecture and systems are designed. This embraces a twofold meaning: improvement of designers' productivity, and completion of the virtuous cycle. In this paper, we present a comprehensive review of the work that applies ML for computer architecture and system design. First, we perform a high-level taxonomy by considering the typical role that ML "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2102.07952","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/2102.07952/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":"2102.07952","created_at":"2026-07-05T03:59:37.987060+00:00"},{"alias_kind":"arxiv_version","alias_value":"2102.07952v2","created_at":"2026-07-05T03:59:37.987060+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2102.07952","created_at":"2026-07-05T03:59:37.987060+00:00"},{"alias_kind":"pith_short_12","alias_value":"WPGWB5SE2DPR","created_at":"2026-07-05T03:59:37.987060+00:00"},{"alias_kind":"pith_short_16","alias_value":"WPGWB5SE2DPRLPNX","created_at":"2026-07-05T03:59:37.987060+00:00"},{"alias_kind":"pith_short_8","alias_value":"WPGWB5SE","created_at":"2026-07-05T03:59:37.987060+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/WPGWB5SE2DPRLPNX7SWKE2MSDS","json":"https://pith.science/pith/WPGWB5SE2DPRLPNX7SWKE2MSDS.json","graph_json":"https://pith.science/api/pith-number/WPGWB5SE2DPRLPNX7SWKE2MSDS/graph.json","events_json":"https://pith.science/api/pith-number/WPGWB5SE2DPRLPNX7SWKE2MSDS/events.json","paper":"https://pith.science/paper/WPGWB5SE"},"agent_actions":{"view_html":"https://pith.science/pith/WPGWB5SE2DPRLPNX7SWKE2MSDS","download_json":"https://pith.science/pith/WPGWB5SE2DPRLPNX7SWKE2MSDS.json","view_paper":"https://pith.science/paper/WPGWB5SE","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2102.07952&json=true","fetch_graph":"https://pith.science/api/pith-number/WPGWB5SE2DPRLPNX7SWKE2MSDS/graph.json","fetch_events":"https://pith.science/api/pith-number/WPGWB5SE2DPRLPNX7SWKE2MSDS/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/WPGWB5SE2DPRLPNX7SWKE2MSDS/action/timestamp_anchor","attest_storage":"https://pith.science/pith/WPGWB5SE2DPRLPNX7SWKE2MSDS/action/storage_attestation","attest_author":"https://pith.science/pith/WPGWB5SE2DPRLPNX7SWKE2MSDS/action/author_attestation","sign_citation":"https://pith.science/pith/WPGWB5SE2DPRLPNX7SWKE2MSDS/action/citation_signature","submit_replication":"https://pith.science/pith/WPGWB5SE2DPRLPNX7SWKE2MSDS/action/replication_record"}},"created_at":"2026-07-05T03:59:37.987060+00:00","updated_at":"2026-07-05T03:59:37.987060+00:00"}