{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:ZBHGR6BHGUHMSANHQEZ6LKSVPG","short_pith_number":"pith:ZBHGR6BH","canonical_record":{"source":{"id":"1707.03478","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2017-07-11T22:10:43Z","cross_cats_sorted":["cs.DC"],"title_canon_sha256":"fff7f374c34bb4d4178cf282d836226e402095b38dd54537d642a15fd96d4dd9","abstract_canon_sha256":"376536724aa30f796d4351ccaa5627e1b1d837fd99137173e62acf86ac6a1ec6"},"schema_version":"1.0"},"canonical_sha256":"c84e68f827350ec901a78133e5aa5579bd97e9b04651c359da212056d65a874d","source":{"kind":"arxiv","id":"1707.03478","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1707.03478","created_at":"2026-05-18T00:24:36Z"},{"alias_kind":"arxiv_version","alias_value":"1707.03478v2","created_at":"2026-05-18T00:24:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1707.03478","created_at":"2026-05-18T00:24:36Z"},{"alias_kind":"pith_short_12","alias_value":"ZBHGR6BHGUHM","created_at":"2026-05-18T12:31:59Z"},{"alias_kind":"pith_short_16","alias_value":"ZBHGR6BHGUHMSANH","created_at":"2026-05-18T12:31:59Z"},{"alias_kind":"pith_short_8","alias_value":"ZBHGR6BH","created_at":"2026-05-18T12:31:59Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:ZBHGR6BHGUHMSANHQEZ6LKSVPG","target":"record","payload":{"canonical_record":{"source":{"id":"1707.03478","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2017-07-11T22:10:43Z","cross_cats_sorted":["cs.DC"],"title_canon_sha256":"fff7f374c34bb4d4178cf282d836226e402095b38dd54537d642a15fd96d4dd9","abstract_canon_sha256":"376536724aa30f796d4351ccaa5627e1b1d837fd99137173e62acf86ac6a1ec6"},"schema_version":"1.0"},"canonical_sha256":"c84e68f827350ec901a78133e5aa5579bd97e9b04651c359da212056d65a874d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:24:36.054420Z","signature_b64":"Zhv45RevGFY3E+6PkrGnIXoav6lUvQVk+4wcRFgDw/knuzXy1PP+20jB1gEKExx9fs5zQhsp9sU4ACY5f+kgDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c84e68f827350ec901a78133e5aa5579bd97e9b04651c359da212056d65a874d","last_reissued_at":"2026-05-18T00:24:36.054023Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:24:36.054023Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1707.03478","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":"2026-05-18T00:24:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AY5MhzCHBkvC3FqrThh+wPVkPihLeKw4kNgV8XGE1F2/a3G9Oho21GLqKPB9ofuWY8hITDyEMwr2bvPFjairAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-09T11:18:09.285674Z"},"content_sha256":"4f4e9f9fb070a001f1f225923c87520b1f31fcb8f44dac2bd4b8af1901633349","schema_version":"1.0","event_id":"sha256:4f4e9f9fb070a001f1f225923c87520b1f31fcb8f44dac2bd4b8af1901633349"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:ZBHGR6BHGUHMSANHQEZ6LKSVPG","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Round Compression for Parallel Matching Algorithms","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DC"],"primary_cat":"cs.DS","authors_text":"Aleksander M\\k{a}dry, Artur Czumaj, Jakub {\\L}\\k{a}cki, Krzysztof Onak, Piotr Sankowski, Slobodan Mitrovi\\'c","submitted_at":"2017-07-11T22:10:43Z","abstract_excerpt":"For over a decade now we have been witnessing the success of {\\em massive parallel computation} (MPC) frameworks, such as MapReduce, Hadoop, Dryad, or Spark. One of the reasons for their success is the fact that these frameworks are able to accurately capture the nature of large-scale computation. In particular, compared to the classic distributed algorithms or PRAM models, these frameworks allow for much more local computation. The fundamental question that arises in this context is though: can we leverage this additional power to obtain even faster parallel algorithms?\n  A prominent example "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1707.03478","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":""},"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":"2026-05-18T00:24:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ocz0JXbVxgu8SzU0MfnwbYZOe2QiDgwHHJ/pcno5dDMq0Xsj3CVwAGCprvG4RqG4E2TQbshui7fRsmcIpuHfAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-09T11:18:09.286011Z"},"content_sha256":"86cb3749acf3cbc22701b3d05490f35e5c467c563036d503623ef5f9b598a643","schema_version":"1.0","event_id":"sha256:86cb3749acf3cbc22701b3d05490f35e5c467c563036d503623ef5f9b598a643"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZBHGR6BHGUHMSANHQEZ6LKSVPG/bundle.json","state_url