{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:5BQ4U5IMOZUBF4RE3FYELYUVQB","short_pith_number":"pith:5BQ4U5IM","canonical_record":{"source":{"id":"2608.07733","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.DC","submitted_at":"2026-08-07T19:55:45Z","cross_cats_sorted":["cs.AI","cs.AR","cs.LG","cs.PF"],"title_canon_sha256":"67c059f8806bfe9c425d652c241a81ba528d2be428963a34de30526b85a57a9b","abstract_canon_sha256":"d94107ac7783ccdb77c777b8dae205a3144db9932a7fd7373e1196d69103171d"},"schema_version":"1.0"},"canonical_sha256":"e861ca750c766812f224d97045e295807e12a029297dc98704bc48fe34c2ccb3","source":{"kind":"arxiv","id":"2608.07733","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2608.07733","created_at":"2026-08-11T00:15:49Z"},{"alias_kind":"arxiv_version","alias_value":"2608.07733v1","created_at":"2026-08-11T00:15:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.07733","created_at":"2026-08-11T00:15:49Z"},{"alias_kind":"pith_short_12","alias_value":"5BQ4U5IMOZUB","created_at":"2026-08-11T00:15:49Z"},{"alias_kind":"pith_short_16","alias_value":"5BQ4U5IMOZUBF4RE","created_at":"2026-08-11T00:15:49Z"},{"alias_kind":"pith_short_8","alias_value":"5BQ4U5IM","created_at":"2026-08-11T00:15:49Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:5BQ4U5IMOZUBF4RE3FYELYUVQB","target":"record","payload":{"canonical_record":{"source":{"id":"2608.07733","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.DC","submitted_at":"2026-08-07T19:55:45Z","cross_cats_sorted":["cs.AI","cs.AR","cs.LG","cs.PF"],"title_canon_sha256":"67c059f8806bfe9c425d652c241a81ba528d2be428963a34de30526b85a57a9b","abstract_canon_sha256":"d94107ac7783ccdb77c777b8dae205a3144db9932a7fd7373e1196d69103171d"},"schema_version":"1.0"},"canonical_sha256":"e861ca750c766812f224d97045e295807e12a029297dc98704bc48fe34c2ccb3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-08-11T00:15:49.356818Z","signature_b64":"185rElJLuOomsjhhtyNAP9e6yzILyRMyj4n/3dcvIrufJV+TY8Igz3nvCS+THIsiD3hFB/SL4XUdOwYATZQ+Dg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e861ca750c766812f224d97045e295807e12a029297dc98704bc48fe34c2ccb3","last_reissued_at":"2026-08-11T00:15:49.354490Z","signature_status":"signed_v1","first_computed_at":"2026-08-11T00:15:49.354490Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2608.07733","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":"2026-08-11T00:15:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZvFlyfUrdYIr6+pT73s8zN8TbwBlZuDX+5ZnWxUNU6wOxsyV6tmhJ9v0A/JpmmyPleHc/FJijw3R2xkTOKOeBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T04:06:18.527602Z"},"content_sha256":"0f8b946888768386b2613928ecf14856e44cc9724aa222ae32d0e155bc42de4b","schema_version":"1.0","event_id":"sha256:0f8b946888768386b2613928ecf14856e44cc9724aa222ae32d0e155bc42de4b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:5BQ4U5IMOZUBF4RE3FYELYUVQB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"LGNNIC: Acceleration of Large-Scale GNN Training using SmartNICs","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.AR","cs.LG","cs.PF"],"primary_cat":"cs.DC","authors_text":"Aditya Dhakal, Avi Mendelson, Dejan Milojicic, Liad Gerstman","submitted_at":"2026-08-07T19:55:45Z","abstract_excerpt":"Graph Neural Networks (GNNs) are widely used across domains such as natural sciences, social network analysis, chip design, and recommendation systems. However, as graph sizes grow, storing and processing them entirely on a single-node CPU-GPU system becomes increasingly impractical. A promising approach is to distribute the graph across multiple remote memory nodes, though this introduces a major bottleneck: inter-node network congestion during training. To address this, we propose LGNNIC, a novel inter-node system architecture that leverages SmartNICs co-located with remote memory nodes-a co"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.07733","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/2608.07733/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":"2026-08-11T00:15:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/Qo30KxSVBvR4W37rmn4P84ENw5CEsWKpZ19pjhpglpENLTYiUA0vFsK+FufFmA0fp/vm/CNelbCaeaX9IMGDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T04:06:18.528168Z"},"content_sha256":"6e28f8c70d01c4e0adb68a4035b50470ee083d2d0dd7aee138f60652c72ab5f6","schema_version":"1.0","event_id":"sha256:6e28f8c70d01c4e0adb68a4035b50470ee083d2d0dd7aee138f60652c72ab5f6"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5BQ4U5IMOZUBF4RE3FYELYUVQB/bundle.json","state_url":"https://pith.science/pith/5BQ4U5IMOZUBF4