{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:J3UMPLM3KT324D4OEZUHJD3HKT","short_pith_number":"pith:J3UMPLM3","canonical_record":{"source":{"id":"1812.00886","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-11-27T19:20:35Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"15676581283236bf3d35b0d4a94b79bef4b9804ec7f3e3a4997b2190073cb3ca","abstract_canon_sha256":"db2f98f2e109d3498645ae85cd2ab2a7a7c945df664dc9885355dc434ef3e786"},"schema_version":"1.0"},"canonical_sha256":"4ee8c7ad9b54f7ae0f8e2668748f6754d8eaa0e27464374a35dafe253aefae3b","source":{"kind":"arxiv","id":"1812.00886","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1812.00886","created_at":"2026-05-17T23:59:18Z"},{"alias_kind":"arxiv_version","alias_value":"1812.00886v1","created_at":"2026-05-17T23:59:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1812.00886","created_at":"2026-05-17T23:59:18Z"},{"alias_kind":"pith_short_12","alias_value":"J3UMPLM3KT32","created_at":"2026-05-18T12:32:31Z"},{"alias_kind":"pith_short_16","alias_value":"J3UMPLM3KT324D4O","created_at":"2026-05-18T12:32:31Z"},{"alias_kind":"pith_short_8","alias_value":"J3UMPLM3","created_at":"2026-05-18T12:32:31Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:J3UMPLM3KT324D4OEZUHJD3HKT","target":"record","payload":{"canonical_record":{"source":{"id":"1812.00886","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-11-27T19:20:35Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"15676581283236bf3d35b0d4a94b79bef4b9804ec7f3e3a4997b2190073cb3ca","abstract_canon_sha256":"db2f98f2e109d3498645ae85cd2ab2a7a7c945df664dc9885355dc434ef3e786"},"schema_version":"1.0"},"canonical_sha256":"4ee8c7ad9b54f7ae0f8e2668748f6754d8eaa0e27464374a35dafe253aefae3b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:59:18.686761Z","signature_b64":"A0rojEmNB8YyBwmN4NM+kwnUumIqAsJmghYzB9WOcmNzSHQgPEQzTWA+dAELUS6NNXYRzHLn0kVpsxG/PMRIDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4ee8c7ad9b54f7ae0f8e2668748f6754d8eaa0e27464374a35dafe253aefae3b","last_reissued_at":"2026-05-17T23:59:18.686242Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:59:18.686242Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1812.00886","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":"2026-05-17T23:59:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5yulTIS0moYaWf7qZzFMltIS405bSt5yp8eP6fu0251vdrrkiNXWy6JqHphybbbaoD3Lt6WpNcmQyvPkCaY1AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T18:42:44.673673Z"},"content_sha256":"05ff972724d00669b7d5d490395562655b66f00158897146f2c32a36dc3abc67","schema_version":"1.0","event_id":"sha256:05ff972724d00669b7d5d490395562655b66f00158897146f2c32a36dc3abc67"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:J3UMPLM3KT324D4OEZUHJD3HKT","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"AI Matrix - Synthetic Benchmarks for DNN","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Lingjie Xu, Lingling Jin, Tianjun Zhang, Wei Wei, Wei Zhang","submitted_at":"2018-11-27T19:20:35Z","abstract_excerpt":"Deep neural network (DNN) architectures, such as convolutional neural networks (CNN), involve heavy computation and require hardware, such as CPU, GPU, and AI accelerators, to provide the massive computing power. With the many varieties of AI hardware prevailing on the market, it is often hard to decide which one is the best to use. Thus, benchmarking AI hardware effectively becomes important and is of great help to select and optimize AI hardware. Unfortunately, there are few AI benchmarks available in both academia and industry. Examples are BenchNN[1], DeepBench[2], and Dawn Bench[3], which"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1812.00886","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":"2026-05-17T23:59:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jwXDn75G/DwHYjsMZC93KzNxtMNHww6Pw5TgKfw2qnveohTrg95oKX3mo/q1K9uVlpraI/qqKCDDC9KAKgvrDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T18:42:44.674036Z"},"content_sha256":"5c1393d8b46ad7d95d9e8ba7080e539e6fdf7a781a31ed3aea4b4bfea1bcd4a6","schema_version":"1.0","event_id":"sha256:5c1393d8b46ad7d95d9e8ba7080e539e6fdf7a781a31ed3aea4b4bfea1bcd4a6"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/J3UMPLM3KT324D4OEZUHJD3HKT/bundle.json","state_url":"https://pith.science/pith/J3UMPLM3KT324