{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:G6ASGSDKWUA6ZIQTKJBOCBU7CI","short_pith_number":"pith:G6ASGSDK","schema_version":"1.0","canonical_sha256":"378123486ab501eca2135242e1069f120a4f0d508c3522a16bfb632558489f4e","source":{"kind":"arxiv","id":"1708.04701","version":2},"attestation_state":"computed","paper":{"title":"Performance Characterization of Multi-threaded Graph Processing Applications on Intel Many-Integrated-Core Architecture","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DC","authors_text":"Judy Qiu, Langshi Chen, Lei Jiang","submitted_at":"2017-08-15T21:59:38Z","abstract_excerpt":"Intel Xeon Phi many-integrated-core (MIC) architectures usher in a new era of terascale integration. Among emerging killer applications, parallel graph processing has been a critical technique to analyze connected data. In this paper, we empirically evaluate various computing platforms including an Intel Xeon E5 CPU, a Nvidia Geforce GTX1070 GPU and an Xeon Phi 7210 processor codenamed Knights Landing (KNL) in the domain of parallel graph processing. We show that the KNL gains encouraging performance when processing graphs, so that it can become a promising solution to accelerating multi-threa"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1708.04701","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2017-08-15T21:59:38Z","cross_cats_sorted":[],"title_canon_sha256":"246e68b5df5f7f0c3e9fe0b3705d0e9442fa8f17031bd488acba73238d94436c","abstract_canon_sha256":"421da3c0729818918e2a395b24d65885e98a273858e73bb07a113dea94704146"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:52:56.046798Z","signature_b64":"AUFsidBr6InrmBYBkHHOakL5d8pjG0QF612Lp6pFQ3aQvKr0l/WJMMVhhbDd2cVWr4m0m5sywSbY8Hd6+LZGBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"378123486ab501eca2135242e1069f120a4f0d508c3522a16bfb632558489f4e","last_reissued_at":"2026-05-17T23:52:56.045938Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:52:56.045938Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Performance Characterization of Multi-threaded Graph Processing Applications on Intel Many-Integrated-Core Architecture","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DC","authors_text":"Judy Qiu, Langshi Chen, Lei Jiang","submitted_at":"2017-08-15T21:59:38Z","abstract_excerpt":"Intel Xeon Phi many-integrated-core (MIC) architectures usher in a new era of terascale integration. Among emerging killer applications, parallel graph processing has been a critical technique to analyze connected data. In this paper, we empirically evaluate various computing platforms including an Intel Xeon E5 CPU, a Nvidia Geforce GTX1070 GPU and an Xeon Phi 7210 processor codenamed Knights Landing (KNL) in the domain of parallel graph processing. We show that the KNL gains encouraging performance when processing graphs, so that it can become a promising solution to accelerating multi-threa"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1708.04701","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1708.04701","created_at":"2026-05-17T23:52:56.046089+00:00"},{"alias_kind":"arxiv_version","alias_value":"1708.04701v2","created_at":"2026-05-17T23:52:56.046089+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1708.04701","created_at":"2026-05-17T23:52:56.046089+00:00"},{"alias_kind":"pith_short_12","alias_value":"G6ASGSDKWUA6","created_at":"2026-05-18T12:31:15.632608+00:00"},{"alias_kind":"pith_short_16","alias_value":"G6ASGSDKWUA6ZIQT","created_at":"2026-05-18T12:31:15.632608+00:00"},{"alias_kind":"pith_short_8","alias_value":"G6ASGSDK","created_at":"2026-05-18T12:31:15.632608+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/G6ASGSDKWUA6ZIQTKJBOCBU7CI","json":"https://pith.science/pith/G6ASGSDKWUA6ZIQTKJBOCBU7CI.json","graph_json":"https://pith.science/api/pith-number/G6ASGSDKWUA6ZIQTKJBOCBU7CI/graph.json","events_json":"https://pith.science/api/pith-number/G6ASGSDKWUA6ZIQTKJBOCBU7CI/events.json","paper":"https://pith.science/paper/G6ASGSDK"},"agent_actions":{"view_html":"https://pith.science/pith/G6ASGSDKWUA6ZIQTKJBOCBU7CI","download_json":"https://pith.science/pith/G6ASGSDKWUA6ZIQTKJBOCBU7CI.json","view_paper":"https://pith.science/paper/G6ASGSDK","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1708.04701&json=true","fetch_graph":"https://pith.science/api/pith-number/G6ASGSDKWUA6ZIQTKJBOCBU7CI/graph.json","fetch_events":"https://pith.science/api/pith-number/G6ASGSDKWUA6ZIQTKJBOCBU7CI/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/G6ASGSDKWUA6ZIQTKJBOCBU7CI/action/timestamp_anchor","attest_storage":"https://pith.science/pith/G6ASGSDKWUA6ZIQTKJBOCBU7CI/action/storage_attestation","attest_author":"https://pith.science/pith/G6ASGSDKWUA6ZIQTKJBOCBU7CI/action/author_attestation","sign_citation":"https://pith.science/pith/G6ASGSDKWUA6ZIQTKJBOCBU7CI/action/citation_signature","submit_replication":"https://pith.science/pith/G6ASGSDKWUA6ZIQTKJBOCBU7CI/action/replication_record"}},"created_at":"2026-05-17T23:52:56.046089+00:00","updated_at":"2026-05-17T23:52:56.046089+00:00"}