{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:S7YO3POCMZGVUVFWRQITWT42D5","short_pith_number":"pith:S7YO3POC","canonical_record":{"source":{"id":"1907.01989","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-07-03T15:23:20Z","cross_cats_sorted":["cs.CV","cs.DC","stat.ML"],"title_canon_sha256":"b16cbcc796fd58c566c68ed2c910544775083f6a0b53de08a1470f40444c0fd2","abstract_canon_sha256":"93e74ad9c4544920cade58f6d049c4eec6b6f59f6e46aa6e3485a113796e49cf"},"schema_version":"1.0"},"canonical_sha256":"97f0edbdc2664d5a54b68c113b4f9a1f63cd852f7fd31fb97521c754b40f9723","source":{"kind":"arxiv","id":"1907.01989","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.01989","created_at":"2026-07-05T00:12:02Z"},{"alias_kind":"arxiv_version","alias_value":"1907.01989v1","created_at":"2026-07-05T00:12:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.01989","created_at":"2026-07-05T00:12:02Z"},{"alias_kind":"pith_short_12","alias_value":"S7YO3POCMZGV","created_at":"2026-07-05T00:12:02Z"},{"alias_kind":"pith_short_16","alias_value":"S7YO3POCMZGVUVFW","created_at":"2026-07-05T00:12:02Z"},{"alias_kind":"pith_short_8","alias_value":"S7YO3POC","created_at":"2026-07-05T00:12:02Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:S7YO3POCMZGVUVFWRQITWT42D5","target":"record","payload":{"canonical_record":{"source":{"id":"1907.01989","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-07-03T15:23:20Z","cross_cats_sorted":["cs.CV","cs.DC","stat.ML"],"title_canon_sha256":"b16cbcc796fd58c566c68ed2c910544775083f6a0b53de08a1470f40444c0fd2","abstract_canon_sha256":"93e74ad9c4544920cade58f6d049c4eec6b6f59f6e46aa6e3485a113796e49cf"},"schema_version":"1.0"},"canonical_sha256":"97f0edbdc2664d5a54b68c113b4f9a1f63cd852f7fd31fb97521c754b40f9723","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:12:02.121067Z","signature_b64":"Kwta6MTnSTj/II9d8cOgeA2mPAmfkyygJqzOZwuGV0NRG+hqh96PZNFVFs294A1rStt3i2v2dWC48q0Quk95CQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"97f0edbdc2664d5a54b68c113b4f9a1f63cd852f7fd31fb97521c754b40f9723","last_reissued_at":"2026-07-05T00:12:02.120603Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:12:02.120603Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1907.01989","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":"2026-07-05T00:12:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aXMX8zk7ZukhERQUAMEIygVuBXkYgRu4U7BMUhxD7eyctJB0CxosQ14FN8BEg23fuqs+KUyUzUdXcOCUnRXaBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-05T14:36:34.423106Z"},"content_sha256":"5dcfc3cbff28d9b235a5a4581baac1738d3b4883dbac4516f0695c793a9897ef","schema_version":"1.0","event_id":"sha256:5dcfc3cbff28d9b235a5a4581baac1738d3b4883dbac4516f0695c793a9897ef"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:S7YO3POCMZGVUVFWRQITWT42D5","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"On-Device Neural Net Inference with Mobile GPUs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV","cs.DC","stat.ML"],"primary_cat":"cs.LG","authors_text":"Andrei Kulik, Ekaterina Ignasheva, Fabio Riccardi, Juhyun Lee, Matthias Grundmann, Mogan Shieh, Nikolay Chirkov, Raman Sarokin, Yury Pisarchyk","submitted_at":"2019-07-03T15:23:20Z","abstract_excerpt":"On-device inference of machine learning models for mobile phones is desirable due to its lower latency and increased privacy. Running such a compute-intensive task solely on the mobile CPU, however, can be difficult due to limited computing power, thermal constraints, and energy consumption. App developers and researchers have begun exploiting hardware accelerators to overcome these challenges. Recently, device manufacturers are adding neural processing units into high-end phones for on-device inference, but these account for only a small fraction of hand-held devices. In this paper, we presen"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.01989","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/1907.01989/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":"2026-07-05T00:12:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"i4qbk3SUwr3qD3IDu2udggC5risYWflH0t7pMiFvZVerjsPZzPAX0BjunmdoTaoxLLdehJ3lrZcaLWQgxzzBCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-05T14:36:34.423503Z"},"content_sha256":"e1d5f62a4c6239d3a7704437286719f39b564d041f9e4bc929fbd934e4e7a768","schema_version":"1.0","event_id":"sha256:e1d5f62a4c6239d3a7704437286719f39b564d041f9e4bc929fbd934e4e7a768"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/S7YO3POCMZGVUVFWRQITWT42D5/bundle.json","state_url":"https://pith.science/pith/S