{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:WPVAPO6A757YX4IWNXAVKWPW43","short_pith_number":"pith:WPVAPO6A","canonical_record":{"source":{"id":"1805.00361","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-04-30T17:36:14Z","cross_cats_sorted":["cs.LG","stat.ML"],"title_canon_sha256":"295b274b89c30403983e73fee404fa329402d66bacea2b149bb75461b46a3102","abstract_canon_sha256":"ee37f6ed8727597d194f3b0b6bcb1fc789d99f35e41cab702e29bec6064d65ff"},"schema_version":"1.0"},"canonical_sha256":"b3ea07bbc0ff7f8bf1166dc15559f6e6d15a2498220fd082b250ff3d57bae2a4","source":{"kind":"arxiv","id":"1805.00361","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1805.00361","created_at":"2026-05-18T00:16:58Z"},{"alias_kind":"arxiv_version","alias_value":"1805.00361v1","created_at":"2026-05-18T00:16:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1805.00361","created_at":"2026-05-18T00:16:58Z"},{"alias_kind":"pith_short_12","alias_value":"WPVAPO6A757Y","created_at":"2026-05-18T12:33:01Z"},{"alias_kind":"pith_short_16","alias_value":"WPVAPO6A757YX4IW","created_at":"2026-05-18T12:33:01Z"},{"alias_kind":"pith_short_8","alias_value":"WPVAPO6A","created_at":"2026-05-18T12:33:01Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:WPVAPO6A757YX4IWNXAVKWPW43","target":"record","payload":{"canonical_record":{"source":{"id":"1805.00361","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-04-30T17:36:14Z","cross_cats_sorted":["cs.LG","stat.ML"],"title_canon_sha256":"295b274b89c30403983e73fee404fa329402d66bacea2b149bb75461b46a3102","abstract_canon_sha256":"ee37f6ed8727597d194f3b0b6bcb1fc789d99f35e41cab702e29bec6064d65ff"},"schema_version":"1.0"},"canonical_sha256":"b3ea07bbc0ff7f8bf1166dc15559f6e6d15a2498220fd082b250ff3d57bae2a4","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:16:58.770370Z","signature_b64":"mCHPF13o8bqcRc/77AWmdIL4Om14sCQKoEiiS+ovT0acL/qxDkh6padTlt3hPyMx149sCTWc36a9mU8wvISEBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b3ea07bbc0ff7f8bf1166dc15559f6e6d15a2498220fd082b250ff3d57bae2a4","last_reissued_at":"2026-05-18T00:16:58.769592Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:16:58.769592Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1805.00361","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":"2026-05-18T00:16:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YlTlGGpokwFUbGxkk6IwcMw6XpkiSLUbVKiEnZFlazfRyIO9qNIcWtB7huUP2L3m4pU2ATJLocCqGhKaBogQAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-27T20:47:48.243129Z"},"content_sha256":"ac3120c17c6c7b39d56af3d30fc45a8eb12f173384b0b5a930c003d596a09744","schema_version":"1.0","event_id":"sha256:ac3120c17c6c7b39d56af3d30fc45a8eb12f173384b0b5a930c003d596a09744"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:WPVAPO6A757YX4IWNXAVKWPW43","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Ultra Power-Efficient CNN Domain Specific Accelerator with 9.3TOPS/Watt for Mobile and Embedded Applications","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","stat.ML"],"primary_cat":"cs.CV","authors_text":"Baohua Sun, Charles Young, Jason Dong, Lin Yang, Patrick Dong, Wenhan Zhang","submitted_at":"2018-04-30T17:36:14Z","abstract_excerpt":"Computer vision performances have been significantly improved in recent years by Convolutional Neural Networks(CNN). Currently, applications using CNN algorithms are deployed mainly on general purpose hardwares, such as CPUs, GPUs or FPGAs. However, power consumption, speed, accuracy, memory footprint, and die size should all be taken into consideration for mobile and embedded applications. Domain Specific Architecture (DSA) for CNN is the efficient and practical solution for CNN deployment and implementation. We designed and produced a 28nm Two-Dimensional CNN-DSA accelerator with an ultra