{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:YOEQOK37B4I7H6OTQZWAEDP6DT","short_pith_number":"pith:YOEQOK37","canonical_record":{"source":{"id":"2110.09524","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-10-18T12:51:50Z","cross_cats_sorted":["cs.PF"],"title_canon_sha256":"22235096a4900b2dab41465bbed6026c774ec0d1e0061887f7c576c5a17e54c4","abstract_canon_sha256":"dd85b73c98cfed1bdb5dd35bacd8ddbbe48e9f89ad131888e35edebb0f0c62c2"},"schema_version":"1.0"},"canonical_sha256":"c389072b7f0f11f3f9d3866c020dfe1cc61d3aa8efb3d5ed42b47c3557efa802","source":{"kind":"arxiv","id":"2110.09524","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2110.09524","created_at":"2026-07-05T03:23:30Z"},{"alias_kind":"arxiv_version","alias_value":"2110.09524v1","created_at":"2026-07-05T03:23:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2110.09524","created_at":"2026-07-05T03:23:30Z"},{"alias_kind":"pith_short_12","alias_value":"YOEQOK37B4I7","created_at":"2026-07-05T03:23:30Z"},{"alias_kind":"pith_short_16","alias_value":"YOEQOK37B4I7H6OT","created_at":"2026-07-05T03:23:30Z"},{"alias_kind":"pith_short_8","alias_value":"YOEQOK37","created_at":"2026-07-05T03:23:30Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:YOEQOK37B4I7H6OTQZWAEDP6DT","target":"record","payload":{"canonical_record":{"source":{"id":"2110.09524","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-10-18T12:51:50Z","cross_cats_sorted":["cs.PF"],"title_canon_sha256":"22235096a4900b2dab41465bbed6026c774ec0d1e0061887f7c576c5a17e54c4","abstract_canon_sha256":"dd85b73c98cfed1bdb5dd35bacd8ddbbe48e9f89ad131888e35edebb0f0c62c2"},"schema_version":"1.0"},"canonical_sha256":"c389072b7f0f11f3f9d3866c020dfe1cc61d3aa8efb3d5ed42b47c3557efa802","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:23:30.152498Z","signature_b64":"rEVcHxEADLUaXA6CfaKejYfg/qJB8OzaUqX73cVCq1yTxrVA0zk7bx8cUaEiC2++KqsnheI9LMjJpEU2nMHkBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c389072b7f0f11f3f9d3866c020dfe1cc61d3aa8efb3d5ed42b47c3557efa802","last_reissued_at":"2026-07-05T03:23:30.152014Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:23:30.152014Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2110.09524","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":"2026-07-05T03:23:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Ct9Y3r7oDz60k8qGy7N2uxBxsx1hSFX24MReH/CfkHVO9hiGdoXkx2kl98qwUjO8apMwA1kIH4jbLgLgmafhAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T03:10:26.098763Z"},"content_sha256":"32171d65af5a2ee7914196b2e1137096bcf19ff04a8970c1e938a3c56a42a714","schema_version":"1.0","event_id":"sha256:32171d65af5a2ee7914196b2e1137096bcf19ff04a8970c1e938a3c56a42a714"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:YOEQOK37B4I7H6OTQZWAEDP6DT","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Understanding GNN Computational Graph: A Coordinated Computation, IO, and Memory Perspective","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.PF"],"primary_cat":"cs.LG","authors_text":"Guohao Dai, Guyue Huang, Hengrui Zhang, Yuan Xie, Yufei Ding, Yu Wang, Zhongming Yu","submitted_at":"2021-10-18T12:51:50Z","abstract_excerpt":"Graph Neural Networks (GNNs) have been widely used in various domains, and GNNs with sophisticated computational graph lead to higher latency and larger memory consumption. Optimizing the GNN computational graph suffers from: (1) Redundant neural operator computation. The same data are propagated through the graph structure to perform the same neural operation multiple times in GNNs, leading to redundant computation which accounts for 92.4% of total operators. (2) Inconsistent thread mapping. Efficient thread mapping schemes for vertex-centric and edge-centric operators are different. This inc"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2110.09524","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/2110.09524/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":"2026-07-05T03:23:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DGhMm+P7chLokiWWteu/dTkzfHFmIL06dWn/muJz3C8I8SCXOtrXZ8/ziiNfuHFcIQUSyXNXJnFhM1aWyhFsDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T03:10:26.099053Z"},"content_sha256":"1de75351ad1b101a795f7da690f01061248ede5d3caf3159796ff10c48519b4f","schema_version":"1.0","event_id":"sha256:1de75351ad1b101a795f7da690f01061248ede5d3caf3159796ff10c48519b4f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YOEQOK37B4I7H6OTQZWAEDP6DT/bundle.json","state_url":"https://pith.science/pith/YOEQOK