{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:ASPBVG2DIDPKNWMKEX4LYHYGIW","short_pith_number":"pith:ASPBVG2D","schema_version":"1.0","canonical_sha256":"049e1a9b4340dea6d98a25f8bc1f06459f79b0ab7ab502c703474a6b8c1d55fe","source":{"kind":"arxiv","id":"1705.09056","version":5},"attestation_state":"computed","paper":{"title":"Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descent","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DC","cs.LG","stat.ML"],"primary_cat":"math.OC","authors_text":"Ce Zhang, Cho-Jui Hsieh, Huan Zhang, Ji Liu, Wei Zhang, Xiangru Lian","submitted_at":"2017-05-25T05:58:17Z","abstract_excerpt":"Most distributed machine learning systems nowadays, including TensorFlow and CNTK, are built in a centralized fashion. One bottleneck of centralized algorithms lies on high communication cost on the central node. Motivated by this, we ask, can decentralized algorithms be faster than its centralized counterpart?\n  Although decentralized PSGD (D-PSGD) algorithms have been studied by the control community, existing analysis and theory do not show any advantage over centralized PSGD (C-PSGD) algorithms, simply assuming the application scenario where only the decentralized network is available. In "},"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":"1705.09056","kind":"arxiv","version":5},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2017-05-25T05:58:17Z","cross_cats_sorted":["cs.DC","cs.LG","stat.ML"],"title_canon_sha256":"037b590ec2909dd9929102b31bd84fa78024e206d2e0418da0ba0343b952fd23","abstract_canon_sha256":"a3178e917c7c092c47a95d2455e1f07b1e6182f164437ffea1d9a234f1175610"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:35:41.238520Z","signature_b64":"3UuoMKmlnx/ctJgkCXgXSb1CYv4ui7bICFi3tO7F19+KRJGIuKhBCpmYQfa26+gtGExY2D5aXu7YtvldnTMUBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"049e1a9b4340dea6d98a25f8bc1f06459f79b0ab7ab502c703474a6b8c1d55fe","last_reissued_at":"2026-05-18T00:35:41.237822Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:35:41.237822Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descent","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DC","cs.LG","stat.ML"],"primary_cat":"math.OC","authors_text":"Ce Zhang, Cho-Jui Hsieh, Huan Zhang, Ji Liu, Wei Zhang, Xiangru Lian","submitted_at":"2017-05-25T05:58:17Z","abstract_excerpt":"Most distributed machine learning systems nowadays, including TensorFlow and CNTK, are built in a centralized fashion. One bottleneck of centralized algorithms lies on high communication cost on the central node. Motivated by this, we ask, can decentralized algorithms be faster than its centralized counterpart?\n  Although decentralized PSGD (D-PSGD) algorithms have been studied by the control community, existing analysis and theory do not show any advantage over centralized PSGD (C-PSGD) algorithms, simply assuming the application scenario where only the decentralized network is available. In "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1705.09056","kind":"arxiv","version":5},"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":"1705.09056","created_at":"2026-05-18T00:35:41.237934+00:00"},{"alias_kind":"arxiv_version","alias_value":"1705.09056v5","created_at":"2026-05-18T00:35:41.237934+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1705.09056","created_at":"2026-05-18T00:35:41.237934+00:00"},{"alias_kind":"pith_short_12","alias_value":"ASPBVG2DIDPK","created_at":"2026-05-18T12:31:08.081275+00:00"},{"alias_kind":"pith_short_16","alias_value":"ASPBVG2DIDPKNWMK","created_at":"2026-05-18T12:31:08.081275+00:00"},{"alias_kind":"pith_short_8","alias_value":"ASPBVG2D","created_at":"2026-05-18T12:31:08.081275+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/ASPBVG2DIDPKNWMKEX4LYHYGIW","json":"https://pith.science/pith/ASPBVG2DIDPKNWMKEX4LYHYGIW.json","graph_json":"https://pith.science/api/pith-number/ASPBVG2DIDPKNWMKEX4LYHYGIW/graph.json","events_json":"https://pith.science/api/pith-number/ASPBVG2DIDPKNWMKEX4LYHYGIW/events.json","paper":"https://pith.science/paper/ASPBVG2D"},"agent_actions":{"view_html":"https://pith.science/pith/ASPBVG2DIDPKNWMKEX4LYHYGIW","download_json":"https://pith.science/pith/ASPBVG2DIDPKNWMKEX4LYHYGIW.json","view_paper":"https://pith.science/paper/ASPBVG2D","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1705.09056&json=true","fetch_graph":"https://pith.science/api/pith-number/ASPBVG2DIDPKNWMKEX4LYHYGIW/graph.json","fetch_events":"https://pith.science/api/pith-number/ASPBVG2DIDPKNWMKEX4LYHYGIW/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ASPBVG2DIDPKNWMKEX4LYHYGIW/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ASPBVG2DIDPKNWMKEX4LYHYGIW/action/storage_attestation","attest_author":"https://pith.science/pith/ASPBVG2DIDPKNWMKEX4LYHYGIW/action/author_attestation","sign_citation":"https://pith.science/pith/ASPBVG2DIDPKNWMKEX4LYHYGIW/action/citation_signature","submit_replication":"https://pith.science/pith/ASPBVG2DIDPKNWMKEX4LYHYGIW/action/replication_record"}},"created_at":"2026-05-18T00:35:41.237934+00:00","updated_at":"2026-05-18T00:35:41.237934+00:00"}