{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:2KGEE7LVQZ4P7AZ4VOBG4XOWE6","short_pith_number":"pith:2KGEE7LV","canonical_record":{"source":{"id":"2306.02267","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2023-06-04T05:47:32Z","cross_cats_sorted":[],"title_canon_sha256":"823bff92d0ff36355b6c45180b538ea8b38e2e82b966b33396d6feaa49e47bfe","abstract_canon_sha256":"879bfc693e7dd07fa0f6864aecd289735093e998dd88e2c9c2538a5735893cf0"},"schema_version":"1.0"},"canonical_sha256":"d28c427d758678ff833cab826e5dd6278548eb5b7d49110a350c0b96a4f90c47","source":{"kind":"arxiv","id":"2306.02267","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2306.02267","created_at":"2026-07-05T06:17:15Z"},{"alias_kind":"arxiv_version","alias_value":"2306.02267v1","created_at":"2026-07-05T06:17:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2306.02267","created_at":"2026-07-05T06:17:15Z"},{"alias_kind":"pith_short_12","alias_value":"2KGEE7LVQZ4P","created_at":"2026-07-05T06:17:15Z"},{"alias_kind":"pith_short_16","alias_value":"2KGEE7LVQZ4P7AZ4","created_at":"2026-07-05T06:17:15Z"},{"alias_kind":"pith_short_8","alias_value":"2KGEE7LV","created_at":"2026-07-05T06:17:15Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:2KGEE7LVQZ4P7AZ4VOBG4XOWE6","target":"record","payload":{"canonical_record":{"source":{"id":"2306.02267","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2023-06-04T05:47:32Z","cross_cats_sorted":[],"title_canon_sha256":"823bff92d0ff36355b6c45180b538ea8b38e2e82b966b33396d6feaa49e47bfe","abstract_canon_sha256":"879bfc693e7dd07fa0f6864aecd289735093e998dd88e2c9c2538a5735893cf0"},"schema_version":"1.0"},"canonical_sha256":"d28c427d758678ff833cab826e5dd6278548eb5b7d49110a350c0b96a4f90c47","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:17:15.098793Z","signature_b64":"O0PFwPaZyBfhxmQvPij6Ujvdp89IF0f5+SfIF/gfCA9ECUQgTn7y6Gi0bPZBOf5dHcZfglV2YskT6B5+9f4oBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d28c427d758678ff833cab826e5dd6278548eb5b7d49110a350c0b96a4f90c47","last_reissued_at":"2026-07-05T06:17:15.098397Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:17:15.098397Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2306.02267","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T06:17:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zEdvDG54e+gjeTYlYGVmRZIMchKiRiSRzA0917QCJulpAQ21JWe9HG3S/kGVZfaPqKKTujjrnfum8qRBVCUkBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T19:40:17.515531Z"},"content_sha256":"9bc559a829ad9f63d495a9fd0b137f2798f41e2c49ae83ce7b16db451c97b146","schema_version":"1.0","event_id":"sha256:9bc559a829ad9f63d495a9fd0b137f2798f41e2c49ae83ce7b16db451c97b146"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:2KGEE7LVQZ4P7AZ4VOBG4XOWE6","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Proteus: Simulating the Performance of Distributed DNN Training","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DC","authors_text":"Dahua Lin, Jiangfei Duan, Ping Xu, Shengen Yan, Xingcheng Zhang, Xiuhong Li, Yun Liang","submitted_at":"2023-06-04T05:47:32Z","abstract_excerpt":"DNN models are becoming increasingly larger to achieve unprecedented accuracy, and the accompanying increased computation and memory requirements necessitate the employment of massive clusters and elaborate parallelization strategies to accelerate DNN training. In order to better optimize the performance and analyze the cost, it is indispensable to model the training throughput of distributed DNN training. However, complex parallelization strategies and the resulting complex runtime behaviors make it challenging to construct an accurate performance model. In this paper, we present Proteus, the"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2306.02267","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/2306.02267/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":"2026-07-05T06:17:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jLLPPjCbQ7VDvOir6dKK1HKMMKjsAJMGAw3NyzBDzOjDQXD/PB09xXTawcNxWaILkRGpLHLQXKJTnp5OZ+BpAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T19:40:17.516578Z"},"content_sha256":"0fa1c60462e4b582911b97ca3d846c236f2f942f26302716347d462a57f6f03e","schema_version":"1.0","event_id":"sha256:0fa1c60462e4b582911b97ca3d846c236f2f942f26302716347d462a57f6f03e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2KGEE7LVQZ4P7AZ4VOBG4XOWE6/bundle.json","state_url":"https://pith.science