{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:HXN7VTCCUYEVJOVXJSFH5CL2VG","short_pith_number":"pith:HXN7VTCC","schema_version":"1.0","canonical_sha256":"3ddbfacc42a60954bab74c8a7e897aa9ac557c5b535c18a139c14f39b78447ef","source":{"kind":"arxiv","id":"1901.01328","version":2},"attestation_state":"computed","paper":{"title":"StreamBox-HBM: Stream Analytics on High Bandwidth Hybrid Memory","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DB","authors_text":"Felix Xiaozhu Lin, Gennady Pekhimenko, Hongyu Miao, Kathryn S. McKinley, Myeongjae Jeon","submitted_at":"2019-01-04T22:14:14Z","abstract_excerpt":"Stream analytics have an insatiable demand for memory and performance. Emerging hybrid memories combine commodity DDR4 DRAM with 3D-stacked High Bandwidth Memory (HBM) DRAM to meet such demands. However, achieving this promise is challenging because (1) HBM is capacity-limited and (2) HBM boosts performance best for sequential access and high parallelism workloads. At first glance, stream analytics appear a particularly poor match for HBM because they have high capacity demands and data grouping operations, their most demanding computations, use random access. This paper presents the design an"},"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":"1901.01328","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2019-01-04T22:14:14Z","cross_cats_sorted":[],"title_canon_sha256":"7374c789f4ba9c0081c4dc9dfcd47f4c3819019319fe80046c6b230068b8c187","abstract_canon_sha256":"5e77f44ff8e6f552d1bce5978d9267d90da96289031ffbafca219ba9e0778002"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:55:26.918672Z","signature_b64":"CuqJuV4YGePzFn+ZnMdcD/hO6Y+E3f6Fh7hja+9FMPEXodgveuwnudPhhaD2dEUWtoCcejJ9iSblYzqEZh6IBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3ddbfacc42a60954bab74c8a7e897aa9ac557c5b535c18a139c14f39b78447ef","last_reissued_at":"2026-05-17T23:55:26.918259Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:55:26.918259Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"StreamBox-HBM: Stream Analytics on High Bandwidth Hybrid Memory","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DB","authors_text":"Felix Xiaozhu Lin, Gennady Pekhimenko, Hongyu Miao, Kathryn S. McKinley, Myeongjae Jeon","submitted_at":"2019-01-04T22:14:14Z","abstract_excerpt":"Stream analytics have an insatiable demand for memory and performance. Emerging hybrid memories combine commodity DDR4 DRAM with 3D-stacked High Bandwidth Memory (HBM) DRAM to meet such demands. However, achieving this promise is challenging because (1) HBM is capacity-limited and (2) HBM boosts performance best for sequential access and high parallelism workloads. At first glance, stream analytics appear a particularly poor match for HBM because they have high capacity demands and data grouping operations, their most demanding computations, use random access. This paper presents the design an"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1901.01328","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":""},"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":"1901.01328","created_at":"2026-05-17T23:55:26.918327+00:00"},{"alias_kind":"arxiv_version","alias_value":"1901.01328v2","created_at":"2026-05-17T23:55:26.918327+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1901.01328","created_at":"2026-05-17T23:55:26.918327+00:00"},{"alias_kind":"pith_short_12","alias_value":"HXN7VTCCUYEV","created_at":"2026-05-18T12:33:18.533446+00:00"},{"alias_kind":"pith_short_16","alias_value":"HXN7VTCCUYEVJOVX","created_at":"2026-05-18T12:33:18.533446+00:00"},{"alias_kind":"pith_short_8","alias_value":"HXN7VTCC","created_at":"2026-05-18T12:33:18.533446+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/HXN7VTCCUYEVJOVXJSFH5CL2VG","json":"https://pith.science/pith/HXN7VTCCUYEVJOVXJSFH5CL2VG.json","graph_json":"https://pith.science/api/pith-number/HXN7VTCCUYEVJOVXJSFH5CL2VG/graph.json","events_json":"https://pith.science/api/pith-number/HXN7VTCCUYEVJOVXJSFH5CL2VG/events.json","paper":"https://pith.science/paper/HXN7VTCC"},"agent_actions":{"view_html":"https://pith.science/pith/HXN7VTCCUYEVJOVXJSFH5CL2VG","download_json":"https://pith.science/pith/HXN7VTCCUYEVJOVXJSFH5CL2VG.json","view_paper":"https://pith.science/paper/HXN7VTCC","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1901.01328&json=true","fetch_graph":"https://pith.science/api/pith-number/HXN7VTCCUYEVJOVXJSFH5CL2VG/graph.json","fetch_events":"https://pith.science/api/pith-number/HXN7VTCCUYEVJOVXJSFH5CL2VG/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/HXN7VTCCUYEVJOVXJSFH5CL2VG/action/timestamp_anchor","attest_storage":"https://pith.science/pith/HXN7VTCCUYEVJOVXJSFH5CL2VG/action/storage_attestation","attest_author":"https://pith.science/pith/HXN7VTCCUYEVJOVXJSFH5CL2VG/action/author_attestation","sign_citation":"https://pith.science/pith/HXN7VTCCUYEVJOVXJSFH5CL2VG/action/citation_signature","submit_replication":"https://pith.science/pith/HXN7VTCCUYEVJOVXJSFH5CL2VG/action/replication_record"}},"created_at":"2026-05-17T23:55:26.918327+00:00","updated_at":"2026-05-17T23:55:26.918327+00:00"}