{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:545VV5TWOWRWQ3PEMEMSEYRLMS","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"157b828c47c63f7f239a1f169dfae3ac594b57e6578052e316685ea224ca23a4","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2018-06-08T23:18:08Z","title_canon_sha256":"830960112e779d7ddea5ad989371da375eecfae6c6bc8a1d8c4c79fc80fcfe9d"},"schema_version":"1.0","source":{"id":"1806.03377","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1806.03377","created_at":"2026-05-18T00:13:43Z"},{"alias_kind":"arxiv_version","alias_value":"1806.03377v1","created_at":"2026-05-18T00:13:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1806.03377","created_at":"2026-05-18T00:13:43Z"},{"alias_kind":"pith_short_12","alias_value":"545VV5TWOWRW","created_at":"2026-05-18T12:32:05Z"},{"alias_kind":"pith_short_16","alias_value":"545VV5TWOWRWQ3PE","created_at":"2026-05-18T12:32:05Z"},{"alias_kind":"pith_short_8","alias_value":"545VV5TW","created_at":"2026-05-18T12:32:05Z"}],"graph_snapshots":[{"event_id":"sha256:c714aaebbda2aa361e3b4934f38a7a93c3a3c377ca6ba200b89d17b5063fc901","target":"graph","created_at":"2026-05-18T00:13:43Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"PipeDream is a Deep Neural Network(DNN) training system for GPUs that parallelizes computation by pipelining execution across multiple machines. Its pipeline parallel computing model avoids the slowdowns faced by data-parallel training when large models and/or limited network bandwidth induce high communication-to-computation ratios. PipeDream reduces communication by up to 95% for large DNNs relative to data-parallel training, and allows perfect overlap of communication and computation. PipeDream keeps all available GPUs productive by systematically partitioning DNN layers among them to balan","authors_text":"Aaron Harlap, Amar Phanishayee, Deepak Narayanan, Greg Ganger, Nikhil Devanur, Phil Gibbons, Vivek Seshadri","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2018-06-08T23:18:08Z","title":"PipeDream: Fast and Efficient Pipeline Parallel DNN Training"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.03377","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:ba0bf506232c9e691d0de9b36a50206b17531e5d54331408d4ee07d800b4caea","target":"record","created_at":"2026-05-18T00:13:43Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"157b828c47c63f7f239a1f169dfae3ac594b57e6578052e316685ea224ca23a4","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2018-06-08T23:18:08Z","title_canon_sha256":"830960112e779d7ddea5ad989371da375eecfae6c6bc8a1d8c4c79fc80fcfe9d"},"schema_version":"1.0","source":{"id":"1806.03377","kind":"arxiv","version":1}},"canonical_sha256":"ef3b5af67675a3686de4611922622b6492d374cc5cd6c5e1665e4f3fd206ba91","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ef3b5af67675a3686de4611922622b6492d374cc5cd6c5e1665e4f3fd206ba91","first_computed_at":"2026-05-18T00:13:43.574235Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:13:43.574235Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"bqt1zIVlfxqFa4sHUH13X6yvSi/3ugKDGRMXsxttyKpda/hGZ+io+7Yi1+gQ1KAw4w7GoahtqllO+3WNxPQjAQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:13:43.574928Z","signed_message":"canonical_sha256_bytes"},"source_id":"1806.03377","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ba0bf506232c9e691d0de9b36a50206b17531e5d54331408d4ee07d800b4caea","sha256:c714aaebbda2aa361e3b4934f38a7a93c3a3c377ca6ba200b89d17b5063fc901"],"state_sha256":"b4c7076fef2e46728a5f36b7657b0cb25bcfaf95849cbc6647473582b0e28173"}