{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2012:KMZOQOIT26YLB6S2MCWDUWMYXF","short_pith_number":"pith:KMZOQOIT","schema_version":"1.0","canonical_sha256":"5332e83913d7b0b0fa5a60ac3a5998b976fd4d9b66fb1f6e6d846ae15137a000","source":{"kind":"arxiv","id":"1201.3778","version":2},"attestation_state":"computed","paper":{"title":"Processor Allocation for Optimistic Parallelization of Irregular Programs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DS"],"primary_cat":"cs.PL","authors_text":"Francesco Versaci, Keshav Pingali","submitted_at":"2012-01-18T13:16:57Z","abstract_excerpt":"Optimistic parallelization is a promising approach for the parallelization of irregular algorithms: potentially interfering tasks are launched dynamically, and the runtime system detects conflicts between concurrent activities, aborting and rolling back conflicting tasks. However, parallelism in irregular algorithms is very complex. In a regular algorithm like dense matrix multiplication, the amount of parallelism can usually be expressed as a function of the problem size, so it is reasonably straightforward to determine how many processors should be allocated to execute a regular algorithm of"},"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":"1201.3778","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.PL","submitted_at":"2012-01-18T13:16:57Z","cross_cats_sorted":["cs.DS"],"title_canon_sha256":"05b2ae07820882b100f173521872af28c8c4f76209d722b58b00a9d80433950b","abstract_canon_sha256":"cd80ed06783037e1c8b1672a2c422d48ab979adf9372d4061ec3185d4ced4df5"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:52:28.166706Z","signature_b64":"ncWnSBcAbuKnxHZM6NdGuZO63X5cQO6jUgNqfuGnZ9Xm/6Lm3KU/vIU5s5D5017Gfwjnm8YYkqZovdatjTCfBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5332e83913d7b0b0fa5a60ac3a5998b976fd4d9b66fb1f6e6d846ae15137a000","last_reissued_at":"2026-05-18T03:52:28.165562Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:52:28.165562Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Processor Allocation for Optimistic Parallelization of Irregular Programs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DS"],"primary_cat":"cs.PL","authors_text":"Francesco Versaci, Keshav Pingali","submitted_at":"2012-01-18T13:16:57Z","abstract_excerpt":"Optimistic parallelization is a promising approach for the parallelization of irregular algorithms: potentially interfering tasks are launched dynamically, and the runtime system detects conflicts between concurrent activities, aborting and rolling back conflicting tasks. However, parallelism in irregular algorithms is very complex. In a regular algorithm like dense matrix multiplication, the amount of parallelism can usually be expressed as a function of the problem size, so it is reasonably straightforward to determine how many processors should be allocated to execute a regular algorithm of"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1201.3778","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":"1201.3778","created_at":"2026-05-18T03:52:28.165909+00:00"},{"alias_kind":"arxiv_version","alias_value":"1201.3778v2","created_at":"2026-05-18T03:52:28.165909+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1201.3778","created_at":"2026-05-18T03:52:28.165909+00:00"},{"alias_kind":"pith_short_12","alias_value":"KMZOQOIT26YL","created_at":"2026-05-18T12:27:11.947152+00:00"},{"alias_kind":"pith_short_16","alias_value":"KMZOQOIT26YLB6S2","created_at":"2026-05-18T12:27:11.947152+00:00"},{"alias_kind":"pith_short_8","alias_value":"KMZOQOIT","created_at":"2026-05-18T12:27:11.947152+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/KMZOQOIT26YLB6S2MCWDUWMYXF","json":"https://pith.science/pith/KMZOQOIT26YLB6S2MCWDUWMYXF.json","graph_json":"https://pith.science/api/pith-number/KMZOQOIT26YLB6S2MCWDUWMYXF/graph.json","events_json":"https://pith.science/api/pith-number/KMZOQOIT26YLB6S2MCWDUWMYXF/events.json","paper":"https://pith.science/paper/KMZOQOIT"},"agent_actions":{"view_html":"https://pith.science/pith/KMZOQOIT26YLB6S2MCWDUWMYXF","download_json":"https://pith.science/pith/KMZOQOIT26YLB6S2MCWDUWMYXF.json","view_paper":"https://pith.science/paper/KMZOQOIT","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1201.3778&json=true","fetch_graph":"https://pith.science/api/pith-number/KMZOQOIT26YLB6S2MCWDUWMYXF/graph.json","fetch_events":"https://pith.science/api/pith-number/KMZOQOIT26YLB6S2MCWDUWMYXF/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/KMZOQOIT26YLB6S2MCWDUWMYXF/action/timestamp_anchor","attest_storage":"https://pith.science/pith/KMZOQOIT26YLB6S2MCWDUWMYXF/action/storage_attestation","attest_author":"https://pith.science/pith/KMZOQOIT26YLB6S2MCWDUWMYXF/action/author_attestation","sign_citation":"https://pith.science/pith/KMZOQOIT26YLB6S2MCWDUWMYXF/action/citation_signature","submit_replication":"https://pith.science/pith/KMZOQOIT26YLB6S2MCWDUWMYXF/action/replication_record"}},"created_at":"2026-05-18T03:52:28.165909+00:00","updated_at":"2026-05-18T03:52:28.165909+00:00"}