{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:IX7Z6LRSDJRNOET2JA4SEPLN2N","short_pith_number":"pith:IX7Z6LRS","canonical_record":{"source":{"id":"2007.06775","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2020-07-14T02:16:56Z","cross_cats_sorted":["cs.LG","cs.OS"],"title_canon_sha256":"940c3e3f0aad18b56fd9e199cc0fa5a898adfd9caed6c95e2338cde0bf130abe","abstract_canon_sha256":"bf47724e11dce4803d6b986333ffc35e3ae7aa82ad219c53ca8842af7515a258"},"schema_version":"1.0"},"canonical_sha256":"45ff9f2e321a62d7127a4839223d6dd341735abf53d011c611daee6f96390c38","source":{"kind":"arxiv","id":"2007.06775","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2007.06775","created_at":"2026-07-05T02:07:48Z"},{"alias_kind":"arxiv_version","alias_value":"2007.06775v3","created_at":"2026-07-05T02:07:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2007.06775","created_at":"2026-07-05T02:07:48Z"},{"alias_kind":"pith_short_12","alias_value":"IX7Z6LRSDJRN","created_at":"2026-07-05T02:07:48Z"},{"alias_kind":"pith_short_16","alias_value":"IX7Z6LRSDJRNOET2","created_at":"2026-07-05T02:07:48Z"},{"alias_kind":"pith_short_8","alias_value":"IX7Z6LRS","created_at":"2026-07-05T02:07:48Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:IX7Z6LRSDJRNOET2JA4SEPLN2N","target":"record","payload":{"canonical_record":{"source":{"id":"2007.06775","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2020-07-14T02:16:56Z","cross_cats_sorted":["cs.LG","cs.OS"],"title_canon_sha256":"940c3e3f0aad18b56fd9e199cc0fa5a898adfd9caed6c95e2338cde0bf130abe","abstract_canon_sha256":"bf47724e11dce4803d6b986333ffc35e3ae7aa82ad219c53ca8842af7515a258"},"schema_version":"1.0"},"canonical_sha256":"45ff9f2e321a62d7127a4839223d6dd341735abf53d011c611daee6f96390c38","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:07:48.331105Z","signature_b64":"mapYibHF1+NU75nBeV8SyQKQgS2LgrfB6HpO4fFvlFGg+P+e9Kng8KeEIcQ/PbGFMwNSDA7sot+r3kZ5QKtIDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"45ff9f2e321a62d7127a4839223d6dd341735abf53d011c611daee6f96390c38","last_reissued_at":"2026-07-05T02:07:48.330640Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:07:48.330640Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2007.06775","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T02:07:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5DNBGAMzQLBo9Sc8lGKv3U3gtryLm9OGKrFk599m4tGw/QgH3LlWRBB5HDaM5BYXpskdS676SOdy+NSWSSOEAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T14:41:38.933761Z"},"content_sha256":"def4958d1738fbe05ee8d72664a33782fffc73d82850e837617de062599bf806","schema_version":"1.0","event_id":"sha256:def4958d1738fbe05ee8d72664a33782fffc73d82850e837617de062599bf806"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:IX7Z6LRSDJRNOET2JA4SEPLN2N","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Analyzing and Mitigating Data Stalls in DNN Training","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.OS"],"primary_cat":"cs.DC","authors_text":"Amar Phanishayee, Ashish Raniwala, Jayashree Mohan, Vijay Chidambaram","submitted_at":"2020-07-14T02:16:56Z","abstract_excerpt":"Training Deep Neural Networks (DNNs) is resource-intensive and time-consuming. While prior research has explored many different ways of reducing DNN training time, the impact of input data pipeline, i.e., fetching raw data items from storage and performing data pre-processing in memory, has been relatively unexplored. This paper makes the following contributions: (1) We present the first comprehensive analysis of how the input data pipeline affects the training time of widely-used computer vision and audio Deep Neural Networks (DNNs), that typically involve complex data preprocessing. We analy"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2007.06775","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2007.06775/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":"2026-07-05T02:07:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"y/nLZJAKEWN+vEZ+CEqAxyjauqN3BAEkNna4mcDh79CS0Cj80o9cA2l5/hD0KFbFUKOCsK6aSgo7AGSxKCV5Ag==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T14:41:38.934645Z"},"content_sha256":"d5b869705187191d66c23a1f7cfc6e07c8dd7afe71e80571307e1f930ffeeb88","schema_version":"1.0","event_id":"sha256:d5b869705187191d66c23a1f7cfc6e07c8dd7afe71e80571307e1f930ffeeb88"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/IX7Z6LRSDJRNOET2JA4SEPLN2N/bundle.json","state_url":"https://pith.science/pith/IX7Z6LRSDJRNOET2JA4SEPLN2N/