{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:FUXYSSH6JNEELDARLMWMUTR4VX","short_pith_number":"pith:FUXYSSH6","canonical_record":{"source":{"id":"1907.11612","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-07-26T15:07:49Z","cross_cats_sorted":["cs.DC","stat.ML"],"title_canon_sha256":"9d7f6136dc5745c9a3f2662f8a0b85c31086f49767cd88caf9003c50dfdd3c95","abstract_canon_sha256":"9e435c7ee0074c58dc63cf28a065fc7fa3e7afcf5c384d639aa6af12f6df4d6b"},"schema_version":"1.0"},"canonical_sha256":"2d2f8948fe4b48458c115b2cca4e3cadf88d042a52bfac4a083a838da6af1317","source":{"kind":"arxiv","id":"1907.11612","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.11612","created_at":"2026-07-05T01:42:52Z"},{"alias_kind":"arxiv_version","alias_value":"1907.11612v3","created_at":"2026-07-05T01:42:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.11612","created_at":"2026-07-05T01:42:52Z"},{"alias_kind":"pith_short_12","alias_value":"FUXYSSH6JNEE","created_at":"2026-07-05T01:42:52Z"},{"alias_kind":"pith_short_16","alias_value":"FUXYSSH6JNEELDAR","created_at":"2026-07-05T01:42:52Z"},{"alias_kind":"pith_short_8","alias_value":"FUXYSSH6","created_at":"2026-07-05T01:42:52Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:FUXYSSH6JNEELDARLMWMUTR4VX","target":"record","payload":{"canonical_record":{"source":{"id":"1907.11612","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-07-26T15:07:49Z","cross_cats_sorted":["cs.DC","stat.ML"],"title_canon_sha256":"9d7f6136dc5745c9a3f2662f8a0b85c31086f49767cd88caf9003c50dfdd3c95","abstract_canon_sha256":"9e435c7ee0074c58dc63cf28a065fc7fa3e7afcf5c384d639aa6af12f6df4d6b"},"schema_version":"1.0"},"canonical_sha256":"2d2f8948fe4b48458c115b2cca4e3cadf88d042a52bfac4a083a838da6af1317","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:42:52.098038Z","signature_b64":"J90WMnRqcLIXDQA4633f26BrZ0KzDCIY5IyRa2NGVOQxgx/IkpH0CHEycY41ESlNHA4R+UAubh5H3OrnRfg0AQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2d2f8948fe4b48458c115b2cca4e3cadf88d042a52bfac4a083a838da6af1317","last_reissued_at":"2026-07-05T01:42:52.097500Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:42:52.097500Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1907.11612","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T01:42:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ORfaDvZmYjIHkktc0N0HlcOemnamWp332c+pIAYvEMg9VzjByvMMJoOxJ5lJQqchX9tuUKuru3iOVcswNSnrAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T17:54:43.041945Z"},"content_sha256":"3a3903306ef1cb6cf95aec207b590c3826c5fe7f0223e6ae7d07d7e3fa6d5c95","schema_version":"1.0","event_id":"sha256:3a3903306ef1cb6cf95aec207b590c3826c5fe7f0223e6ae7d07d7e3fa6d5c95"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:FUXYSSH6JNEELDARLMWMUTR4VX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Taming Momentum in a Distributed Asynchronous Environment","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DC","stat.ML"],"primary_cat":"cs.LG","authors_text":"Assaf Schuster, Ido Hakimi, Moshe Gabel, Saar Barkai","submitted_at":"2019-07-26T15:07:49Z","abstract_excerpt":"Although distributed computing can significantly reduce the training time of deep neural networks, scaling the training process while maintaining high efficiency and final accuracy is challenging. Distributed asynchronous training enjoys near-linear speedup, but asynchrony causes gradient staleness - the main difficulty in scaling stochastic gradient descent to large clusters. Momentum, which is often used to accelerate convergence and escape local minima, exacerbates the gradient staleness, thereby hindering convergence. We propose DANA: a novel technique for asynchronous distributed SGD with"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.11612","kind":"arxiv","version":3},"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/1907.11612/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T01:42:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AH8CLhcaLJBc2SO05y5bKRn3ZWGFoTDpTxzaM6iK2k4qEsaeglYDq6C0uyZV6Bb4yZcUv9TIesiaConS4fpuAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T17:54:43.042660Z"},"content_sha256":"3e3e85b1d4c54dcdf01074aa01179eba020ccbcc80eca16e81716b60a233e36d","schema_version":"1.0","event_id":"sha256:3e3e85b1d4c54dcdf01074aa01179eba020ccbcc80eca16e81716b60a233e36d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/FUXYSSH6JNEELDARLMWMUTR4VX/bundle.json","state_url":"https://pith.science/pith/