{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2015:LKSUUP2ZL4TWY43YKBRES3VKYD","short_pith_number":"pith:LKSUUP2Z","canonical_record":{"source":{"id":"1509.03778","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.PF","submitted_at":"2015-09-12T20:47:29Z","cross_cats_sorted":[],"title_canon_sha256":"a561e08f3abaef70ae8e3e7f0629bef2de6e270df1a30e14d07619e2db03790c","abstract_canon_sha256":"2399768bca9a4ea9a6a51935300cc495762178e579a8d9601ad420f558a77bbe"},"schema_version":"1.0"},"canonical_sha256":"5aa54a3f595f276c73785062496eaac0d66d63446302f74efde53516cc7493d4","source":{"kind":"arxiv","id":"1509.03778","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1509.03778","created_at":"2026-05-18T01:27:45Z"},{"alias_kind":"arxiv_version","alias_value":"1509.03778v2","created_at":"2026-05-18T01:27:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1509.03778","created_at":"2026-05-18T01:27:45Z"},{"alias_kind":"pith_short_12","alias_value":"LKSUUP2ZL4TW","created_at":"2026-05-18T12:29:29Z"},{"alias_kind":"pith_short_16","alias_value":"LKSUUP2ZL4TWY43Y","created_at":"2026-05-18T12:29:29Z"},{"alias_kind":"pith_short_8","alias_value":"LKSUUP2Z","created_at":"2026-05-18T12:29:29Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2015:LKSUUP2ZL4TWY43YKBRES3VKYD","target":"record","payload":{"canonical_record":{"source":{"id":"1509.03778","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.PF","submitted_at":"2015-09-12T20:47:29Z","cross_cats_sorted":[],"title_canon_sha256":"a561e08f3abaef70ae8e3e7f0629bef2de6e270df1a30e14d07619e2db03790c","abstract_canon_sha256":"2399768bca9a4ea9a6a51935300cc495762178e579a8d9601ad420f558a77bbe"},"schema_version":"1.0"},"canonical_sha256":"5aa54a3f595f276c73785062496eaac0d66d63446302f74efde53516cc7493d4","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:27:45.625859Z","signature_b64":"U5ki2rI+xxHNACHaLGlIsu23uu1WZ5Pqb8EO5wZjSITLtQAXbCAUnQKZXA8vmOtDPznNnG5dYRxo51s9hKbLCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5aa54a3f595f276c73785062496eaac0d66d63446302f74efde53516cc7493d4","last_reissued_at":"2026-05-18T01:27:45.625220Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:27:45.625220Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1509.03778","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":"2026-05-18T01:27:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sjg6xYZaXUeCKU2FElkR4z0WoKq3NQ/rj6RV5OaDHxCOFrZwiaKLy8TN429FVc0Wj7G7yKJ7rfKvQMG+IvL8DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T10:09:43.601183Z"},"content_sha256":"efa8ef1708a4ef61475d4767be6834e47bf9b2ecc2131bd1b8e307c1d3562169","schema_version":"1.0","event_id":"sha256:efa8ef1708a4ef61475d4767be6834e47bf9b2ecc2131bd1b8e307c1d3562169"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2015:LKSUUP2ZL4TWY43YKBRES3VKYD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Automatic Loop Kernel Analysis and Performance Modeling With Kerncraft","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.PF","authors_text":"Georg Hager, Gerhard Wellein, Jan Eitzinger, Julian Hammer","submitted_at":"2015-09-12T20:47:29Z","abstract_excerpt":"Analytic performance models are essential for understanding the performance characteristics of loop kernels, which consume a major part of CPU cycles in computational science. Starting from a validated performance model one can infer the relevant hardware bottlenecks and promising optimization opportunities. Unfortunately, analytic performance modeling is often tedious even for experienced developers since it requires in-depth knowledge about the hardware and how it interacts with the software. We present the \"Kerncraft\" tool, which eases the construction of analytic performance models for str"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1509.03778","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":"2026-05-18T01:27:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TaX4c94oVYvOGRDhBMPnv+3pk65CJTlRaxrXjM+hJTa1GgYEWLEpXiBpG6RG7Moc+t3oOkAI1F2TEvjbPhXlDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T10:09:43.601548Z"},"content_sha256":"90c3f598c13573cd296d683e8a791b99262e4803f7f52e15e8ab1af7bf1149cf","schema_version":"1.0","event_id":"sha256:90c3f598c13573cd296d683e8a791b99262e4803f7f52e15e8ab1af7bf1149cf"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LKSUUP2ZL4TWY43YKBRES3VKYD/bundle.json","state_url":"https://pith.science