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/IX7Z6LRSDJRNOET2JA4SEPLN2N/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":"2026-08-08T14:41:38Z","links":{"resolver":"https://pith.science/pith/IX7Z6LRSDJRNOET2JA4SEPLN2N","bundle":"https://pith.science/pith/IX7Z6LRSDJRNOET2JA4SEPLN2N/bundle.json","state":"https://pith.science/pith/IX7Z6LRSDJRNOET2JA4SEPLN2N/state.json","well_known_bundle":"https://pith.science/.well-known/pith/IX7Z6LRSDJRNOET2JA4SEPLN2N/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:IX7Z6LRSDJRNOET2JA4SEPLN2N","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":"bf47724e11dce4803d6b986333ffc35e3ae7aa82ad219c53ca8842af7515a258","cross_cats_sorted":["cs.LG","cs.OS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2020-07-14T02:16:56Z","title_canon_sha256":"940c3e3f0aad18b56fd9e199cc0fa5a898adfd9caed6c95e2338cde0bf130abe"},"schema_version":"1.0","source":{"id":"2007.06775","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2007.06775","created_at":"2026-07-05T02:07:48Z"},{"alias_kind":"arxiv_version","alias_value":"2007.06775v3","created_at":"2026-07-05T02:07:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2007.06775","created_at":"2026-07-05T02:07:48Z"},{"alias_kind":"pith_short_12","alias_value":"IX7Z6LRSDJRN","created_at":"2026-07-05T02:07:48Z"},{"alias_kind":"pith_short_16","alias_value":"IX7Z6LRSDJRNOET2","created_at":"2026-07-05T02:07:48Z"},{"alias_kind":"pith_short_8","alias_value":"IX7Z6LRS","created_at":"2026-07-05T02:07:48Z"}],"graph_snapshots":[{"event_id":"sha256:d5b869705187191d66c23a1f7cfc6e07c8dd7afe71e80571307e1f930ffeeb88","target":"graph","created_at":"2026-07-05T02:07:48Z","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/2007.06775/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Training Deep Neural Networks (DNNs) is resource-intensive and time-consuming. While prior research has explored many different ways of reducing DNN training time, the impact of input data pipeline, i.e., fetching raw data items from storage and performing data pre-processing in memory, has been relatively unexplored. This paper makes the following contributions: (1) We present the first comprehensive analysis of how the input data pipeline affects the training time of widely-used computer vision and audio Deep Neural Networks (DNNs), that typically involve complex data preprocessing. We analy","authors_text":"Amar Phanishayee, Ashish Raniwala, Jayashree Mohan, Vijay Chidambaram","cross_cats":["cs.LG","cs.OS"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2020-07-14T02:16:56Z","title":"Analyzing and Mitigating Data Stalls in DNN Training"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2007.06775","kind":"arxiv","version":3},"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:def4958d1738fbe05ee8d72664a33782fffc73d82850e837617de062599bf806","target":"record","created_at":"2026-07-05T02:07:48Z","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":"bf47724e11dce4803d6b986333ffc35e3ae7aa82ad219c53ca8842af7515a258","cross_cats_sorted":["cs.LG","cs.OS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2020-07-14T02:16:56Z","title_canon_sha256":"940c3e3f0aad18b56fd9e199cc0fa5a898adfd9caed6c95e2338cde0bf130abe"},"schema_version":"1.0","source":{"id":"2007.06775","kind":"arxiv","version":3}},"canonical_sha256":"45ff9f2e321a62d7127a4839223d6dd341735abf53d011c611daee6f96390c38","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"45ff9f2e321a62d7127a4839223d6dd341735abf53d011c611daee6f96390c38","first_computed_at":"2026-07-05T02:07:48.330640Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:07:48.330640Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"mapYibHF1+NU75nBeV8SyQKQgS2LgrfB6HpO4fFvlFGg+P+e9Kng8KeEIcQ/PbGFMwNSDA7sot+r3kZ5QKtIDA==","signature_status":"signed_v1","signed_at":"2026-07-05T02:07:48.331105Z","signed_message":"canonical_sha256_bytes"},"source_id":"2007.06775","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:def4958d1738fbe05ee8d72664a33782fffc73d82850e837617de062599bf806","sha256:d5b869705187191d66c23a1f7cfc6e07c8dd7afe71e80571307e1f930ffeeb88"],"state_sha256":"52320ec2480d9756d20c542c61502f150c2bfcbb35d493df8e70252d54164415"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QeeAuL3YAZvSDfDaUry3Rs4BKZ1X/7JtzgeYHuVKLOUy+8RMZyuTojQIGaQmJAsBg5h3uqvgycn4u5RxDGrOCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T14:41:38.940285Z","bundle_sha256":"105d47922676fbb9deb4d22daba40704cd0f00cc9619c00005e8549229299698"}}