{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:TVRU2JGUQAY4MK4JOGUXBRFWFJ","short_pith_number":"pith:TVRU2JGU","canonical_record":{"source":{"id":"2406.19580","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.AR","submitted_at":"2024-06-28T00:05:53Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"4a6d194b45d1ea1da2fb9f820864cfe27e026ad1e8deb0866ba91c749505d432","abstract_canon_sha256":"28169dad315a657351ffc35b93f8e59bc11d48340cbaff14b2a1f68968a204ab"},"schema_version":"1.0"},"canonical_sha256":"9d634d24d48031c62b8971a970c4b62a4c0a4fce31460f2001707b8621791404","source":{"kind":"arxiv","id":"2406.19580","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.19580","created_at":"2026-07-05T11:18:13Z"},{"alias_kind":"arxiv_version","alias_value":"2406.19580v2","created_at":"2026-07-05T11:18:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.19580","created_at":"2026-07-05T11:18:13Z"},{"alias_kind":"pith_short_12","alias_value":"TVRU2JGUQAY4","created_at":"2026-07-05T11:18:13Z"},{"alias_kind":"pith_short_16","alias_value":"TVRU2JGUQAY4MK4J","created_at":"2026-07-05T11:18:13Z"},{"alias_kind":"pith_short_8","alias_value":"TVRU2JGU","created_at":"2026-07-05T11:18:13Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:TVRU2JGUQAY4MK4JOGUXBRFWFJ","target":"record","payload":{"canonical_record":{"source":{"id":"2406.19580","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.AR","submitted_at":"2024-06-28T00:05:53Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"4a6d194b45d1ea1da2fb9f820864cfe27e026ad1e8deb0866ba91c749505d432","abstract_canon_sha256":"28169dad315a657351ffc35b93f8e59bc11d48340cbaff14b2a1f68968a204ab"},"schema_version":"1.0"},"canonical_sha256":"9d634d24d48031c62b8971a970c4b62a4c0a4fce31460f2001707b8621791404","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:18:13.055784Z","signature_b64":"sepEWS56nMOSuZ0YiKHymVbTvBH048d/BFQdDzndV05aWeieTG/s5HMIBRXMp8j8lXn7MWVBY0W4YwRyCbFNDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9d634d24d48031c62b8971a970c4b62a4c0a4fce31460f2001707b8621791404","last_reissued_at":"2026-07-05T11:18:13.055376Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:18:13.055376Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2406.19580","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:18:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uIC7/sIAraj32nI7fHt9V4FbzwvC+Bg0uBea1BXxYDAnFzEr7X8rNJF6J6D/4Y4YJYY16MM4SeWi3fXfAN4pDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T08:01:19.110023Z"},"content_sha256":"8e899fd7f271a97fc39675adc12bf7bd1dc31af31cd8ac27f537aac6291e122f","schema_version":"1.0","event_id":"sha256:8e899fd7f271a97fc39675adc12bf7bd1dc31af31cd8ac27f537aac6291e122f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:TVRU2JGUQAY4MK4JOGUXBRFWFJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"FRED: Flexible REduction-Distribution Interconnect and Communication Implementation for Wafer-Scale Distributed Training of DNN Models","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.AR","authors_text":"Puneet Gupta, Saeed Rashidi, Sudarshan Srinivasan, Tushar Krishna, William Won","submitted_at":"2024-06-28T00:05:53Z","abstract_excerpt":"Distributed Deep Neural Network (DNN) training is a technique to reduce the training overhead by distributing the training tasks into multiple accelerators, according to a parallelization strategy. However, high-performance compute and interconnects are needed for maximum speed-up and linear scaling of the system. Wafer-scale systems are a promising technology that allows for tightly integrating high-end accelerators with high-speed wafer-scale interconnects, making it an attractive platform for distributed training. However, the wafer-scale interconnect should offer high performance and flexi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.19580","kind":"arxiv","version":2},"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/2406.19580/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":"2026-07-05T11:18:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"58esobL8MTsT1j9FUShVLVaI1+1R5CDrjzM7yDRvgUA+F/O4Qb/SAyhukd01c2MpRpoEFZrHKvyr0G+DuZLECA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T08:01:19.110618Z"},"content_sha256":"6d7401e60c9e58a8f739e6a8b46e5130608632acfb28810b9be0a2eb6d302fc0","schema_version":"1.0","event_id":"sha256:6d7401e60c9e58a8f739e6a8b46e5130608632acfb28810b9be0a2eb6d302fc0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TVRU2JGUQAY4MK4JOGUXBRFWFJ/bundle.json","state_url":"https://pith.science