7YO3POCMZGVUVFWRQITWT42D5/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/S7YO3POCMZGVUVFWRQITWT42D5/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":"2026-07-05T14:36:34Z","links":{"resolver":"https://pith.science/pith/S7YO3POCMZGVUVFWRQITWT42D5","bundle":"https://pith.science/pith/S7YO3POCMZGVUVFWRQITWT42D5/bundle.json","state":"https://pith.science/pith/S7YO3POCMZGVUVFWRQITWT42D5/state.json","well_known_bundle":"https://pith.science/.well-known/pith/S7YO3POCMZGVUVFWRQITWT42D5/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:S7YO3POCMZGVUVFWRQITWT42D5","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":"93e74ad9c4544920cade58f6d049c4eec6b6f59f6e46aa6e3485a113796e49cf","cross_cats_sorted":["cs.CV","cs.DC","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-07-03T15:23:20Z","title_canon_sha256":"b16cbcc796fd58c566c68ed2c910544775083f6a0b53de08a1470f40444c0fd2"},"schema_version":"1.0","source":{"id":"1907.01989","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.01989","created_at":"2026-07-05T00:12:02Z"},{"alias_kind":"arxiv_version","alias_value":"1907.01989v1","created_at":"2026-07-05T00:12:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.01989","created_at":"2026-07-05T00:12:02Z"},{"alias_kind":"pith_short_12","alias_value":"S7YO3POCMZGV","created_at":"2026-07-05T00:12:02Z"},{"alias_kind":"pith_short_16","alias_value":"S7YO3POCMZGVUVFW","created_at":"2026-07-05T00:12:02Z"},{"alias_kind":"pith_short_8","alias_value":"S7YO3POC","created_at":"2026-07-05T00:12:02Z"}],"graph_snapshots":[{"event_id":"sha256:e1d5f62a4c6239d3a7704437286719f39b564d041f9e4bc929fbd934e4e7a768","target":"graph","created_at":"2026-07-05T00:12:02Z","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/1907.01989/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"On-device inference of machine learning models for mobile phones is desirable due to its lower latency and increased privacy. Running such a compute-intensive task solely on the mobile CPU, however, can be difficult due to limited computing power, thermal constraints, and energy consumption. App developers and researchers have begun exploiting hardware accelerators to overcome these challenges. Recently, device manufacturers are adding neural processing units into high-end phones for on-device inference, but these account for only a small fraction of hand-held devices. In this paper, we presen","authors_text":"Andrei Kulik, Ekaterina Ignasheva, Fabio Riccardi, Juhyun Lee, Matthias Grundmann, Mogan Shieh, Nikolay Chirkov, Raman Sarokin, Yury Pisarchyk","cross_cats":["cs.CV","cs.DC","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-07-03T15:23:20Z","title":"On-Device Neural Net Inference with Mobile GPUs"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.01989","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":"sha256:5dcfc3cbff28d9b235a5a4581baac1738d3b4883dbac4516f0695c793a9897ef","target":"record","created_at":"2026-07-05T00:12:02Z","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":"93e74ad9c4544920cade58f6d049c4eec6b6f59f6e46aa6e3485a113796e49cf","cross_cats_sorted":["cs.CV","cs.DC","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-07-03T15:23:20Z","title_canon_sha256":"b16cbcc796fd58c566c68ed2c910544775083f6a0b53de08a1470f40444c0fd2"},"schema_version":"1.0","source":{"id":"1907.01989","kind":"arxiv","version":1}},"canonical_sha256":"97f0edbdc2664d5a54b68c113b4f9a1f63cd852f7fd31fb97521c754b40f9723","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"97f0edbdc2664d5a54b68c113b4f9a1f63cd852f7fd31fb97521c754b40f9723","first_computed_at":"2026-07-05T00:12:02.120603Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:12:02.120603Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Kwta6MTnSTj/II9d8cOgeA2mPAmfkyygJqzOZwuGV0NRG+hqh96PZNFVFs294A1rStt3i2v2dWC48q0Quk95CQ==","signature_status":"signed_v1","signed_at":"2026-07-05T00:12:02.121067Z","signed_message":"canonical_sha256_bytes"},"source_id":"1907.01989","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5dcfc3cbff28d9b235a5a4581baac1738d3b4883dbac4516f0695c793a9897ef","sha256:e1d5f62a4c6239d3a7704437286719f39b564d041f9e4bc929fbd934e4e7a768"],"state_sha256":"ad71d69bc469c650bda2bc43a331c26625e0e979805b9201687cded601dac4e1"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yoE4/Phcjz2REb9XEceQdsGhx6Pb7a12N6oD3Vvtps79RlEZ96c4tldX90/RNc9l9RMHb9IekiOQzNVltOjpBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-05T14:36:34.426086Z","bundle_sha256":"b3d94eb7f923165bf9457254d7d924c9807efb1ebe8cd867f3dc8c51d5862de7"}}