{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:VJA4KF2G32ZGBRJRDJSJ6LKTSO","short_pith_number":"pith:VJA4KF2G","canonical_record":{"source":{"id":"2411.02797","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.PF","submitted_at":"2024-11-05T04:15:26Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"cffbd08f61817ce90a14d42dee94b9737b0e5ee96cfb3b3d12e3df905fadd356","abstract_canon_sha256":"c9be558a4be8c33bdbff9b61c3a4d5c7a0ae57938fbb43df1ed304c73677aa05"},"schema_version":"1.0"},"canonical_sha256":"aa41c51746deb260c5311a649f2d539381bf4a7633f591e7a7318c3e8984e84e","source":{"kind":"arxiv","id":"2411.02797","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.02797","created_at":"2026-07-05T09:31:18Z"},{"alias_kind":"arxiv_version","alias_value":"2411.02797v1","created_at":"2026-07-05T09:31:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.02797","created_at":"2026-07-05T09:31:18Z"},{"alias_kind":"pith_short_12","alias_value":"VJA4KF2G32ZG","created_at":"2026-07-05T09:31:18Z"},{"alias_kind":"pith_short_16","alias_value":"VJA4KF2G32ZGBRJR","created_at":"2026-07-05T09:31:18Z"},{"alias_kind":"pith_short_8","alias_value":"VJA4KF2G","created_at":"2026-07-05T09:31:18Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:VJA4KF2G32ZGBRJRDJSJ6LKTSO","target":"record","payload":{"canonical_record":{"source":{"id":"2411.02797","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.PF","submitted_at":"2024-11-05T04:15:26Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"cffbd08f61817ce90a14d42dee94b9737b0e5ee96cfb3b3d12e3df905fadd356","abstract_canon_sha256":"c9be558a4be8c33bdbff9b61c3a4d5c7a0ae57938fbb43df1ed304c73677aa05"},"schema_version":"1.0"},"canonical_sha256":"aa41c51746deb260c5311a649f2d539381bf4a7633f591e7a7318c3e8984e84e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:31:18.264397Z","signature_b64":"axp/x3Di9dmbIC0v0DnKMfpvsHYH38Nol3HR8yVDEUXTp9fD/vqA81L7y+hScAtvipyZtlkZsRSvxzwhUNPRBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"aa41c51746deb260c5311a649f2d539381bf4a7633f591e7a7318c3e8984e84e","last_reissued_at":"2026-07-05T09:31:18.263910Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:31:18.263910Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2411.02797","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:31:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/GWC5d+zSYyaxvhklpJkr7w0bBJZongAVoFEotr7iRaUOR+5gC09gbIZqCaqech+Ncohwom0REdAbIQOzDggBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T05:52:57.879610Z"},"content_sha256":"46eac9bd2b89948a957301eb75d691534f56afc2e0a55953ea0ac127869d3e3d","schema_version":"1.0","event_id":"sha256:46eac9bd2b89948a957301eb75d691534f56afc2e0a55953ea0ac127869d3e3d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:VJA4KF2G32ZGBRJRDJSJ6LKTSO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"DeepContext: A Context-aware, Cross-platform, and Cross-framework Tool for Performance Profiling and Analysis of Deep Learning Workloads","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.PF","authors_text":"Hao Wu, Jiajia Li, Keren Zhou, Qidong Zhao, Xu Liu, Yuming Hao, Zilingfeng Ye","submitted_at":"2024-11-05T04:15:26Z","abstract_excerpt":"Effective performance profiling and analysis are essential for optimizing training and inference of deep learning models, especially given the growing complexity of heterogeneous computing environments. However, existing tools often lack the capability to provide comprehensive program context information and performance optimization insights for sophisticated interactions between CPUs and GPUs. This paper introduces DeepContext, a novel profiler that links program contexts across high-level Python code, deep learning frameworks, underlying libraries written in C/C++, as well as device code exe"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.02797","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/2411.02797/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:31:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lMt+gbpzpHLmEV0CxagL+D2oWXSfcIBnvRSO0NCY8y9KgcdEIEufD5LRoHqlhxF7M5JcBYekvfyUMKLsf5/fAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T05:52:57.880497Z"},"content_sha256":"2fb26e6b093bc44e790d9b3219fb0cab660498f8c837326d6ffb687cb804429c","schema_version":"1.0","event_id":"sha256:2fb26e6b093bc44e790d9b3219fb0cab660498f8c837326d6ffb687cb804429c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VJA4KF2G32ZGBRJRDJSJ6LKTSO/bundle.json","state_url":"https://pith.science/pith/VJA