{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:HCIUEKOCZK7GBZAYZMPYYDJVV7","short_pith_number":"pith:HCIUEKOC","canonical_record":{"source":{"id":"2103.13262","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-03-24T15:27:15Z","cross_cats_sorted":["cs.CL","cs.DC"],"title_canon_sha256":"420eb6c48720380f673ee115386e26397350d2fc81cf3a26863e8764201dc24e","abstract_canon_sha256":"02d7aa237a82911dc057f44969c8d7d1f6ece3acbefa02c63d94102193813883"},"schema_version":"1.0"},"canonical_sha256":"38914229c2cabe60e418cb1f8c0d35afdf4bb1219fc2c0466ceba69676d4e042","source":{"kind":"arxiv","id":"2103.13262","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2103.13262","created_at":"2026-07-05T02:26:07Z"},{"alias_kind":"arxiv_version","alias_value":"2103.13262v1","created_at":"2026-07-05T02:26:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2103.13262","created_at":"2026-07-05T02:26:07Z"},{"alias_kind":"pith_short_12","alias_value":"HCIUEKOCZK7G","created_at":"2026-07-05T02:26:07Z"},{"alias_kind":"pith_short_16","alias_value":"HCIUEKOCZK7GBZAY","created_at":"2026-07-05T02:26:07Z"},{"alias_kind":"pith_short_8","alias_value":"HCIUEKOC","created_at":"2026-07-05T02:26:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:HCIUEKOCZK7GBZAYZMPYYDJVV7","target":"record","payload":{"canonical_record":{"source":{"id":"2103.13262","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-03-24T15:27:15Z","cross_cats_sorted":["cs.CL","cs.DC"],"title_canon_sha256":"420eb6c48720380f673ee115386e26397350d2fc81cf3a26863e8764201dc24e","abstract_canon_sha256":"02d7aa237a82911dc057f44969c8d7d1f6ece3acbefa02c63d94102193813883"},"schema_version":"1.0"},"canonical_sha256":"38914229c2cabe60e418cb1f8c0d35afdf4bb1219fc2c0466ceba69676d4e042","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:26:07.671155Z","signature_b64":"JO/pxPln58vzvoAz57Prr6mFrMFgfOs8fp3EwT42UeXMkjFF0m2Zj3U7CmUXlA/ADf7+RmbnS16AcdqkXEJ4Dw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"38914229c2cabe60e418cb1f8c0d35afdf4bb1219fc2c0466ceba69676d4e042","last_reissued_at":"2026-07-05T02:26:07.670617Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:26:07.670617Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2103.13262","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":"2026-07-05T02:26:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ShhGwre2/uzhZ8kWsYE3H++4bsWXjCxmImB8mOtyRod2iwwWJD4/dv/s2MLWs0plqUcTLCbKEU44LU+MTXknCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T11:18:06.326515Z"},"content_sha256":"4acf11e1366850929523d3608c9919b323b13dfaf13d69003d422bad687d2589","schema_version":"1.0","event_id":"sha256:4acf11e1366850929523d3608c9919b323b13dfaf13d69003d422bad687d2589"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:HCIUEKOCZK7GBZAYZMPYYDJVV7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"FastMoE: A Fast Mixture-of-Expert Training System","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL","cs.DC"],"primary_cat":"cs.LG","authors_text":"Aohan Zeng, Jiaao He, Jidong Zhai, Jie Tang, Jiezhong Qiu, Zhilin Yang","submitted_at":"2021-03-24T15:27:15Z","abstract_excerpt":"Mixture-of-Expert (MoE) presents a strong potential in enlarging the size of language model to trillions of parameters. However, training trillion-scale MoE requires algorithm and system co-design for a well-tuned high performance distributed training system. Unfortunately, the only existing platform that meets the requirements strongly depends on Google's hardware (TPU) and software (Mesh Tensorflow) stack, and is not open and available to the public, especially GPU and PyTorch communities.\n  In this paper, we present FastMoE, a distributed MoE training system based on PyTorch with common acc"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2103.13262","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/2103.13262/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":"2026-07-05T02:26:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YNXpwVywYAVquQlKFomNEYYEO1Mp/Q4jsJ2tJzG9FbOCsKFS4gJWPxZoRQtlCUTHK5S3EaNk5iMVDgjyj1DzAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T11:18:06.327450Z"},"content_sha256":"bbefc4b43e966674603b46af8585fe49616084d8bf436f5dce3fc7373f1987c5","schema_version":"1.0","event_id":"sha256:bbefc4b43e966674603b46af8585fe49616084d8bf436f5dce3fc7373f1987c5"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HCIUEKOCZK7GBZAYZMPYYDJVV7/bundle.json","state_url":"https://pith.science/pith/HCIUEKOCZK7GBZAYZMPYYDJVV7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HCIUEKOCZK7GBZAYZMPYYDJVV7/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":"2026-08-05T11:18:06Z","links":{"resolver":"https://pith.science/pith/HCIUEKOCZK7GBZAYZMPYYDJVV7","bundle":"https://pith.science/pith/HCIUEKOCZK7GBZAYZMPYYDJVV7/bundle.json","state":"https://pith.science/pith/HCIUEKOCZK7GBZAYZMPYYDJVV7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HCIUEKOCZK7GBZAYZMPYYDJVV7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:HCIUEKOCZK7GBZAYZMPYYDJVV7","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":"02d7aa237a82911dc057f44969c8d7d1f6ece3acbefa02c63d94102193813883","cross_cats_sorted":["cs.CL","cs.DC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-03-24T15:27:15Z","title_canon_sha256":"420eb6c48720380f673ee115386e26397350d2fc81cf3a26863e8764201dc24e"},"schema_version":"1.0","source":{"id":"2103.13262","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2103.13262","created_at":"2026-07-05T02:26:07Z"},{"alias_kind":"arxiv_version","alias_value":"2103.13262v1","created_at":"2026-07-05T02:26:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2103.13262","created_at":"2026-07-05T02:26:07Z"},{"alias_kind":"pith_short_12","alias_value":"HCIUEKOCZK7G","created_at":"2026-07-05T02:26:07Z"},{"alias_kind":"pith_short_16","alias_value":"HCIUEKOCZK7GBZAY","created_at":"2026-07-05T02:26:07Z"},{"alias_kind":"pith_short_8","alias_value":"HCIUEKOC","created_at":"2026-07-05T02:26:07Z"}],"graph_snapshots":[{"event_id":"sha256:bbefc4b43e966674603b46af8585fe49616084d8bf436f5dce3fc7373f1987c5","target":"graph","created_at":"2026-07-05T02:26:07Z","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/2103.13262/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Mixture-of-Expert (MoE) presents a strong potential in enlarging the size of language model to trillions of parameters. However, training trillion-scale MoE requires algorithm and system co-design for a well-tuned high performance distributed training system. Unfortunately, the only existing platform that meets the requirements strongly depends on Google's hardware (TPU) and software (Mesh Tensorflow) stack, and is not open and available to the public, especially GPU and PyTorch communities.\n  In this paper, we present FastMoE, a distributed MoE training system based on PyTorch with common acc","authors_text":"Aohan Zeng, Jiaao He, Jidong Zhai, Jie Tang, Jiezhong Qiu, Zhilin Yang","cross_cats":["cs.CL","cs.DC"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-03-24T15:27:15Z","title":"FastMoE: A Fast Mixture-of-Expert Training System"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2103.13262","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":"sha256:4acf11e1366850929523d3608c9919b323b13dfaf13d69003d422bad687d2589","target":"record","created_at":"2026-07-05T02:26:07Z","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":"02d7aa237a82911dc057f44969c8d7d1f6ece3acbefa02c63d94102193813883","cross_cats_sorted":["cs.CL","cs.DC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-03-24T15:27:15Z","title_canon_sha256":"420eb6c48720380f673ee115386e26397350d2fc81cf3a26863e8764201dc24e"},"schema_version":"1.0","source":{"id":"2103.13262","kind":"arxiv","version":1}},"canonical_sha256":"38914229c2cabe60e418cb1f8c0d35afdf4bb1219fc2c0466ceba69676d4e042","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"38914229c2cabe60e418cb1f8c0d35afdf4bb1219fc2c0466ceba69676d4e042","first_computed_at":"2026-07-05T02:26:07.670617Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:26:07.670617Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"JO/pxPln58vzvoAz57Prr6mFrMFgfOs8fp3EwT42UeXMkjFF0m2Zj3U7CmUXlA/ADf7+RmbnS16AcdqkXEJ4Dw==","signature_status":"signed_v1","signed_at":"2026-07-05T02:26:07.671155Z","signed_message":"canonical_sha256_bytes"},"source_id":"2103.13262","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4acf11e1366850929523d3608c9919b323b13dfaf13d69003d422bad687d2589","sha256:bbefc4b43e966674603b46af8585fe49616084d8bf436f5dce3fc7373f1987c5"],"state_sha256":"604827b551dabd7275d8724f6ba0c17802fe5074dbc17eefd9e3682af714a97c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jzOScZdETV4WNAA3hPguOo3CfSgW1ddNrsDlM9LbWXHcacuM53K3Pp5PtFUGkrRvviyNd+lmecZ5DubVArR6CA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T11:18:06.341054Z","bundle_sha256":"fdc22834db443b3f1ec8509ae18d644f3d01dfa2cad9ed0c35d32ac7f933f4b2"}}