{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:JU4YE6KIFQ7WJS7EUEFXJLRMB6","short_pith_number":"pith:JU4YE6KI","schema_version":"1.0","canonical_sha256":"4d398279482c3f64cbe4a10b74ae2c0fb5361769eff9986475cafa6e79d1480f","source":{"kind":"arxiv","id":"1905.01833","version":3},"attestation_state":"computed","paper":{"title":"Characterizing and Detecting CUDA Program Bugs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.SE","authors_text":"Cong Liu, Husheng Zhou, Lingming Zhang, Mingyuan Wu, Yuqun Zhang","submitted_at":"2019-05-06T06:12:58Z","abstract_excerpt":"While CUDA has become a major parallel computing platform and programming model for general-purpose GPU computing, CUDA-induced bug patterns have not yet been well explored. In this paper, we conduct the first empirical study to reveal important categories of CUDA program bug patterns based on 319 bugs identified within 5 popular CUDA projects in GitHub. Our findings demonstrate that CUDA-specific characteristics may cause program bugs such as synchronization bugs that are rather difficult to detect. To efficiently detect such synchronization bugs, we establish the first lightweight general CU"},"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":"1905.01833","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SE","submitted_at":"2019-05-06T06:12:58Z","cross_cats_sorted":[],"title_canon_sha256":"cc58ea92a58345e286614ae98c86a8d31669cdeaf379135743681e26e8959f46","abstract_canon_sha256":"fce37398cb53394d0feabd96802ff5b519b74456c0de8c069b809eb21805321f"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:44:47.258558Z","signature_b64":"nu7IjVdTh+b4EroD5MR0cE1q/RykBoGkv4vx6Aups/vT26vOxIVXntZccwvy1f6zjOW5wEQ/o8vPVB6OLxKuCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4d398279482c3f64cbe4a10b74ae2c0fb5361769eff9986475cafa6e79d1480f","last_reissued_at":"2026-05-17T23:44:47.258110Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:44:47.258110Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Characterizing and Detecting CUDA Program Bugs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.SE","authors_text":"Cong Liu, Husheng Zhou, Lingming Zhang, Mingyuan Wu, Yuqun Zhang","submitted_at":"2019-05-06T06:12:58Z","abstract_excerpt":"While CUDA has become a major parallel computing platform and programming model for general-purpose GPU computing, CUDA-induced bug patterns have not yet been well explored. In this paper, we conduct the first empirical study to reveal important categories of CUDA program bug patterns based on 319 bugs identified within 5 popular CUDA projects in GitHub. Our findings demonstrate that CUDA-specific characteristics may cause program bugs such as synchronization bugs that are rather difficult to detect. To efficiently detect such synchronization bugs, we establish the first lightweight general CU"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1905.01833","kind":"arxiv","version":3},"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":"1905.01833","created_at":"2026-05-17T23:44:47.258173+00:00"},{"alias_kind":"arxiv_version","alias_value":"1905.01833v3","created_at":"2026-05-17T23:44:47.258173+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1905.01833","created_at":"2026-05-17T23:44:47.258173+00:00"},{"alias_kind":"pith_short_12","alias_value":"JU4YE6KIFQ7W","created_at":"2026-05-18T12:33:21.387695+00:00"},{"alias_kind":"pith_short_16","alias_value":"JU4YE6KIFQ7WJS7E","created_at":"2026-05-18T12:33:21.387695+00:00"},{"alias_kind":"pith_short_8","alias_value":"JU4YE6KI","created_at":"2026-05-18T12:33:21.387695+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2605.08455","citing_title":"CUDABeaver: Benchmarking LLM-Based Automated CUDA Debugging","ref_index":34,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/JU4YE6KIFQ7WJS7EUEFXJLRMB6","json":"https://pith.science/pith/JU4YE6KIFQ7WJS7EUEFXJLRMB6.json","graph_json":"https://pith.science/api/pith-number/JU4YE6KIFQ7WJS7EUEFXJLRMB6/graph.json","events_json":"https://pith.science/api/pith-number/JU4YE6KIFQ7WJS7EUEFXJLRMB6/events.json","paper":"https://pith.science/paper/JU4YE6KI"},"agent_actions":{"view_html":"https://pith.science/pith/JU4YE6KIFQ7WJS7EUEFXJLRMB6","download_json":"https://pith.science/pith/JU4YE6KIFQ7WJS7EUEFXJLRMB6.json","view_paper":"https://pith.science/paper/JU4YE6KI","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1905.01833&json=true","fetch_graph":"https://pith.science/api/pith-number/JU4YE6KIFQ7WJS7EUEFXJLRMB6/graph.json","fetch_events":"https://pith.science/api/pith-number/JU4YE6KIFQ7WJS7EUEFXJLRMB6/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/JU4YE6KIFQ7WJS7EUEFXJLRMB6/action/timestamp_anchor","attest_storage":"https://pith.science/pith/JU4YE6KIFQ7WJS7EUEFXJLRMB6/action/storage_attestation","attest_author":"https://pith.science/pith/JU4YE6KIFQ7WJS7EUEFXJLRMB6/action/author_attestation","sign_citation":"https://pith.science/pith/JU4YE6KIFQ7WJS7EUEFXJLRMB6/action/citation_signature","submit_replication":"https://pith.science/pith/JU4YE6KIFQ7WJS7EUEFXJLRMB6/action/replication_record"}},"created_at":"2026-05-17T23:44:47.258173+00:00","updated_at":"2026-05-17T23:44:47.258173+00:00"}