{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:NYP6UXRTMGMMLZ67M2MKT5D2JL","short_pith_number":"pith:NYP6UXRT","schema_version":"1.0","canonical_sha256":"6e1fea5e336198c5e7df6698a9f47a4acf5c6a8ce4a2a3b1de0844cc1364c791","source":{"kind":"arxiv","id":"1808.06411","version":2},"attestation_state":"computed","paper":{"title":"Scalable Edge Partitioning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DC","cs.DM"],"primary_cat":"cs.DS","authors_text":"Christian Schulz, Daniel Seemaier, Darren Strash, Sebastian Schlag","submitted_at":"2018-08-20T12:09:31Z","abstract_excerpt":"Edge-centric distributed computations have appeared as a recent technique to improve the shortcomings of think-like-a-vertex algorithms on large scale-free networks. In order to increase parallelism on this model, edge partitioning - partitioning edges into roughly equally sized blocks - has emerged as an alternative to traditional (node-based) graph partitioning. In this work, we give a distributed memory parallel algorithm to compute high-quality edge partitions in a scalable way. Our algorithm scales to networks with billions of edges, and runs efficiently on thousands of PEs. Our technique"},"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":"1808.06411","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2018-08-20T12:09:31Z","cross_cats_sorted":["cs.DC","cs.DM"],"title_canon_sha256":"268f092b8fcf2e9218f3e214424f3e75ca95b76a727814f2748b60416f81e550","abstract_canon_sha256":"f4fde4b9618e770b81710af635478fc533f605541f9e3a7cf60569a1f14981b3"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:03:36.578295Z","signature_b64":"vrnYc7V3fJqXXhc0tyQkkm71yxojoaHMxtQs3UFSEwBJbGSrNVCb4pFqHEbqgGk9Sr7myD894/KF2N83f+TBCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6e1fea5e336198c5e7df6698a9f47a4acf5c6a8ce4a2a3b1de0844cc1364c791","last_reissued_at":"2026-05-18T00:03:36.577503Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:03:36.577503Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Scalable Edge Partitioning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DC","cs.DM"],"primary_cat":"cs.DS","authors_text":"Christian Schulz, Daniel Seemaier, Darren Strash, Sebastian Schlag","submitted_at":"2018-08-20T12:09:31Z","abstract_excerpt":"Edge-centric distributed computations have appeared as a recent technique to improve the shortcomings of think-like-a-vertex algorithms on large scale-free networks. In order to increase parallelism on this model, edge partitioning - partitioning edges into roughly equally sized blocks - has emerged as an alternative to traditional (node-based) graph partitioning. In this work, we give a distributed memory parallel algorithm to compute high-quality edge partitions in a scalable way. Our algorithm scales to networks with billions of edges, and runs efficiently on thousands of PEs. Our technique"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1808.06411","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":"1808.06411","created_at":"2026-05-18T00:03:36.577637+00:00"},{"alias_kind":"arxiv_version","alias_value":"1808.06411v2","created_at":"2026-05-18T00:03:36.577637+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1808.06411","created_at":"2026-05-18T00:03:36.577637+00:00"},{"alias_kind":"pith_short_12","alias_value":"NYP6UXRTMGMM","created_at":"2026-05-18T12:32:40.477152+00:00"},{"alias_kind":"pith_short_16","alias_value":"NYP6UXRTMGMMLZ67","created_at":"2026-05-18T12:32:40.477152+00:00"},{"alias_kind":"pith_short_8","alias_value":"NYP6UXRT","created_at":"2026-05-18T12:32:40.477152+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/NYP6UXRTMGMMLZ67M2MKT5D2JL","json":"https://pith.science/pith/NYP6UXRTMGMMLZ67M2MKT5D2JL.json","graph_json":"https://pith.science/api/pith-number/NYP6UXRTMGMMLZ67M2MKT5D2JL/graph.json","events_json":"https://pith.science/api/pith-number/NYP6UXRTMGMMLZ67M2MKT5D2JL/events.json","paper":"https://pith.science/paper/NYP6UXRT"},"agent_actions":{"view_html":"https://pith.science/pith/NYP6UXRTMGMMLZ67M2MKT5D2JL","download_json":"https://pith.science/pith/NYP6UXRTMGMMLZ67M2MKT5D2JL.json","view_paper":"https://pith.science/paper/NYP6UXRT","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1808.06411&json=true","fetch_graph":"https://pith.science/api/pith-number/NYP6UXRTMGMMLZ67M2MKT5D2JL/graph.json","fetch_events":"https://pith.science/api/pith-number/NYP6UXRTMGMMLZ67M2MKT5D2JL/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/NYP6UXRTMGMMLZ67M2MKT5D2JL/action/timestamp_anchor","attest_storage":"https://pith.science/pith/NYP6UXRTMGMMLZ67M2MKT5D2JL/action/storage_attestation","attest_author":"https://pith.science/pith/NYP6UXRTMGMMLZ67M2MKT5D2JL/action/author_attestation","sign_citation":"https://pith.science/pith/NYP6UXRTMGMMLZ67M2MKT5D2JL/action/citation_signature","submit_replication":"https://pith.science/pith/NYP6UXRTMGMMLZ67M2MKT5D2JL/action/replication_record"}},"created_at":"2026-05-18T00:03:36.577637+00:00","updated_at":"2026-05-18T00:03:36.577637+00:00"}