{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:NXRJOIHUS4HKNO4C3ECNLQZ4O7","short_pith_number":"pith:NXRJOIHU","canonical_record":{"source":{"id":"1708.01159","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2017-08-03T14:33:22Z","cross_cats_sorted":[],"title_canon_sha256":"2f7bc8f7e9cc8f255227e964567168f5c858a24bb0fad380293734b7c0c91b6f","abstract_canon_sha256":"0343eb7d04bce128ba7022fb2c43d99696fc4251816c95b24c68d74d2868fc57"},"schema_version":"1.0"},"canonical_sha256":"6de29720f4970ea6bb82d904d5c33c77f46d0145b044fd7571da9ab66c0fe49c","source":{"kind":"arxiv","id":"1708.01159","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1708.01159","created_at":"2026-05-18T00:38:40Z"},{"alias_kind":"arxiv_version","alias_value":"1708.01159v1","created_at":"2026-05-18T00:38:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1708.01159","created_at":"2026-05-18T00:38:40Z"},{"alias_kind":"pith_short_12","alias_value":"NXRJOIHUS4HK","created_at":"2026-05-18T12:31:34Z"},{"alias_kind":"pith_short_16","alias_value":"NXRJOIHUS4HKNO4C","created_at":"2026-05-18T12:31:34Z"},{"alias_kind":"pith_short_8","alias_value":"NXRJOIHU","created_at":"2026-05-18T12:31:34Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:NXRJOIHUS4HKNO4C3ECNLQZ4O7","target":"record","payload":{"canonical_record":{"source":{"id":"1708.01159","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2017-08-03T14:33:22Z","cross_cats_sorted":[],"title_canon_sha256":"2f7bc8f7e9cc8f255227e964567168f5c858a24bb0fad380293734b7c0c91b6f","abstract_canon_sha256":"0343eb7d04bce128ba7022fb2c43d99696fc4251816c95b24c68d74d2868fc57"},"schema_version":"1.0"},"canonical_sha256":"6de29720f4970ea6bb82d904d5c33c77f46d0145b044fd7571da9ab66c0fe49c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:38:40.492113Z","signature_b64":"dqreLvvVRJd6GuUI3J840q0CXh8abQ0ma7EIMptedL5vMk31YjhwmZs//THXDqz3iI+pJ6tRrQUrgetsPTceCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6de29720f4970ea6bb82d904d5c33c77f46d0145b044fd7571da9ab66c0fe49c","last_reissued_at":"2026-05-18T00:38:40.491726Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:38:40.491726Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1708.01159","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":"2026-05-18T00:38:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KlGMeT0zltgru6CaJc9ZJzNJvuAmhyJxiciwT5vq82UL9PsrGQnZbNjFHaPILC529xwxqN20cuzqbPPzKvfdDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-07T10:46:05.575344Z"},"content_sha256":"ab9388cc08775d1657805d659075b3466cc0c2559f14a5147a14cc7cd17c5951","schema_version":"1.0","event_id":"sha256:ab9388cc08775d1657805d659075b3466cc0c2559f14a5147a14cc7cd17c5951"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:NXRJOIHUS4HKNO4C3ECNLQZ4O7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Using Graph Properties to Speed-up GPU-based Graph Traversal: A Model-driven Approach","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DC","authors_text":"Ana Lucia Varbanescu, Cees de Laat, Merijn Verstraaten","submitted_at":"2017-08-03T14:33:22Z","abstract_excerpt":"While it is well-known and acknowledged that the performance of graph algorithms is heavily dependent on the input data, there has been surprisingly little research to quantify and predict the impact the graph structure has on performance. Parallel graph algorithms, running on many-core systems such as GPUs, are no exception: most research has focused on how to efficiently implement and tune different graph operations on a specific GPU. However, the performance impact of the input graph has only been taken into account indirectly as a result of the graphs used to benchmark the system.\n  In thi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1708.01159","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":""},"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":"2026-05-18T00:38:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2OLs4NtpcjOULT3G72YPBzI/Mw9mMvuSQjWraSlu+qgYbnRgA2Kz1/lbTmIzVsCn6lpXSA/d5Dgya5PcdFlQDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-07T10:46:05.575911Z"},"content_sha256":"77c7a62cee84cb048014a1876346590a73679f020e4ccbf20d208f94113bbef3","schema_version":"1.0","event_id":"sha256:77c7a62cee84cb048014a1876346590a73679f020e4ccbf20d208f94113bbef3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/NXRJOIHUS4HKNO4C3ECNLQZ4O7/bundle.json","state