/pith/TVRU2JGUQAY4MK4JOGUXBRFWFJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TVRU2JGUQAY4MK4JOGUXBRFWFJ/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":"2026-08-04T08:01:19Z","links":{"resolver":"https://pith.science/pith/TVRU2JGUQAY4MK4JOGUXBRFWFJ","bundle":"https://pith.science/pith/TVRU2JGUQAY4MK4JOGUXBRFWFJ/bundle.json","state":"https://pith.science/pith/TVRU2JGUQAY4MK4JOGUXBRFWFJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TVRU2JGUQAY4MK4JOGUXBRFWFJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:TVRU2JGUQAY4MK4JOGUXBRFWFJ","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":"28169dad315a657351ffc35b93f8e59bc11d48340cbaff14b2a1f68968a204ab","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.AR","submitted_at":"2024-06-28T00:05:53Z","title_canon_sha256":"4a6d194b45d1ea1da2fb9f820864cfe27e026ad1e8deb0866ba91c749505d432"},"schema_version":"1.0","source":{"id":"2406.19580","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.19580","created_at":"2026-07-05T11:18:13Z"},{"alias_kind":"arxiv_version","alias_value":"2406.19580v2","created_at":"2026-07-05T11:18:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.19580","created_at":"2026-07-05T11:18:13Z"},{"alias_kind":"pith_short_12","alias_value":"TVRU2JGUQAY4","created_at":"2026-07-05T11:18:13Z"},{"alias_kind":"pith_short_16","alias_value":"TVRU2JGUQAY4MK4J","created_at":"2026-07-05T11:18:13Z"},{"alias_kind":"pith_short_8","alias_value":"TVRU2JGU","created_at":"2026-07-05T11:18:13Z"}],"graph_snapshots":[{"event_id":"sha256:6d7401e60c9e58a8f739e6a8b46e5130608632acfb28810b9be0a2eb6d302fc0","target":"graph","created_at":"2026-07-05T11:18:13Z","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/2406.19580/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Distributed Deep Neural Network (DNN) training is a technique to reduce the training overhead by distributing the training tasks into multiple accelerators, according to a parallelization strategy. However, high-performance compute and interconnects are needed for maximum speed-up and linear scaling of the system. Wafer-scale systems are a promising technology that allows for tightly integrating high-end accelerators with high-speed wafer-scale interconnects, making it an attractive platform for distributed training. However, the wafer-scale interconnect should offer high performance and flexi","authors_text":"Puneet Gupta, Saeed Rashidi, Sudarshan Srinivasan, Tushar Krishna, William Won","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.AR","submitted_at":"2024-06-28T00:05:53Z","title":"FRED: Flexible REduction-Distribution Interconnect and Communication Implementation for Wafer-Scale Distributed Training of DNN Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.19580","kind":"arxiv","version":2},"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":"sha256:8e899fd7f271a97fc39675adc12bf7bd1dc31af31cd8ac27f537aac6291e122f","target":"record","created_at":"2026-07-05T11:18:13Z","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":"28169dad315a657351ffc35b93f8e59bc11d48340cbaff14b2a1f68968a204ab","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.AR","submitted_at":"2024-06-28T00:05:53Z","title_canon_sha256":"4a6d194b45d1ea1da2fb9f820864cfe27e026ad1e8deb0866ba91c749505d432"},"schema_version":"1.0","source":{"id":"2406.19580","kind":"arxiv","version":2}},"canonical_sha256":"9d634d24d48031c62b8971a970c4b62a4c0a4fce31460f2001707b8621791404","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9d634d24d48031c62b8971a970c4b62a4c0a4fce31460f2001707b8621791404","first_computed_at":"2026-07-05T11:18:13.055376Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:18:13.055376Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"sepEWS56nMOSuZ0YiKHymVbTvBH048d/BFQdDzndV05aWeieTG/s5HMIBRXMp8j8lXn7MWVBY0W4YwRyCbFNDA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:18:13.055784Z","signed_message":"canonical_sha256_bytes"},"source_id":"2406.19580","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8e899fd7f271a97fc39675adc12bf7bd1dc31af31cd8ac27f537aac6291e122f","sha256:6d7401e60c9e58a8f739e6a8b46e5130608632acfb28810b9be0a2eb6d302fc0"],"state_sha256":"a5f905b2b0da99c20f8c9af978242b86fc2130dcabd886becf8ff0849173551d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cZQWDTsW9KN5W4xAPsIfvV7Q9kEWZ7hC+e739R3V6Rj50pMDgIjlUUDKcFKJOV/ULJs26xkxFLqExyHjr0joAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T08:01:19.114741Z","bundle_sha256":"b08101be7ebe77fc2cae9ef3b67d7a1330cc552efd829d9e6f05e612f4f7e6bb"}}