FUXYSSH6JNEELDARLMWMUTR4VX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/FUXYSSH6JNEELDARLMWMUTR4VX/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-18T17:54:43Z","links":{"resolver":"https://pith.science/pith/FUXYSSH6JNEELDARLMWMUTR4VX","bundle":"https://pith.science/pith/FUXYSSH6JNEELDARLMWMUTR4VX/bundle.json","state":"https://pith.science/pith/FUXYSSH6JNEELDARLMWMUTR4VX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/FUXYSSH6JNEELDARLMWMUTR4VX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:FUXYSSH6JNEELDARLMWMUTR4VX","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":"9e435c7ee0074c58dc63cf28a065fc7fa3e7afcf5c384d639aa6af12f6df4d6b","cross_cats_sorted":["cs.DC","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-07-26T15:07:49Z","title_canon_sha256":"9d7f6136dc5745c9a3f2662f8a0b85c31086f49767cd88caf9003c50dfdd3c95"},"schema_version":"1.0","source":{"id":"1907.11612","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.11612","created_at":"2026-07-05T01:42:52Z"},{"alias_kind":"arxiv_version","alias_value":"1907.11612v3","created_at":"2026-07-05T01:42:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.11612","created_at":"2026-07-05T01:42:52Z"},{"alias_kind":"pith_short_12","alias_value":"FUXYSSH6JNEE","created_at":"2026-07-05T01:42:52Z"},{"alias_kind":"pith_short_16","alias_value":"FUXYSSH6JNEELDAR","created_at":"2026-07-05T01:42:52Z"},{"alias_kind":"pith_short_8","alias_value":"FUXYSSH6","created_at":"2026-07-05T01:42:52Z"}],"graph_snapshots":[{"event_id":"sha256:3e3e85b1d4c54dcdf01074aa01179eba020ccbcc80eca16e81716b60a233e36d","target":"graph","created_at":"2026-07-05T01:42:52Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/1907.11612/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Although distributed computing can significantly reduce the training time of deep neural networks, scaling the training process while maintaining high efficiency and final accuracy is challenging. Distributed asynchronous training enjoys near-linear speedup, but asynchrony causes gradient staleness - the main difficulty in scaling stochastic gradient descent to large clusters. Momentum, which is often used to accelerate convergence and escape local minima, exacerbates the gradient staleness, thereby hindering convergence. We propose DANA: a novel technique for asynchronous distributed SGD with","authors_text":"Assaf Schuster, Ido Hakimi, Moshe Gabel, Saar Barkai","cross_cats":["cs.DC","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-07-26T15:07:49Z","title":"Taming Momentum in a Distributed Asynchronous Environment"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.11612","kind":"arxiv","version":3},"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":"sha256:3a3903306ef1cb6cf95aec207b590c3826c5fe7f0223e6ae7d07d7e3fa6d5c95","target":"record","created_at":"2026-07-05T01:42:52Z","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":"9e435c7ee0074c58dc63cf28a065fc7fa3e7afcf5c384d639aa6af12f6df4d6b","cross_cats_sorted":["cs.DC","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-07-26T15:07:49Z","title_canon_sha256":"9d7f6136dc5745c9a3f2662f8a0b85c31086f49767cd88caf9003c50dfdd3c95"},"schema_version":"1.0","source":{"id":"1907.11612","kind":"arxiv","version":3}},"canonical_sha256":"2d2f8948fe4b48458c115b2cca4e3cadf88d042a52bfac4a083a838da6af1317","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2d2f8948fe4b48458c115b2cca4e3cadf88d042a52bfac4a083a838da6af1317","first_computed_at":"2026-07-05T01:42:52.097500Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:42:52.097500Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"J90WMnRqcLIXDQA4633f26BrZ0KzDCIY5IyRa2NGVOQxgx/IkpH0CHEycY41ESlNHA4R+UAubh5H3OrnRfg0AQ==","signature_status":"signed_v1","signed_at":"2026-07-05T01:42:52.098038Z","signed_message":"canonical_sha256_bytes"},"source_id":"1907.11612","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3a3903306ef1cb6cf95aec207b590c3826c5fe7f0223e6ae7d07d7e3fa6d5c95","sha256:3e3e85b1d4c54dcdf01074aa01179eba020ccbcc80eca16e81716b60a233e36d"],"state_sha256":"a7493b1b3b2f76020dc8cf168315b0c5d6a4f75ea8d9e0a1770b4fe28a8444bf"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pFLxP7CGy+/3gkdXkc/e32JWWRaJ0djaQ/iIisCSCj840ZH4kFZuTp5K1r6Tt+MSz1el9mLZdtiP72EP3YzBDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-18T17:54:43.048651Z","bundle_sha256":"c2ba7d64dae3f1df751aca1ace1d7c4a65ce99640f767905184f83b2124ac09f"}}