_url":"https://pith.science/pith/NXRJOIHUS4HKNO4C3ECNLQZ4O7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/NXRJOIHUS4HKNO4C3ECNLQZ4O7/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":"2026-06-07T10:46:05Z","links":{"resolver":"https://pith.science/pith/NXRJOIHUS4HKNO4C3ECNLQZ4O7","bundle":"https://pith.science/pith/NXRJOIHUS4HKNO4C3ECNLQZ4O7/bundle.json","state":"https://pith.science/pith/NXRJOIHUS4HKNO4C3ECNLQZ4O7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/NXRJOIHUS4HKNO4C3ECNLQZ4O7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:NXRJOIHUS4HKNO4C3ECNLQZ4O7","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":"0343eb7d04bce128ba7022fb2c43d99696fc4251816c95b24c68d74d2868fc57","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2017-08-03T14:33:22Z","title_canon_sha256":"2f7bc8f7e9cc8f255227e964567168f5c858a24bb0fad380293734b7c0c91b6f"},"schema_version":"1.0","source":{"id":"1708.01159","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1708.01159","created_at":"2026-05-18T00:38:40Z"},{"alias_kind":"arxiv_version","alias_value":"1708.01159v1","created_at":"2026-05-18T00:38:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1708.01159","created_at":"2026-05-18T00:38:40Z"},{"alias_kind":"pith_short_12","alias_value":"NXRJOIHUS4HK","created_at":"2026-05-18T12:31:34Z"},{"alias_kind":"pith_short_16","alias_value":"NXRJOIHUS4HKNO4C","created_at":"2026-05-18T12:31:34Z"},{"alias_kind":"pith_short_8","alias_value":"NXRJOIHU","created_at":"2026-05-18T12:31:34Z"}],"graph_snapshots":[{"event_id":"sha256:77c7a62cee84cb048014a1876346590a73679f020e4ccbf20d208f94113bbef3","target":"graph","created_at":"2026-05-18T00:38:40Z","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"},"paper":{"abstract_excerpt":"While it is well-known and acknowledged that the performance of graph algorithms is heavily dependent on the input data, there has been surprisingly little research to quantify and predict the impact the graph structure has on performance. Parallel graph algorithms, running on many-core systems such as GPUs, are no exception: most research has focused on how to efficiently implement and tune different graph operations on a specific GPU. However, the performance impact of the input graph has only been taken into account indirectly as a result of the graphs used to benchmark the system.\n  In thi","authors_text":"Ana Lucia Varbanescu, Cees de Laat, Merijn Verstraaten","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2017-08-03T14:33:22Z","title":"Using Graph Properties to Speed-up GPU-based Graph Traversal: A Model-driven Approach"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1708.01159","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:ab9388cc08775d1657805d659075b3466cc0c2559f14a5147a14cc7cd17c5951","target":"record","created_at":"2026-05-18T00:38:40Z","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":"0343eb7d04bce128ba7022fb2c43d99696fc4251816c95b24c68d74d2868fc57","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2017-08-03T14:33:22Z","title_canon_sha256":"2f7bc8f7e9cc8f255227e964567168f5c858a24bb0fad380293734b7c0c91b6f"},"schema_version":"1.0","source":{"id":"1708.01159","kind":"arxiv","version":1}},"canonical_sha256":"6de29720f4970ea6bb82d904d5c33c77f46d0145b044fd7571da9ab66c0fe49c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6de29720f4970ea6bb82d904d5c33c77f46d0145b044fd7571da9ab66c0fe49c","first_computed_at":"2026-05-18T00:38:40.491726Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:38:40.491726Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"dqreLvvVRJd6GuUI3J840q0CXh8abQ0ma7EIMptedL5vMk31YjhwmZs//THXDqz3iI+pJ6tRrQUrgetsPTceCg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:38:40.492113Z","signed_message":"canonical_sha256_bytes"},"source_id":"1708.01159","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ab9388cc08775d1657805d659075b3466cc0c2559f14a5147a14cc7cd17c5951","sha256:77c7a62cee84cb048014a1876346590a73679f020e4ccbf20d208f94113bbef3"],"state_sha256":"bb0a28c69f21129961729d4c7c22b2633ab9d3aa3a6c471de68a5f26d32eccb2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"hj3Iv1BSubEgJ5giM1n0/YaCDIbRc/zqIRCxWbwFCd2NC1k4n4opeUDSbt+xlOgywrCh6UBGLXz3APcY1xY9DQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-07T10:46:05.579109Z","bundle_sha256":"b764083fcb4e657c24826f4069862c2f062e2ff67e9e18ca9afd8fc9d2e3359c"}}