":"https://pith.science/pith/ZBHGR6BHGUHMSANHQEZ6LKSVPG/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZBHGR6BHGUHMSANHQEZ6LKSVPG/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":"2026-06-09T11:18:09Z","links":{"resolver":"https://pith.science/pith/ZBHGR6BHGUHMSANHQEZ6LKSVPG","bundle":"https://pith.science/pith/ZBHGR6BHGUHMSANHQEZ6LKSVPG/bundle.json","state":"https://pith.science/pith/ZBHGR6BHGUHMSANHQEZ6LKSVPG/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZBHGR6BHGUHMSANHQEZ6LKSVPG/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:ZBHGR6BHGUHMSANHQEZ6LKSVPG","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":"376536724aa30f796d4351ccaa5627e1b1d837fd99137173e62acf86ac6a1ec6","cross_cats_sorted":["cs.DC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2017-07-11T22:10:43Z","title_canon_sha256":"fff7f374c34bb4d4178cf282d836226e402095b38dd54537d642a15fd96d4dd9"},"schema_version":"1.0","source":{"id":"1707.03478","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1707.03478","created_at":"2026-05-18T00:24:36Z"},{"alias_kind":"arxiv_version","alias_value":"1707.03478v2","created_at":"2026-05-18T00:24:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1707.03478","created_at":"2026-05-18T00:24:36Z"},{"alias_kind":"pith_short_12","alias_value":"ZBHGR6BHGUHM","created_at":"2026-05-18T12:31:59Z"},{"alias_kind":"pith_short_16","alias_value":"ZBHGR6BHGUHMSANH","created_at":"2026-05-18T12:31:59Z"},{"alias_kind":"pith_short_8","alias_value":"ZBHGR6BH","created_at":"2026-05-18T12:31:59Z"}],"graph_snapshots":[{"event_id":"sha256:86cb3749acf3cbc22701b3d05490f35e5c467c563036d503623ef5f9b598a643","target":"graph","created_at":"2026-05-18T00:24:36Z","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":"For over a decade now we have been witnessing the success of {\\em massive parallel computation} (MPC) frameworks, such as MapReduce, Hadoop, Dryad, or Spark. One of the reasons for their success is the fact that these frameworks are able to accurately capture the nature of large-scale computation. In particular, compared to the classic distributed algorithms or PRAM models, these frameworks allow for much more local computation. The fundamental question that arises in this context is though: can we leverage this additional power to obtain even faster parallel algorithms?\n  A prominent example ","authors_text":"Aleksander M\\k{a}dry, Artur Czumaj, Jakub {\\L}\\k{a}cki, Krzysztof Onak, Piotr Sankowski, Slobodan Mitrovi\\'c","cross_cats":["cs.DC"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2017-07-11T22:10:43Z","title":"Round Compression for Parallel Matching Algorithms"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1707.03478","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":"sha256:4f4e9f9fb070a001f1f225923c87520b1f31fcb8f44dac2bd4b8af1901633349","target":"record","created_at":"2026-05-18T00:24:36Z","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":"376536724aa30f796d4351ccaa5627e1b1d837fd99137173e62acf86ac6a1ec6","cross_cats_sorted":["cs.DC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2017-07-11T22:10:43Z","title_canon_sha256":"fff7f374c34bb4d4178cf282d836226e402095b38dd54537d642a15fd96d4dd9"},"schema_version":"1.0","source":{"id":"1707.03478","kind":"arxiv","version":2}},"canonical_sha256":"c84e68f827350ec901a78133e5aa5579bd97e9b04651c359da212056d65a874d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c84e68f827350ec901a78133e5aa5579bd97e9b04651c359da212056d65a874d","first_computed_at":"2026-05-18T00:24:36.054023Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:24:36.054023Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Zhv45RevGFY3E+6PkrGnIXoav6lUvQVk+4wcRFgDw/knuzXy1PP+20jB1gEKExx9fs5zQhsp9sU4ACY5f+kgDA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:24:36.054420Z","signed_message":"canonical_sha256_bytes"},"source_id":"1707.03478","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4f4e9f9fb070a001f1f225923c87520b1f31fcb8f44dac2bd4b8af1901633349","sha256:86cb3749acf3cbc22701b3d05490f35e5c467c563036d503623ef5f9b598a643"],"state_sha256":"6c11ca12646bd11a221eec5715cd324b49152e75f36cdcb5b429a70fbac572a1"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yFob1UqXynbx2T9oTXTvuoiWat/y77DQ1w1f6i0StPmuuBonLMHovvk1rkMME6gbnXAn5upf3DDMX55QxPW0AQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-09T11:18:09.287959Z","bundle_sha256":"de03eb8cfb30ebd063677ab7995673092b0d7053040b923cc19c3bc6b898dfa1"}}