4KF2G32ZGBRJRDJSJ6LKTSO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VJA4KF2G32ZGBRJRDJSJ6LKTSO/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":"2026-08-06T05:52:57Z","links":{"resolver":"https://pith.science/pith/VJA4KF2G32ZGBRJRDJSJ6LKTSO","bundle":"https://pith.science/pith/VJA4KF2G32ZGBRJRDJSJ6LKTSO/bundle.json","state":"https://pith.science/pith/VJA4KF2G32ZGBRJRDJSJ6LKTSO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VJA4KF2G32ZGBRJRDJSJ6LKTSO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:VJA4KF2G32ZGBRJRDJSJ6LKTSO","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":"c9be558a4be8c33bdbff9b61c3a4d5c7a0ae57938fbb43df1ed304c73677aa05","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.PF","submitted_at":"2024-11-05T04:15:26Z","title_canon_sha256":"cffbd08f61817ce90a14d42dee94b9737b0e5ee96cfb3b3d12e3df905fadd356"},"schema_version":"1.0","source":{"id":"2411.02797","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.02797","created_at":"2026-07-05T09:31:18Z"},{"alias_kind":"arxiv_version","alias_value":"2411.02797v1","created_at":"2026-07-05T09:31:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.02797","created_at":"2026-07-05T09:31:18Z"},{"alias_kind":"pith_short_12","alias_value":"VJA4KF2G32ZG","created_at":"2026-07-05T09:31:18Z"},{"alias_kind":"pith_short_16","alias_value":"VJA4KF2G32ZGBRJR","created_at":"2026-07-05T09:31:18Z"},{"alias_kind":"pith_short_8","alias_value":"VJA4KF2G","created_at":"2026-07-05T09:31:18Z"}],"graph_snapshots":[{"event_id":"sha256:2fb26e6b093bc44e790d9b3219fb0cab660498f8c837326d6ffb687cb804429c","target":"graph","created_at":"2026-07-05T09:31:18Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2411.02797/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Effective performance profiling and analysis are essential for optimizing training and inference of deep learning models, especially given the growing complexity of heterogeneous computing environments. However, existing tools often lack the capability to provide comprehensive program context information and performance optimization insights for sophisticated interactions between CPUs and GPUs. This paper introduces DeepContext, a novel profiler that links program contexts across high-level Python code, deep learning frameworks, underlying libraries written in C/C++, as well as device code exe","authors_text":"Hao Wu, Jiajia Li, Keren Zhou, Qidong Zhao, Xu Liu, Yuming Hao, Zilingfeng Ye","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.PF","submitted_at":"2024-11-05T04:15:26Z","title":"DeepContext: A Context-aware, Cross-platform, and Cross-framework Tool for Performance Profiling and Analysis of Deep Learning Workloads"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.02797","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":"sha256:46eac9bd2b89948a957301eb75d691534f56afc2e0a55953ea0ac127869d3e3d","target":"record","created_at":"2026-07-05T09:31:18Z","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":"c9be558a4be8c33bdbff9b61c3a4d5c7a0ae57938fbb43df1ed304c73677aa05","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.PF","submitted_at":"2024-11-05T04:15:26Z","title_canon_sha256":"cffbd08f61817ce90a14d42dee94b9737b0e5ee96cfb3b3d12e3df905fadd356"},"schema_version":"1.0","source":{"id":"2411.02797","kind":"arxiv","version":1}},"canonical_sha256":"aa41c51746deb260c5311a649f2d539381bf4a7633f591e7a7318c3e8984e84e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"aa41c51746deb260c5311a649f2d539381bf4a7633f591e7a7318c3e8984e84e","first_computed_at":"2026-07-05T09:31:18.263910Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:31:18.263910Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"axp/x3Di9dmbIC0v0DnKMfpvsHYH38Nol3HR8yVDEUXTp9fD/vqA81L7y+hScAtvipyZtlkZsRSvxzwhUNPRBw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:31:18.264397Z","signed_message":"canonical_sha256_bytes"},"source_id":"2411.02797","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:46eac9bd2b89948a957301eb75d691534f56afc2e0a55953ea0ac127869d3e3d","sha256:2fb26e6b093bc44e790d9b3219fb0cab660498f8c837326d6ffb687cb804429c"],"state_sha256":"e065a179c642c2f3fb88319fcab314e3d6ba3cd25f1a741e375c6ed8a162dadf"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"P/yXg5F1e9b4+PHsrR+7sPBXLq2i7eYGha8cSiOt+y495RKcbGd+4HraEgeLZq+638HGoe/YY4BB+G6EBfpdCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T05:52:57.886021Z","bundle_sha256":"d51a20084a5fce3e564fab2c3708bfd578b67db1ec6850428a800094e881b230"}}