D4OEZUHJD3HKT/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/J3UMPLM3KT324D4OEZUHJD3HKT/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":"2026-05-27T18:42:44Z","links":{"resolver":"https://pith.science/pith/J3UMPLM3KT324D4OEZUHJD3HKT","bundle":"https://pith.science/pith/J3UMPLM3KT324D4OEZUHJD3HKT/bundle.json","state":"https://pith.science/pith/J3UMPLM3KT324D4OEZUHJD3HKT/state.json","well_known_bundle":"https://pith.science/.well-known/pith/J3UMPLM3KT324D4OEZUHJD3HKT/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:J3UMPLM3KT324D4OEZUHJD3HKT","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":"db2f98f2e109d3498645ae85cd2ab2a7a7c945df664dc9885355dc434ef3e786","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-11-27T19:20:35Z","title_canon_sha256":"15676581283236bf3d35b0d4a94b79bef4b9804ec7f3e3a4997b2190073cb3ca"},"schema_version":"1.0","source":{"id":"1812.00886","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1812.00886","created_at":"2026-05-17T23:59:18Z"},{"alias_kind":"arxiv_version","alias_value":"1812.00886v1","created_at":"2026-05-17T23:59:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1812.00886","created_at":"2026-05-17T23:59:18Z"},{"alias_kind":"pith_short_12","alias_value":"J3UMPLM3KT32","created_at":"2026-05-18T12:32:31Z"},{"alias_kind":"pith_short_16","alias_value":"J3UMPLM3KT324D4O","created_at":"2026-05-18T12:32:31Z"},{"alias_kind":"pith_short_8","alias_value":"J3UMPLM3","created_at":"2026-05-18T12:32:31Z"}],"graph_snapshots":[{"event_id":"sha256:5c1393d8b46ad7d95d9e8ba7080e539e6fdf7a781a31ed3aea4b4bfea1bcd4a6","target":"graph","created_at":"2026-05-17T23:59:18Z","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"},"paper":{"abstract_excerpt":"Deep neural network (DNN) architectures, such as convolutional neural networks (CNN), involve heavy computation and require hardware, such as CPU, GPU, and AI accelerators, to provide the massive computing power. With the many varieties of AI hardware prevailing on the market, it is often hard to decide which one is the best to use. Thus, benchmarking AI hardware effectively becomes important and is of great help to select and optimize AI hardware. Unfortunately, there are few AI benchmarks available in both academia and industry. Examples are BenchNN[1], DeepBench[2], and Dawn Bench[3], which","authors_text":"Lingjie Xu, Lingling Jin, Tianjun Zhang, Wei Wei, Wei Zhang","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-11-27T19:20:35Z","title":"AI Matrix - Synthetic Benchmarks for DNN"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1812.00886","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":"sha256:05ff972724d00669b7d5d490395562655b66f00158897146f2c32a36dc3abc67","target":"record","created_at":"2026-05-17T23:59:18Z","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":"db2f98f2e109d3498645ae85cd2ab2a7a7c945df664dc9885355dc434ef3e786","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-11-27T19:20:35Z","title_canon_sha256":"15676581283236bf3d35b0d4a94b79bef4b9804ec7f3e3a4997b2190073cb3ca"},"schema_version":"1.0","source":{"id":"1812.00886","kind":"arxiv","version":1}},"canonical_sha256":"4ee8c7ad9b54f7ae0f8e2668748f6754d8eaa0e27464374a35dafe253aefae3b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4ee8c7ad9b54f7ae0f8e2668748f6754d8eaa0e27464374a35dafe253aefae3b","first_computed_at":"2026-05-17T23:59:18.686242Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:59:18.686242Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"A0rojEmNB8YyBwmN4NM+kwnUumIqAsJmghYzB9WOcmNzSHQgPEQzTWA+dAELUS6NNXYRzHLn0kVpsxG/PMRIDw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:59:18.686761Z","signed_message":"canonical_sha256_bytes"},"source_id":"1812.00886","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:05ff972724d00669b7d5d490395562655b66f00158897146f2c32a36dc3abc67","sha256:5c1393d8b46ad7d95d9e8ba7080e539e6fdf7a781a31ed3aea4b4bfea1bcd4a6"],"state_sha256":"091431a4d4e205c770b3a54097b3f6d8ca92060d85a5eb3d723165f199a5e9b1"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uTgtEGOas7nw24AlS86CSXfEumzxbRHfkOe4/7qjyjoRoE87K+jV3LRUaeJStINu0L+2Nr0lxufLZncfcZiuAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-27T18:42:44.676406Z","bundle_sha256":"8a23c806f4ae67c180a89a3ca28310e5b636f9df51a6168cca72e06ed08e7300"}}