/pith/2KGEE7LVQZ4P7AZ4VOBG4XOWE6/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2KGEE7LVQZ4P7AZ4VOBG4XOWE6/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":"2026-08-10T19:40:17Z","links":{"resolver":"https://pith.science/pith/2KGEE7LVQZ4P7AZ4VOBG4XOWE6","bundle":"https://pith.science/pith/2KGEE7LVQZ4P7AZ4VOBG4XOWE6/bundle.json","state":"https://pith.science/pith/2KGEE7LVQZ4P7AZ4VOBG4XOWE6/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2KGEE7LVQZ4P7AZ4VOBG4XOWE6/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:2KGEE7LVQZ4P7AZ4VOBG4XOWE6","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":"879bfc693e7dd07fa0f6864aecd289735093e998dd88e2c9c2538a5735893cf0","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2023-06-04T05:47:32Z","title_canon_sha256":"823bff92d0ff36355b6c45180b538ea8b38e2e82b966b33396d6feaa49e47bfe"},"schema_version":"1.0","source":{"id":"2306.02267","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2306.02267","created_at":"2026-07-05T06:17:15Z"},{"alias_kind":"arxiv_version","alias_value":"2306.02267v1","created_at":"2026-07-05T06:17:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2306.02267","created_at":"2026-07-05T06:17:15Z"},{"alias_kind":"pith_short_12","alias_value":"2KGEE7LVQZ4P","created_at":"2026-07-05T06:17:15Z"},{"alias_kind":"pith_short_16","alias_value":"2KGEE7LVQZ4P7AZ4","created_at":"2026-07-05T06:17:15Z"},{"alias_kind":"pith_short_8","alias_value":"2KGEE7LV","created_at":"2026-07-05T06:17:15Z"}],"graph_snapshots":[{"event_id":"sha256:0fa1c60462e4b582911b97ca3d846c236f2f942f26302716347d462a57f6f03e","target":"graph","created_at":"2026-07-05T06:17:15Z","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/2306.02267/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"DNN models are becoming increasingly larger to achieve unprecedented accuracy, and the accompanying increased computation and memory requirements necessitate the employment of massive clusters and elaborate parallelization strategies to accelerate DNN training. In order to better optimize the performance and analyze the cost, it is indispensable to model the training throughput of distributed DNN training. However, complex parallelization strategies and the resulting complex runtime behaviors make it challenging to construct an accurate performance model. In this paper, we present Proteus, the","authors_text":"Dahua Lin, Jiangfei Duan, Ping Xu, Shengen Yan, Xingcheng Zhang, Xiuhong Li, Yun Liang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2023-06-04T05:47:32Z","title":"Proteus: Simulating the Performance of Distributed DNN Training"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2306.02267","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":"sha256:9bc559a829ad9f63d495a9fd0b137f2798f41e2c49ae83ce7b16db451c97b146","target":"record","created_at":"2026-07-05T06:17:15Z","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":"879bfc693e7dd07fa0f6864aecd289735093e998dd88e2c9c2538a5735893cf0","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2023-06-04T05:47:32Z","title_canon_sha256":"823bff92d0ff36355b6c45180b538ea8b38e2e82b966b33396d6feaa49e47bfe"},"schema_version":"1.0","source":{"id":"2306.02267","kind":"arxiv","version":1}},"canonical_sha256":"d28c427d758678ff833cab826e5dd6278548eb5b7d49110a350c0b96a4f90c47","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d28c427d758678ff833cab826e5dd6278548eb5b7d49110a350c0b96a4f90c47","first_computed_at":"2026-07-05T06:17:15.098397Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:17:15.098397Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"O0PFwPaZyBfhxmQvPij6Ujvdp89IF0f5+SfIF/gfCA9ECUQgTn7y6Gi0bPZBOf5dHcZfglV2YskT6B5+9f4oBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T06:17:15.098793Z","signed_message":"canonical_sha256_bytes"},"source_id":"2306.02267","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9bc559a829ad9f63d495a9fd0b137f2798f41e2c49ae83ce7b16db451c97b146","sha256:0fa1c60462e4b582911b97ca3d846c236f2f942f26302716347d462a57f6f03e"],"state_sha256":"bdd76478a886dbec51c6255a0cc1a7164ce13d7d0b6f4613183a18f6c9218958"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Pbfovuomw5+jgQtgU2ZRC1H9Z+Ryglwl/Qx/vvT9CAwrL78Yyz73HoXZ/owasqFnhDiIr3NgoVk9isiLz0ChDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T19:40:17.522332Z","bundle_sha256":"c1bd63ebadcb25dfe4c32d499b732fee551c6c2911c2a607c0548cc315717cf8"}}