{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:TCICVMHEULGADD67N2W26NNXAS","short_pith_number":"pith:TCICVMHE","canonical_record":{"source":{"id":"2405.07266","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.ET","submitted_at":"2024-05-12T12:20:26Z","cross_cats_sorted":["cs.AR"],"title_canon_sha256":"9326f456369a344d5b2ae3e2601b86b042900d7adcd07a836c34816351ff0e86","abstract_canon_sha256":"b19d23860171e733ceffac469a15bdb0a31163848eefee0f8f26152ca7ad76c2"},"schema_version":"1.0"},"canonical_sha256":"98902ab0e4a2cc018fdf6eadaf35b704aa49fd93c8f09f071e2dda65de98ecee","source":{"kind":"arxiv","id":"2405.07266","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.07266","created_at":"2026-07-05T09:29:14Z"},{"alias_kind":"arxiv_version","alias_value":"2405.07266v2","created_at":"2026-07-05T09:29:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.07266","created_at":"2026-07-05T09:29:14Z"},{"alias_kind":"pith_short_12","alias_value":"TCICVMHEULGA","created_at":"2026-07-05T09:29:14Z"},{"alias_kind":"pith_short_16","alias_value":"TCICVMHEULGADD67","created_at":"2026-07-05T09:29:14Z"},{"alias_kind":"pith_short_8","alias_value":"TCICVMHE","created_at":"2026-07-05T09:29:14Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:TCICVMHEULGADD67N2W26NNXAS","target":"record","payload":{"canonical_record":{"source":{"id":"2405.07266","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.ET","submitted_at":"2024-05-12T12:20:26Z","cross_cats_sorted":["cs.AR"],"title_canon_sha256":"9326f456369a344d5b2ae3e2601b86b042900d7adcd07a836c34816351ff0e86","abstract_canon_sha256":"b19d23860171e733ceffac469a15bdb0a31163848eefee0f8f26152ca7ad76c2"},"schema_version":"1.0"},"canonical_sha256":"98902ab0e4a2cc018fdf6eadaf35b704aa49fd93c8f09f071e2dda65de98ecee","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:29:14.344897Z","signature_b64":"dwipBRzDFXlgLvVE2GkxDlv+g3GFM472V12DRq4Coqg1lqRknWaduJLx0KPdxnRepjOhD1z4a9YX4dNrrHISCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"98902ab0e4a2cc018fdf6eadaf35b704aa49fd93c8f09f071e2dda65de98ecee","last_reissued_at":"2026-07-05T09:29:14.344387Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:29:14.344387Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2405.07266","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:29:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fU4R4PNcaA/kJ7416WvWKuPc9Lg1MgEQZTph199G/uITTLnbbYdop9+0Hv9lb8F/KTA3y+u2RlzT8ypxlRDCDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T08:48:55.545048Z"},"content_sha256":"4e9683804a1df1f37d0679b696beb66ad151a83137c4f7eda118702fa0101c20","schema_version":"1.0","event_id":"sha256:4e9683804a1df1f37d0679b696beb66ad151a83137c4f7eda118702fa0101c20"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:TCICVMHEULGADD67N2W26NNXAS","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Architecture-Level Modeling of Photonic Deep Neural Network Accelerators","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AR"],"primary_cat":"cs.ET","authors_text":"Gohar Irfan Chaudhry, Joel S. Emer, Tanner Andrulis, Vinith M. Suriyakumar, Vivienne Sze","submitted_at":"2024-05-12T12:20:26Z","abstract_excerpt":"Photonics is a promising technology to accelerate Deep Neural Networks as it can use optical interconnects to reduce data movement energy and it enables low-energy, high-throughput optical-analog computations. To realize these benefits in a full system (accelerator + DRAM), designers must ensure that the benefits of using the electrical, optical, analog, and digital domains exceed the costs of converting data between domains. Designers must also consider system-level energy costs such as data fetch from DRAM. Converting data and accessing DRAM can consume significant energy, so to evaluate