{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:QV55I6IMFP3BPTY5FSDQGKHX2F","short_pith_number":"pith:QV55I6IM","canonical_record":{"source":{"id":"1908.06724","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2019-08-15T18:49:38Z","cross_cats_sorted":["cs.NE","eess.SP"],"title_canon_sha256":"5d61e18fd4eae7d7bc7d36ab307110f408c481d8f4e83d2ff7e62cc76e2bef04","abstract_canon_sha256":"490897a1319ba537ca5cce98abd2eb7f3bf8debae40a1ce76fbb392f9b1dc0e1"},"schema_version":"1.0"},"canonical_sha256":"857bd4790c2bf617cf1d2c870328f7d14418bfcfead6d08d40cd940d8d105c87","source":{"kind":"arxiv","id":"1908.06724","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1908.06724","created_at":"2026-07-04T23:58:18Z"},{"alias_kind":"arxiv_version","alias_value":"1908.06724v1","created_at":"2026-07-04T23:58:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1908.06724","created_at":"2026-07-04T23:58:18Z"},{"alias_kind":"pith_short_12","alias_value":"QV55I6IMFP3B","created_at":"2026-07-04T23:58:18Z"},{"alias_kind":"pith_short_16","alias_value":"QV55I6IMFP3BPTY5","created_at":"2026-07-04T23:58:18Z"},{"alias_kind":"pith_short_8","alias_value":"QV55I6IM","created_at":"2026-07-04T23:58:18Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:QV55I6IMFP3BPTY5FSDQGKHX2F","target":"record","payload":{"canonical_record":{"source":{"id":"1908.06724","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2019-08-15T18:49:38Z","cross_cats_sorted":["cs.NE","eess.SP"],"title_canon_sha256":"5d61e18fd4eae7d7bc7d36ab307110f408c481d8f4e83d2ff7e62cc76e2bef04","abstract_canon_sha256":"490897a1319ba537ca5cce98abd2eb7f3bf8debae40a1ce76fbb392f9b1dc0e1"},"schema_version":"1.0"},"canonical_sha256":"857bd4790c2bf617cf1d2c870328f7d14418bfcfead6d08d40cd940d8d105c87","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-04T23:58:18.863672Z","signature_b64":"SHPSV0yr0UE/jLAwId3SK48T3/a4I+OltekMD9JUKR4vaTLgL2AQFbzlc6+/exflkb8AqvICOLfw0RnVnxZ9DA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"857bd4790c2bf617cf1d2c870328f7d14418bfcfead6d08d40cd940d8d105c87","last_reissued_at":"2026-07-04T23:58:18.863275Z","signature_status":"signed_v1","first_computed_at":"2026-07-04T23:58:18.863275Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1908.06724","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":"2026-07-04T23:58:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AStElhwMkDjrINXzRXovNOOUAcShrVNPaJl9Dk9iaY5ODv5ZgKIfDyKXPckDza6v4/mduoKC75N3X87OP5n0Bw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T20:18:16.759654Z"},"content_sha256":"ab6a42dc50e7504c66847fa48d5ebe07110dfd5b8f2815a3cb41a3c696354994","schema_version":"1.0","event_id":"sha256:ab6a42dc50e7504c66847fa48d5ebe07110dfd5b8f2815a3cb41a3c696354994"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:QV55I6IMFP3BPTY5FSDQGKHX2F","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Automatic Compiler Based FPGA Accelerator for CNN Training","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.NE","eess.SP"],"primary_cat":"cs.LG","authors_text":"Aravind Dasu, Eriko Nurvithadhi, Jae-sun Seo, Shihui Yin, Shreyas Kolala Venkataramanaiah, Yu Cao, Yufei Ma","submitted_at":"2019-08-15T18:49:38Z","abstract_excerpt":"Training of convolutional neural networks (CNNs)on embedded platforms to support on-device learning is earning vital importance in recent days. Designing flexible training hard-ware is much more challenging than inference hardware, due to design complexity and large computation/memory requirement. In this work, we present an automatic compiler-based FPGA accelerator with 16-bit fixed-point precision for complete CNNtraining, including Forward Pass (FP), Backward Pass (BP) and Weight Update (WU). We implemented an optimized RTL library to perform training-specific tasks and developed an RTL com"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1908.06724","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/1908.06724/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":"2026-07-04T23:58:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+1M6pCCabmzBP5P/KHnlzVdoczedNXlai1l4FzSR9gXOgJBz7x4ZMRWgX17RqOBwMy3DiSBNGSmyp4/m/5qAAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T20:18:16.760027Z"},"content_sha256":"fe945e25cb1ffc56609c418a18746c2c051d8deb7ab54f6b0d0d24aac98b3be6","schema_version":"1.0","event_id":"sha256:fe945e25cb1ffc56609c418a18746c2c051d8deb7ab54f6b0d0d24aac98b3be6"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/QV55I6IMFP3BPTY5FSDQGKHX2F/bundle.json","state_url":"https://pith.science/pith/QV