{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:WB4WA7DS4MUXAVIBRF6ZFAHGZ7","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":"3f1989090f5d67866e21aa730d726be40b2023f21d13153af6c4903b2915484a","cross_cats_sorted":["cs.AR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2018-07-09T17:38:42Z","title_canon_sha256":"cbb9eb684e77d5acba4f433c3bb995d847c8fd72671d3962557d220a8b3f32eb"},"schema_version":"1.0","source":{"id":"1807.09250","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1807.09250","created_at":"2026-05-18T00:09:56Z"},{"alias_kind":"arxiv_version","alias_value":"1807.09250v1","created_at":"2026-05-18T00:09:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1807.09250","created_at":"2026-05-18T00:09:56Z"},{"alias_kind":"pith_short_12","alias_value":"WB4WA7DS4MUX","created_at":"2026-05-18T12:32:59Z"},{"alias_kind":"pith_short_16","alias_value":"WB4WA7DS4MUXAVIB","created_at":"2026-05-18T12:32:59Z"},{"alias_kind":"pith_short_8","alias_value":"WB4WA7DS","created_at":"2026-05-18T12:32:59Z"}],"graph_snapshots":[{"event_id":"sha256:a3843e0760a52cd842af63e3ac910904e949d6b129ad9eeff29f0847342982d6","target":"graph","created_at":"2026-05-18T00:09:56Z","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":"The capability of classifying and clustering a desired set of data is an essential part of building knowledge from data. However, as the size and dimensionality of input data increases, the run-time for such clustering algorithms is expected to grow superlinearly, making it a big challenge when dealing with BigData. K-mean clustering is an essential tool for many big data applications including data mining, predictive analysis, forecasting studies, and machine learning. However, due to large size (volume) of Big-Data, and large dimensionality of its data points, even the application of a simpl","authors_text":"Hadi Mardani Kamali","cross_cats":["cs.AR"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2018-07-09T17:38:42Z","title":"Using Multi-Core HW/SW Co-design Architecture for Accelerating K-means Clustering Algorithm"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1807.09250","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:b40ef62f5fa629aecdf017e5af62d30a175285f00d1dec7f504fb0b71c4dea61","target":"record","created_at":"2026-05-18T00:09:56Z","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":"3f1989090f5d67866e21aa730d726be40b2023f21d13153af6c4903b2915484a","cross_cats_sorted":["cs.AR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2018-07-09T17:38:42Z","title_canon_sha256":"cbb9eb684e77d5acba4f433c3bb995d847c8fd72671d3962557d220a8b3f32eb"},"schema_version":"1.0","source":{"id":"1807.09250","kind":"arxiv","version":1}},"canonical_sha256":"b079607c72e329705501897d9280e6cfc0c947767e5812f2a59243f75f032de9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b079607c72e329705501897d9280e6cfc0c947767e5812f2a59243f75f032de9","first_computed_at":"2026-05-18T00:09:56.288084Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:09:56.288084Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Sk1x1VPTzG/YJ3NdH5sw4bIna5ZbCk3JB5MsnO7lP4q0ihgwKJk9hD8K09TDY4gPkp6SjoSDhLaE79pSmAMnCQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:09:56.288812Z","signed_message":"canonical_sha256_bytes"},"source_id":"1807.09250","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b40ef62f5fa629aecdf017e5af62d30a175285f00d1dec7f504fb0b71c4dea61","sha256:a3843e0760a52cd842af63e3ac910904e949d6b129ad9eeff29f0847342982d6"],"state_sha256":"c51fcfc514314a6cb613955557436072daa60bd563dce1bf3b14b4dc8049024d"}