{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:AR7CDMUQHVHWHQ5MBMZYZQROZH","short_pith_number":"pith:AR7CDMUQ","schema_version":"1.0","canonical_sha256":"047e21b2903d4f63c3ac0b338cc22ec9d8a8d2c7aca3c56ea374004a98e8c422","source":{"kind":"arxiv","id":"2403.07112","version":1},"attestation_state":"computed","paper":{"title":"Parameterized Task Graph Scheduling Algorithm for Comparing Algorithmic Components","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.DC","authors_text":"Bhaskar Krishnamachari, Ebrahim Hirani, Jared Coleman, Ravi Vivek Agrawal","submitted_at":"2024-03-11T19:05:59Z","abstract_excerpt":"Scheduling distributed applications modeled as directed, acyclic task graphs to run on heterogeneous compute networks is a fundamental (NP-Hard) problem in distributed computing for which many heuristic algorithms have been proposed over the past decades. Many of these algorithms fall under the list-scheduling paradigm, whereby the algorithm first computes priorities for the tasks and then schedules them greedily to the compute node that minimizes some cost function. Thus, many algorithms differ from each other only in a few key components (e.g., the way they prioritize tasks, their cost funct"},"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":"2403.07112","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.DC","submitted_at":"2024-03-11T19:05:59Z","cross_cats_sorted":[],"title_canon_sha256":"a118b908d28d90fbaa19f5cabc5e6932264cb792b3f549c069c96df2e14b8020","abstract_canon_sha256":"96c74a59a47334dcb8be64b1bcf933ecce80f0807ddd46dd4316692bb89d4ac8"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:54:59.232847Z","signature_b64":"dVi/6Hkyhjfdf3c357t2b4bz5VRipimzfAkzBs9wA3lfBTi08Z8xV278jVvwnKGFxDzoDmXw7ZJFq+wLkYz1Aw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"047e21b2903d4f63c3ac0b338cc22ec9d8a8d2c7aca3c56ea374004a98e8c422","last_reissued_at":"2026-07-05T07:54:59.232087Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:54:59.232087Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Parameterized Task Graph Scheduling Algorithm for Comparing Algorithmic Components","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.DC","authors_text":"Bhaskar Krishnamachari, Ebrahim Hirani, Jared Coleman, Ravi Vivek Agrawal","submitted_at":"2024-03-11T19:05:59Z","abstract_excerpt":"Scheduling distributed applications modeled as directed, acyclic task graphs to run on heterogeneous compute networks is a fundamental (NP-Hard) problem in distributed computing for which many heuristic algorithms have been proposed over the past decades. Many of these algorithms fall under the list-scheduling paradigm, whereby the algorithm first computes priorities for the tasks and then schedules them greedily to the compute node that minimizes some cost function. Thus, many algorithms differ from each other only in a few key components (e.g., the way they prioritize tasks, their cost funct"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.07112","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/2403.07112/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":"2403.07112","created_at":"2026-07-05T07:54:59.232339+00:00"},{"alias_kind":"arxiv_version","alias_value":"2403.07112v1","created_at":"2026-07-05T07:54:59.232339+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.07112","created_at":"2026-07-05T07:54:59.232339+00:00"},{"alias_kind":"pith_short_12","alias_value":"AR7CDMUQHVHW","created_at":"2026-07-05T07:54:59.232339+00:00"},{"alias_kind":"pith_short_16","alias_value":"AR7CDMUQHVHWHQ5M","created_at":"2026-07-05T07:54:59.232339+00:00"},{"alias_kind":"pith_short_8","alias_value":"AR7CDMUQ","created_at":"2026-07-05T07:54:59.232339+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2605.01094","citing_title":"ncsim: A Lightweight Simulator for Networked Edge Computing with Wireless Interference Modeling","ref_index":16,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/AR7CDMUQHVHWHQ5MBMZYZQROZH","json":"https://pith.science/pith/AR7CDMUQHVHWHQ5MBMZYZQROZH.json","graph_json":"https://pith.science/api/pith-number/AR7CDMUQHVHWHQ5MBMZYZQROZH/graph.json","events_json":"https://pith.science/api/pith-number/AR7CDMUQHVHWHQ5MBMZYZQROZH/events.json","paper":"https://pith.science/paper/AR7CDMUQ"},"agent_actions":{"view_html":"https://pith.science/pith/AR7CDMUQHVHWHQ5MBMZYZQROZH","download_json":"https://pith.science/pith/AR7CDMUQHVHWHQ5MBMZYZQROZH.json","view_paper":"https://pith.science/paper/AR7CDMUQ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2403.07112&json=true","fetch_graph":"https://pith.science/api/pith-number/AR7CDMUQHVHWHQ5MBMZYZQROZH/graph.json","fetch_events":"https://pith.science/api/pith-number/AR7CDMUQHVHWHQ5MBMZYZQROZH/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/AR7CDMUQHVHWHQ5MBMZYZQROZH/action/timestamp_anchor","attest_storage":"https://pith.science/pith/AR7CDMUQHVHWHQ5MBMZYZQROZH/action/storage_attestation","attest_author":"https://pith.science/pith/AR7CDMUQHVHWHQ5MBMZYZQROZH/action/author_attestation","sign_citation":"https://pith.science/pith/AR7CDMUQHVHWHQ5MBMZYZQROZH/action/citation_signature","submit_replication":"https://pith.science/pith/AR7CDMUQHVHWHQ5MBMZYZQROZH/action/replication_record"}},"created_at":"2026-07-05T07:54:59.232339+00:00","updated_at":"2026-07-05T07:54:59.232339+00:00"}