55I6IMFP3BPTY5FSDQGKHX2F/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/QV55I6IMFP3BPTY5FSDQGKHX2F/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":"2026-07-06T20:18:16Z","links":{"resolver":"https://pith.science/pith/QV55I6IMFP3BPTY5FSDQGKHX2F","bundle":"https://pith.science/pith/QV55I6IMFP3BPTY5FSDQGKHX2F/bundle.json","state":"https://pith.science/pith/QV55I6IMFP3BPTY5FSDQGKHX2F/state.json","well_known_bundle":"https://pith.science/.well-known/pith/QV55I6IMFP3BPTY5FSDQGKHX2F/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:QV55I6IMFP3BPTY5FSDQGKHX2F","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":"490897a1319ba537ca5cce98abd2eb7f3bf8debae40a1ce76fbb392f9b1dc0e1","cross_cats_sorted":["cs.NE","eess.SP"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2019-08-15T18:49:38Z","title_canon_sha256":"5d61e18fd4eae7d7bc7d36ab307110f408c481d8f4e83d2ff7e62cc76e2bef04"},"schema_version":"1.0","source":{"id":"1908.06724","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1908.06724","created_at":"2026-07-04T23:58:18Z"},{"alias_kind":"arxiv_version","alias_value":"1908.06724v1","created_at":"2026-07-04T23:58:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1908.06724","created_at":"2026-07-04T23:58:18Z"},{"alias_kind":"pith_short_12","alias_value":"QV55I6IMFP3B","created_at":"2026-07-04T23:58:18Z"},{"alias_kind":"pith_short_16","alias_value":"QV55I6IMFP3BPTY5","created_at":"2026-07-04T23:58:18Z"},{"alias_kind":"pith_short_8","alias_value":"QV55I6IM","created_at":"2026-07-04T23:58:18Z"}],"graph_snapshots":[{"event_id":"sha256:fe945e25cb1ffc56609c418a18746c2c051d8deb7ab54f6b0d0d24aac98b3be6","target":"graph","created_at":"2026-07-04T23:58:18Z","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/1908.06724/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Training of convolutional neural networks (CNNs)on embedded platforms to support on-device learning is earning vital importance in recent days. Designing flexible training hard-ware is much more challenging than inference hardware, due to design complexity and large computation/memory requirement. In this work, we present an automatic compiler-based FPGA accelerator with 16-bit fixed-point precision for complete CNNtraining, including Forward Pass (FP), Backward Pass (BP) and Weight Update (WU). We implemented an optimized RTL library to perform training-specific tasks and developed an RTL com","authors_text":"Aravind Dasu, Eriko Nurvithadhi, Jae-sun Seo, Shihui Yin, Shreyas Kolala Venkataramanaiah, Yu Cao, Yufei Ma","cross_cats":["cs.NE","eess.SP"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2019-08-15T18:49:38Z","title":"Automatic Compiler Based FPGA Accelerator for CNN Training"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1908.06724","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:ab6a42dc50e7504c66847fa48d5ebe07110dfd5b8f2815a3cb41a3c696354994","target":"record","created_at":"2026-07-04T23:58:18Z","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":"490897a1319ba537ca5cce98abd2eb7f3bf8debae40a1ce76fbb392f9b1dc0e1","cross_cats_sorted":["cs.NE","eess.SP"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2019-08-15T18:49:38Z","title_canon_sha256":"5d61e18fd4eae7d7bc7d36ab307110f408c481d8f4e83d2ff7e62cc76e2bef04"},"schema_version":"1.0","source":{"id":"1908.06724","kind":"arxiv","version":1}},"canonical_sha256":"857bd4790c2bf617cf1d2c870328f7d14418bfcfead6d08d40cd940d8d105c87","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"857bd4790c2bf617cf1d2c870328f7d14418bfcfead6d08d40cd940d8d105c87","first_computed_at":"2026-07-04T23:58:18.863275Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-04T23:58:18.863275Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"SHPSV0yr0UE/jLAwId3SK48T3/a4I+OltekMD9JUKR4vaTLgL2AQFbzlc6+/exflkb8AqvICOLfw0RnVnxZ9DA==","signature_status":"signed_v1","signed_at":"2026-07-04T23:58:18.863672Z","signed_message":"canonical_sha256_bytes"},"source_id":"1908.06724","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ab6a42dc50e7504c66847fa48d5ebe07110dfd5b8f2815a3cb41a3c696354994","sha256:fe945e25cb1ffc56609c418a18746c2c051d8deb7ab54f6b0d0d24aac98b3be6"],"state_sha256":"180c45105cb61784e3e0c39f9531af7051a2ec52034f234b435670bd028be068"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SiWjlMq3coRUVKFYMppcTEUSqZdvR0i8/HtGkxWQwlRsQZ0OFwjRNCdMeCHXEukh8Ozo913YdGycSS0m/irWCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T20:18:16.762367Z","bundle_sha256":"8fe11799b720ccf694fb83fe2e4e6baa33b1c54b5759e4e629b418f057a5da7f"}}