{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:PK75JNUAGOYC7BLS6X4F4HL32H","short_pith_number":"pith:PK75JNUA","schema_version":"1.0","canonical_sha256":"7abfd4b68033b02f8572f5f85e1d7bd1f568e53b02b1fd94b162d2a942e38d06","source":{"kind":"arxiv","id":"2104.13248","version":1},"attestation_state":"computed","paper":{"title":"Performance Portable Back-projection Algorithms on CPUs: Agnostic Data Locality and Vectorization Optimizations","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.DC","authors_text":"Hirotaka Ogawa, Mohamed Wahib, Peng Chen, Satoshi Matsuoka, Shinichiro Takizawa, Takahiro Hirofuchi, Xiao Wang","submitted_at":"2021-04-27T15:01:12Z","abstract_excerpt":"Computed Tomography (CT) is a key 3D imaging technology that fundamentally relies on the compute-intense back-projection operation to generate 3D volumes. GPUs are typically used for back-projection in production CT devices. However, with the rise of power-constrained micro-CT devices, and also the emergence of CPUs comparable in performance to GPUs, back-projection for CPUs could become favorable. Unlike GPUs, extracting parallelism for back-projection algorithms on CPUs is complex given that parallelism and locality are not explicitly defined and controlled by the programmer, as is the case "},"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":"2104.13248","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.DC","submitted_at":"2021-04-27T15:01:12Z","cross_cats_sorted":[],"title_canon_sha256":"b2bf6f1052bdceb5d0137cbda9354fef58106e230f751b0a6c72320a660b2dba","abstract_canon_sha256":"401748e6ee6061420212560691a0bd8874d03daf2575ccc069fb16b36d4e7ff9"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:35:46.905823Z","signature_b64":"ngI5sFcDx1XntALQvNtWIEGruoELe/WZyPBDpm6wBz8dh/Pkv9rTOQLkZWL0y5aBPtgLOEj7P3he1cN56ZFWDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7abfd4b68033b02f8572f5f85e1d7bd1f568e53b02b1fd94b162d2a942e38d06","last_reissued_at":"2026-07-05T02:35:46.905340Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:35:46.905340Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Performance Portable Back-projection Algorithms on CPUs: Agnostic Data Locality and Vectorization Optimizations","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.DC","authors_text":"Hirotaka Ogawa, Mohamed Wahib, Peng Chen, Satoshi Matsuoka, Shinichiro Takizawa, Takahiro Hirofuchi, Xiao Wang","submitted_at":"2021-04-27T15:01:12Z","abstract_excerpt":"Computed Tomography (CT) is a key 3D imaging technology that fundamentally relies on the compute-intense back-projection operation to generate 3D volumes. GPUs are typically used for back-projection in production CT devices. However, with the rise of power-constrained micro-CT devices, and also the emergence of CPUs comparable in performance to GPUs, back-projection for CPUs could become favorable. Unlike GPUs, extracting parallelism for back-projection algorithms on CPUs is complex given that parallelism and locality are not explicitly defined and controlled by the programmer, as is the case "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2104.13248","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2104.13248/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2104.13248","created_at":"2026-07-05T02:35:46.905396+00:00"},{"alias_kind":"arxiv_version","alias_value":"2104.13248v1","created_at":"2026-07-05T02:35:46.905396+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2104.13248","created_at":"2026-07-05T02:35:46.905396+00:00"},{"alias_kind":"pith_short_12","alias_value":"PK75JNUAGOYC","created_at":"2026-07-05T02:35:46.905396+00:00"},{"alias_kind":"pith_short_16","alias_value":"PK75JNUAGOYC7BLS","created_at":"2026-07-05T02:35:46.905396+00:00"},{"alias_kind":"pith_short_8","alias_value":"PK75JNUA","created_at":"2026-07-05T02:35:46.905396+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/PK75JNUAGOYC7BLS6X4F4HL32H","json":"https://pith.science/pith/PK75JNUAGOYC7BLS6X4F4HL32H.json","graph_json":"https://pith.science/api/pith-number/PK75JNUAGOYC7BLS6X4F4HL32H/graph.json","events_json":"https://pith.science/api/pith-number/PK75JNUAGOYC7BLS6X4F4HL32H/events.json","paper":"https://pith.science/paper/PK75JNUA"},"agent_actions":{"view_html":"https://pith.science/pith/PK75JNUAGOYC7BLS6X4F4HL32H","download_json":"https://pith.science/pith/PK75JNUAGOYC7BLS6X4F4HL32H.json","view_paper":"https://pith.science/paper/PK75JNUA","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2104.13248&json=true","fetch_graph":"https://pith.science/api/pith-number/PK75JNUAGOYC7BLS6X4F4HL32H/graph.json","fetch_events":"https://pith.science/api/pith-number/PK75JNUAGOYC7BLS6X4F4HL32H/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/PK75JNUAGOYC7BLS6X4F4HL32H/action/timestamp_anchor","attest_storage":"https://pith.science/pith/PK75JNUAGOYC7BLS6X4F4HL32H/action/storage_attestation","attest_author":"https://pith.science/pith/PK75JNUAGOYC7BLS6X4F4HL32H/action/author_attestation","sign_citation":"https://pith.science/pith/PK75JNUAGOYC7BLS6X4F4HL32H/action/citation_signature","submit_replication":"https://pith.science/pith/PK75JNUAGOYC7BLS6X4F4HL32H/action/replication_record"}},"created_at":"2026-07-05T02:35:46.905396+00:00","updated_at":"2026-07-05T02:35:46.905396+00:00"}