/pith/LKSUUP2ZL4TWY43YKBRES3VKYD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LKSUUP2ZL4TWY43YKBRES3VKYD/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":"2026-06-01T10:09:43Z","links":{"resolver":"https://pith.science/pith/LKSUUP2ZL4TWY43YKBRES3VKYD","bundle":"https://pith.science/pith/LKSUUP2ZL4TWY43YKBRES3VKYD/bundle.json","state":"https://pith.science/pith/LKSUUP2ZL4TWY43YKBRES3VKYD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LKSUUP2ZL4TWY43YKBRES3VKYD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2015:LKSUUP2ZL4TWY43YKBRES3VKYD","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":"2399768bca9a4ea9a6a51935300cc495762178e579a8d9601ad420f558a77bbe","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.PF","submitted_at":"2015-09-12T20:47:29Z","title_canon_sha256":"a561e08f3abaef70ae8e3e7f0629bef2de6e270df1a30e14d07619e2db03790c"},"schema_version":"1.0","source":{"id":"1509.03778","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1509.03778","created_at":"2026-05-18T01:27:45Z"},{"alias_kind":"arxiv_version","alias_value":"1509.03778v2","created_at":"2026-05-18T01:27:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1509.03778","created_at":"2026-05-18T01:27:45Z"},{"alias_kind":"pith_short_12","alias_value":"LKSUUP2ZL4TW","created_at":"2026-05-18T12:29:29Z"},{"alias_kind":"pith_short_16","alias_value":"LKSUUP2ZL4TWY43Y","created_at":"2026-05-18T12:29:29Z"},{"alias_kind":"pith_short_8","alias_value":"LKSUUP2Z","created_at":"2026-05-18T12:29:29Z"}],"graph_snapshots":[{"event_id":"sha256:90c3f598c13573cd296d683e8a791b99262e4803f7f52e15e8ab1af7bf1149cf","target":"graph","created_at":"2026-05-18T01:27:45Z","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":"Analytic performance models are essential for understanding the performance characteristics of loop kernels, which consume a major part of CPU cycles in computational science. Starting from a validated performance model one can infer the relevant hardware bottlenecks and promising optimization opportunities. Unfortunately, analytic performance modeling is often tedious even for experienced developers since it requires in-depth knowledge about the hardware and how it interacts with the software. We present the \"Kerncraft\" tool, which eases the construction of analytic performance models for str","authors_text":"Georg Hager, Gerhard Wellein, Jan Eitzinger, Julian Hammer","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.PF","submitted_at":"2015-09-12T20:47:29Z","title":"Automatic Loop Kernel Analysis and Performance Modeling With Kerncraft"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1509.03778","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:efa8ef1708a4ef61475d4767be6834e47bf9b2ecc2131bd1b8e307c1d3562169","target":"record","created_at":"2026-05-18T01:27:45Z","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":"2399768bca9a4ea9a6a51935300cc495762178e579a8d9601ad420f558a77bbe","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.PF","submitted_at":"2015-09-12T20:47:29Z","title_canon_sha256":"a561e08f3abaef70ae8e3e7f0629bef2de6e270df1a30e14d07619e2db03790c"},"schema_version":"1.0","source":{"id":"1509.03778","kind":"arxiv","version":2}},"canonical_sha256":"5aa54a3f595f276c73785062496eaac0d66d63446302f74efde53516cc7493d4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5aa54a3f595f276c73785062496eaac0d66d63446302f74efde53516cc7493d4","first_computed_at":"2026-05-18T01:27:45.625220Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:27:45.625220Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"U5ki2rI+xxHNACHaLGlIsu23uu1WZ5Pqb8EO5wZjSITLtQAXbCAUnQKZXA8vmOtDPznNnG5dYRxo51s9hKbLCQ==","signature_status":"signed_v1","signed_at":"2026-05-18T01:27:45.625859Z","signed_message":"canonical_sha256_bytes"},"source_id":"1509.03778","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:efa8ef1708a4ef61475d4767be6834e47bf9b2ecc2131bd1b8e307c1d3562169","sha256:90c3f598c13573cd296d683e8a791b99262e4803f7f52e15e8ab1af7bf1149cf"],"state_sha256":"c7c655b72bd42604685b0b0730055eed7d06bd3565fbb8b92636b990c6226bc6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"S1n6dlUd9MQnQUlmxIGRYRBoohkBj6jkZmvV53WOrLrfyqTNCk8KRv4j4Hzd83m4+eXIe72eBmtkcnnBhPzyBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-01T10:09:43.603513Z","bundle_sha256":"943eac655340821d6b8b3dae1a4b714d66eb82f1f5c58423138f7aa46bacf79b"}}