RE3FYELYUVQB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5BQ4U5IMOZUBF4RE3FYELYUVQB/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":"2026-08-17T04:06:18Z","links":{"resolver":"https://pith.science/pith/5BQ4U5IMOZUBF4RE3FYELYUVQB","bundle":"https://pith.science/pith/5BQ4U5IMOZUBF4RE3FYELYUVQB/bundle.json","state":"https://pith.science/pith/5BQ4U5IMOZUBF4RE3FYELYUVQB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5BQ4U5IMOZUBF4RE3FYELYUVQB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:5BQ4U5IMOZUBF4RE3FYELYUVQB","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":"d94107ac7783ccdb77c777b8dae205a3144db9932a7fd7373e1196d69103171d","cross_cats_sorted":["cs.AI","cs.AR","cs.LG","cs.PF"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.DC","submitted_at":"2026-08-07T19:55:45Z","title_canon_sha256":"67c059f8806bfe9c425d652c241a81ba528d2be428963a34de30526b85a57a9b"},"schema_version":"1.0","source":{"id":"2608.07733","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2608.07733","created_at":"2026-08-11T00:15:49Z"},{"alias_kind":"arxiv_version","alias_value":"2608.07733v1","created_at":"2026-08-11T00:15:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.07733","created_at":"2026-08-11T00:15:49Z"},{"alias_kind":"pith_short_12","alias_value":"5BQ4U5IMOZUB","created_at":"2026-08-11T00:15:49Z"},{"alias_kind":"pith_short_16","alias_value":"5BQ4U5IMOZUBF4RE","created_at":"2026-08-11T00:15:49Z"},{"alias_kind":"pith_short_8","alias_value":"5BQ4U5IM","created_at":"2026-08-11T00:15:49Z"}],"graph_snapshots":[{"event_id":"sha256:6e28f8c70d01c4e0adb68a4035b50470ee083d2d0dd7aee138f60652c72ab5f6","target":"graph","created_at":"2026-08-11T00:15:49Z","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/2608.07733/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Graph Neural Networks (GNNs) are widely used across domains such as natural sciences, social network analysis, chip design, and recommendation systems. However, as graph sizes grow, storing and processing them entirely on a single-node CPU-GPU system becomes increasingly impractical. A promising approach is to distribute the graph across multiple remote memory nodes, though this introduces a major bottleneck: inter-node network congestion during training. To address this, we propose LGNNIC, a novel inter-node system architecture that leverages SmartNICs co-located with remote memory nodes-a co","authors_text":"Aditya Dhakal, Avi Mendelson, Dejan Milojicic, Liad Gerstman","cross_cats":["cs.AI","cs.AR","cs.LG","cs.PF"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.DC","submitted_at":"2026-08-07T19:55:45Z","title":"LGNNIC: Acceleration of Large-Scale GNN Training using SmartNICs"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.07733","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":"sha256:0f8b946888768386b2613928ecf14856e44cc9724aa222ae32d0e155bc42de4b","target":"record","created_at":"2026-08-11T00:15:49Z","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":"d94107ac7783ccdb77c777b8dae205a3144db9932a7fd7373e1196d69103171d","cross_cats_sorted":["cs.AI","cs.AR","cs.LG","cs.PF"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.DC","submitted_at":"2026-08-07T19:55:45Z","title_canon_sha256":"67c059f8806bfe9c425d652c241a81ba528d2be428963a34de30526b85a57a9b"},"schema_version":"1.0","source":{"id":"2608.07733","kind":"arxiv","version":1}},"canonical_sha256":"e861ca750c766812f224d97045e295807e12a029297dc98704bc48fe34c2ccb3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e861ca750c766812f224d97045e295807e12a029297dc98704bc48fe34c2ccb3","first_computed_at":"2026-08-11T00:15:49.354490Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-08-11T00:15:49.354490Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"185rElJLuOomsjhhtyNAP9e6yzILyRMyj4n/3dcvIrufJV+TY8Igz3nvCS+THIsiD3hFB/SL4XUdOwYATZQ+Dg==","signature_status":"signed_v1","signed_at":"2026-08-11T00:15:49.356818Z","signed_message":"canonical_sha256_bytes"},"source_id":"2608.07733","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0f8b946888768386b2613928ecf14856e44cc9724aa222ae32d0e155bc42de4b","sha256:6e28f8c70d01c4e0adb68a4035b50470ee083d2d0dd7aee138f60652c72ab5f6"],"state_sha256":"c008765c6d14f2779ccfe41a215e6c5eeee8d3cf203fb17047691d50d7b31925"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GCc+tloXOK338AwJm9xTj/1HK/FJ+MOkPxeis0HzAE8tpnseIUlhDjHiuVbFFmDdufiEaOGKOSih9Q88wyMMBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-17T04:06:18.532920Z","bundle_sha256":"b72fbdc64998bb81bb79fc0cb815cbdacc4be92118be5ba544107718b9bf5e05"}}