37B4I7H6OTQZWAEDP6DT/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YOEQOK37B4I7H6OTQZWAEDP6DT/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":"2026-08-14T03:10:26Z","links":{"resolver":"https://pith.science/pith/YOEQOK37B4I7H6OTQZWAEDP6DT","bundle":"https://pith.science/pith/YOEQOK37B4I7H6OTQZWAEDP6DT/bundle.json","state":"https://pith.science/pith/YOEQOK37B4I7H6OTQZWAEDP6DT/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YOEQOK37B4I7H6OTQZWAEDP6DT/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:YOEQOK37B4I7H6OTQZWAEDP6DT","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":"dd85b73c98cfed1bdb5dd35bacd8ddbbe48e9f89ad131888e35edebb0f0c62c2","cross_cats_sorted":["cs.PF"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-10-18T12:51:50Z","title_canon_sha256":"22235096a4900b2dab41465bbed6026c774ec0d1e0061887f7c576c5a17e54c4"},"schema_version":"1.0","source":{"id":"2110.09524","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2110.09524","created_at":"2026-07-05T03:23:30Z"},{"alias_kind":"arxiv_version","alias_value":"2110.09524v1","created_at":"2026-07-05T03:23:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2110.09524","created_at":"2026-07-05T03:23:30Z"},{"alias_kind":"pith_short_12","alias_value":"YOEQOK37B4I7","created_at":"2026-07-05T03:23:30Z"},{"alias_kind":"pith_short_16","alias_value":"YOEQOK37B4I7H6OT","created_at":"2026-07-05T03:23:30Z"},{"alias_kind":"pith_short_8","alias_value":"YOEQOK37","created_at":"2026-07-05T03:23:30Z"}],"graph_snapshots":[{"event_id":"sha256:1de75351ad1b101a795f7da690f01061248ede5d3caf3159796ff10c48519b4f","target":"graph","created_at":"2026-07-05T03:23:30Z","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/2110.09524/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Graph Neural Networks (GNNs) have been widely used in various domains, and GNNs with sophisticated computational graph lead to higher latency and larger memory consumption. Optimizing the GNN computational graph suffers from: (1) Redundant neural operator computation. The same data are propagated through the graph structure to perform the same neural operation multiple times in GNNs, leading to redundant computation which accounts for 92.4% of total operators. (2) Inconsistent thread mapping. Efficient thread mapping schemes for vertex-centric and edge-centric operators are different. This inc","authors_text":"Guohao Dai, Guyue Huang, Hengrui Zhang, Yuan Xie, Yufei Ding, Yu Wang, Zhongming Yu","cross_cats":["cs.PF"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-10-18T12:51:50Z","title":"Understanding GNN Computational Graph: A Coordinated Computation, IO, and Memory Perspective"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2110.09524","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":"sha256:32171d65af5a2ee7914196b2e1137096bcf19ff04a8970c1e938a3c56a42a714","target":"record","created_at":"2026-07-05T03:23:30Z","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":"dd85b73c98cfed1bdb5dd35bacd8ddbbe48e9f89ad131888e35edebb0f0c62c2","cross_cats_sorted":["cs.PF"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-10-18T12:51:50Z","title_canon_sha256":"22235096a4900b2dab41465bbed6026c774ec0d1e0061887f7c576c5a17e54c4"},"schema_version":"1.0","source":{"id":"2110.09524","kind":"arxiv","version":1}},"canonical_sha256":"c389072b7f0f11f3f9d3866c020dfe1cc61d3aa8efb3d5ed42b47c3557efa802","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c389072b7f0f11f3f9d3866c020dfe1cc61d3aa8efb3d5ed42b47c3557efa802","first_computed_at":"2026-07-05T03:23:30.152014Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:23:30.152014Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"rEVcHxEADLUaXA6CfaKejYfg/qJB8OzaUqX73cVCq1yTxrVA0zk7bx8cUaEiC2++KqsnheI9LMjJpEU2nMHkBg==","signature_status":"signed_v1","signed_at":"2026-07-05T03:23:30.152498Z","signed_message":"canonical_sha256_bytes"},"source_id":"2110.09524","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:32171d65af5a2ee7914196b2e1137096bcf19ff04a8970c1e938a3c56a42a714","sha256:1de75351ad1b101a795f7da690f01061248ede5d3caf3159796ff10c48519b4f"],"state_sha256":"3b8bebe14dee82bfa83574471661dbe6859b5fa219810a1d5ad7d30a875cea7d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Xrq9yPD1/Jv9aPADxdxDFcOC80WBWLW3Ay6ljrRNUBO7yIIAMCQcqA2dQI6Gc8LNfFlc5SwMqzrH9TqpF0G+CA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-14T03:10:26.102273Z","bundle_sha256":"11ae315de53b8a37566da5aeb05a3ba06ef762e3bd776561fdb3ff69eddc2d93"}}