po"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1805.00361","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":""},"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":"2026-05-18T00:16:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Fn1ckvMdZIbABE6hgW2HzyoAp4oGcBT+gC4zBoc+b5QfXjz26UuA63GHYe/lPBCZgej/RiIcPaEADDlEqu11CA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-27T20:47:48.243487Z"},"content_sha256":"672f4ec15866385ebc49c8eb67f0633de2cfbf060e3ff887e5f9a0fe84c85528","schema_version":"1.0","event_id":"sha256:672f4ec15866385ebc49c8eb67f0633de2cfbf060e3ff887e5f9a0fe84c85528"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WPVAPO6A757YX4IWNXAVKWPW43/bundle.json","state_url":"https://pith.science/pith/WPVAPO6A757YX4IWNXAVKWPW43/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WPVAPO6A757YX4IWNXAVKWPW43/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":"2026-06-27T20:47:48Z","links":{"resolver":"https://pith.science/pith/WPVAPO6A757YX4IWNXAVKWPW43","bundle":"https://pith.science/pith/WPVAPO6A757YX4IWNXAVKWPW43/bundle.json","state":"https://pith.science/pith/WPVAPO6A757YX4IWNXAVKWPW43/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WPVAPO6A757YX4IWNXAVKWPW43/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:WPVAPO6A757YX4IWNXAVKWPW43","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":"ee37f6ed8727597d194f3b0b6bcb1fc789d99f35e41cab702e29bec6064d65ff","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-04-30T17:36:14Z","title_canon_sha256":"295b274b89c30403983e73fee404fa329402d66bacea2b149bb75461b46a3102"},"schema_version":"1.0","source":{"id":"1805.00361","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1805.00361","created_at":"2026-05-18T00:16:58Z"},{"alias_kind":"arxiv_version","alias_value":"1805.00361v1","created_at":"2026-05-18T00:16:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1805.00361","created_at":"2026-05-18T00:16:58Z"},{"alias_kind":"pith_short_12","alias_value":"WPVAPO6A757Y","created_at":"2026-05-18T12:33:01Z"},{"alias_kind":"pith_short_16","alias_value":"WPVAPO6A757YX4IW","created_at":"2026-05-18T12:33:01Z"},{"alias_kind":"pith_short_8","alias_value":"WPVAPO6A","created_at":"2026-05-18T12:33:01Z"}],"graph_snapshots":[{"event_id":"sha256:672f4ec15866385ebc49c8eb67f0633de2cfbf060e3ff887e5f9a0fe84c85528","target":"graph","created_at":"2026-05-18T00:16:58Z","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":"Computer vision performances have been significantly improved in recent years by Convolutional Neural Networks(CNN). Currently, applications using CNN algorithms are deployed mainly on general purpose hardwares, such as CPUs, GPUs or FPGAs. However, power consumption, speed, accuracy, memory footprint, and die size should all be taken into consideration for mobile and embedded applications. Domain Specific Architecture (DSA) for CNN is the efficient and practical solution for CNN deployment and implementation. We designed and produced a 28nm Two-Dimensional CNN-DSA accelerator with an ultra po","authors_text":"Baohua Sun, Charles Young, Jason Dong, Lin Yang, Patrick Dong, Wenhan Zhang","cross_cats":["cs.LG","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-04-30T17:36:14Z","title":"Ultra Power-Efficient CNN Domain Specific Accelerator with 9.3TOPS/Watt for Mobile and Embedded Applications"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1805.00361","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:ac3120c17c6c7b39d56af3d30fc45a8eb12f173384b0b5a930c003d596a09744","target":"record","created_at":"2026-05-18T00:16:58Z","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":"ee37f6ed8727597d194f3b0b6bcb1fc789d99f35e41cab702e29bec6064d65ff","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-04-30T17:36:14Z","title_canon_sha256":"295b274b89c30403983e73fee404fa329402d66bacea2b149bb75461b46a3102"},"schema_version":"1.0","source":{"id":"1805.00361","kind":"arxiv","version":1}},"canonical_sha256":"b3ea07bbc0ff7f8bf1166dc15559f6e6d15a2498220fd082b250ff3d57bae2a4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b3ea07bbc0ff7f8bf1166dc15559f6e6d15a2498220fd082b250ff3d57bae2a4","first_computed_at":"2026-05-18T00:16:58.769592Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:16:58.769592Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"mCHPF13o8bqcRc/77AWmdIL4Om14sCQKoEiiS+ovT0acL/qxDkh6padTlt3hPyMx149sCTWc36a9mU8wvISEBw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:16:58.770370Z","signed_message":"canonical_sha256_bytes"},"source_id":"1805.00361","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ac3120c17c6c7b39d56af3d30fc45a8eb12f173384b0b5a930c003d596a09744","sha256:672f4ec15866385ebc49c8eb67f0633de2cfbf060e3ff887e5f9a0fe84c85528"],"state_sha256":"ea6fed21baced94ecf68be5340336e4f5612aea839fc7fa81d5c241a43c5eee2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tz+X6NSJEW8AVBiQvMY2f4Rr4egzqeYgQCQWW+0bA1+b+hA74/ocAuj1cuyIoJ2MWpJzg+0sns8f8oteJqqdBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-27T20:47:48.245348Z","bundle_sha256":"aa96a77deb33716bc2e366b0e72067cb383904ef275491859507f7d9378f2017"}}