{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:64VGPZTR266TV2LI6VKUB5KUQG","short_pith_number":"pith:64VGPZTR","schema_version":"1.0","canonical_sha256":"f72a67e671d7bd3ae968f55540f55481bfa358ac76dedfe1c6acafbfab291a11","source":{"kind":"arxiv","id":"1908.04718","version":1},"attestation_state":"computed","paper":{"title":"Micro-architectural Analysis of OLAP: Limitations and Opportunities","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.PF"],"primary_cat":"cs.DB","authors_text":"Anastasia Ailamaki, Utku Sirin","submitted_at":"2019-08-13T16:18:00Z","abstract_excerpt":"Understanding micro-architectural behavior is profound in efficiently using hardware resources. Recent work has shown that, despite being aggressively optimized for modern hardware, in-memory online transaction processing (OLTP) systems severely underutilize their core micro-architecture resources [25]. Online analytical processing (OLAP) workloads, on the other hand, exhibit a completely different computing pattern. OLAP workloads are read-only, bandwidth-intensive and include various data access patterns including both sequential and random data accesses. In addition, with the rise of column"},"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":"1908.04718","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2019-08-13T16:18:00Z","cross_cats_sorted":["cs.PF"],"title_canon_sha256":"91704bf830da774a64a666124ba3be0ee9ec7e920ba7aaa91c8a8972d325163a","abstract_canon_sha256":"ff9a148ce0458a6a1d38da556da51b34b5d711eae055c1d1099e5e5126753d87"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T01:06:02.555058Z","signature_b64":"KTGxQBDsg3vfjGxb/FHPYxjGLV4lwdNMDJnXzybExx5Rxjq4yO+gJMtK23xM0fPZd2TXhxWtNclkTeiy6M/EBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f72a67e671d7bd3ae968f55540f55481bfa358ac76dedfe1c6acafbfab291a11","last_reissued_at":"2026-05-20T01:06:02.554164Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T01:06:02.554164Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Micro-architectural Analysis of OLAP: Limitations and Opportunities","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.PF"],"primary_cat":"cs.DB","authors_text":"Anastasia Ailamaki, Utku Sirin","submitted_at":"2019-08-13T16:18:00Z","abstract_excerpt":"Understanding micro-architectural behavior is profound in efficiently using hardware resources. Recent work has shown that, despite being aggressively optimized for modern hardware, in-memory online transaction processing (OLTP) systems severely underutilize their core micro-architecture resources [25]. Online analytical processing (OLAP) workloads, on the other hand, exhibit a completely different computing pattern. OLAP workloads are read-only, bandwidth-intensive and include various data access patterns including both sequential and random data accesses. In addition, with the rise of column"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1908.04718","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/1908.04718/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":"1908.04718","created_at":"2026-05-20T01:06:02.554300+00:00"},{"alias_kind":"arxiv_version","alias_value":"1908.04718v1","created_at":"2026-05-20T01:06:02.554300+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1908.04718","created_at":"2026-05-20T01:06:02.554300+00:00"},{"alias_kind":"pith_short_12","alias_value":"64VGPZTR266T","created_at":"2026-05-20T01:06:02.554300+00:00"},{"alias_kind":"pith_short_16","alias_value":"64VGPZTR266TV2LI","created_at":"2026-05-20T01:06:02.554300+00:00"},{"alias_kind":"pith_short_8","alias_value":"64VGPZTR","created_at":"2026-05-20T01:06:02.554300+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"1908.04718","citing_title":"Micro-architectural Analysis of OLAP: Limitations and Opportunities","ref_index":1,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/64VGPZTR266TV2LI6VKUB5KUQG","json":"https://pith.science/pith/64VGPZTR266TV2LI6VKUB5KUQG.json","graph_json":"https://pith.science/api/pith-number/64VGPZTR266TV2LI6VKUB5KUQG/graph.json","events_json":"https://pith.science/api/pith-number/64VGPZTR266TV2LI6VKUB5KUQG/events.json","paper":"https://pith.science/paper/64VGPZTR"},"agent_actions":{"view_html":"https://pith.science/pith/64VGPZTR266TV2LI6VKUB5KUQG","download_json":"https://pith.science/pith/64VGPZTR266TV2LI6VKUB5KUQG.json","view_paper":"https://pith.science/paper/64VGPZTR","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1908.04718&json=true","fetch_graph":"https://pith.science/api/pith-number/64VGPZTR266TV2LI6VKUB5KUQG/graph.json","fetch_events":"https://pith.science/api/pith-number/64VGPZTR266TV2LI6VKUB5KUQG/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/64VGPZTR266TV2LI6VKUB5KUQG/action/timestamp_anchor","attest_storage":"https://pith.science/pith/64VGPZTR266TV2LI6VKUB5KUQG/action/storage_attestation","attest_author":"https://pith.science/pith/64VGPZTR266TV2LI6VKUB5KUQG/action/author_attestation","sign_citation":"https://pith.science/pith/64VGPZTR266TV2LI6VKUB5KUQG/action/citation_signature","submit_replication":"https://pith.science/pith/64VGPZTR266TV2LI6VKUB5KUQG/action/replication_record"}},"created_at":"2026-05-20T01:06:02.554300+00:00","updated_at":"2026-05-20T01:06:02.554300+00:00"}