{"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"}