and"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.07266","kind":"arxiv","version":2},"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/2405.07266/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":"2026-07-05T09:29:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"D/9iZaEaaFSyoi20mF7tCHuDFFRBlzPsEDn4uGkq/jXdZ/4IpUq+djZAxfrxegdSfd1ySNqb4M27Kmt4Vmc+Aw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T08:48:55.545616Z"},"content_sha256":"4e37173d9c06cdd44819c087adcde356e010fd37cf5682337d1869854e44cfee","schema_version":"1.0","event_id":"sha256:4e37173d9c06cdd44819c087adcde356e010fd37cf5682337d1869854e44cfee"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TCICVMHEULGADD67N2W26NNXAS/bundle.json","state_url":"https://pith.science/pith/TCICVMHEULGADD67N2W26NNXAS/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TCICVMHEULGADD67N2W26NNXAS/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":"2026-08-14T08:48:55Z","links":{"resolver":"https://pith.science/pith/TCICVMHEULGADD67N2W26NNXAS","bundle":"https://pith.science/pith/TCICVMHEULGADD67N2W26NNXAS/bundle.json","state":"https://pith.science/pith/TCICVMHEULGADD67N2W26NNXAS/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TCICVMHEULGADD67N2W26NNXAS/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:TCICVMHEULGADD67N2W26NNXAS","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":"b19d23860171e733ceffac469a15bdb0a31163848eefee0f8f26152ca7ad76c2","cross_cats_sorted":["cs.AR"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.ET","submitted_at":"2024-05-12T12:20:26Z","title_canon_sha256":"9326f456369a344d5b2ae3e2601b86b042900d7adcd07a836c34816351ff0e86"},"schema_version":"1.0","source":{"id":"2405.07266","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.07266","created_at":"2026-07-05T09:29:14Z"},{"alias_kind":"arxiv_version","alias_value":"2405.07266v2","created_at":"2026-07-05T09:29:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.07266","created_at":"2026-07-05T09:29:14Z"},{"alias_kind":"pith_short_12","alias_value":"TCICVMHEULGA","created_at":"2026-07-05T09:29:14Z"},{"alias_kind":"pith_short_16","alias_value":"TCICVMHEULGADD67","created_at":"2026-07-05T09:29:14Z"},{"alias_kind":"pith_short_8","alias_value":"TCICVMHE","created_at":"2026-07-05T09:29:14Z"}],"graph_snapshots":[{"event_id":"sha256:4e37173d9c06cdd44819c087adcde356e010fd37cf5682337d1869854e44cfee","target":"graph","created_at":"2026-07-05T09:29:14Z","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/2405.07266/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Photonics is a promising technology to accelerate Deep Neural Networks as it can use optical interconnects to reduce data movement energy and it enables low-energy, high-throughput optical-analog computations. To realize these benefits in a full system (accelerator + DRAM), designers must ensure that the benefits of using the electrical, optical, analog, and digital domains exceed the costs of converting data between domains. Designers must also consider system-level energy costs such as data fetch from DRAM. Converting data and accessing DRAM can consume significant energy, so to evaluate and","authors_text":"Gohar Irfan Chaudhry, Joel S. Emer, Tanner Andrulis, Vinith M. Suriyakumar, Vivienne Sze","cross_cats":["cs.AR"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.ET","submitted_at":"2024-05-12T12:20:26Z","title":"Architecture-Level Modeling of Photonic Deep Neural Network Accelerators"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.07266","kind":"arxiv","version":2},"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":"sha256:4e9683804a1df1f37d0679b696beb66ad151a83137c4f7eda118702fa0101c20","target":"record","created_at":"2026-07-05T09:29:14Z","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":"b19d23860171e733ceffac469a15bdb0a31163848eefee0f8f26152ca7ad76c2","cross_cats_sorted":["cs.AR"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.ET","submitted_at":"2024-05-12T12:20:26Z","title_canon_sha256":"9326f456369a344d5b2ae3e2601b86b042900d7adcd07a836c34816351ff0e86"},"schema_version":"1.0","source":{"id":"2405.07266","kind":"arxiv","version":2}},"canonical_sha256":"98902ab0e4a2cc018fdf6eadaf35b704aa49fd93c8f09f071e2dda65de98ecee","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"98902ab0e4a2cc018fdf6eadaf35b704aa49fd93c8f09f071e2dda65de98ecee","first_computed_at":"2026-07-05T09:29:14.344387Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:29:14.344387Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"dwipBRzDFXlgLvVE2GkxDlv+g3GFM472V12DRq4Coqg1lqRknWaduJLx0KPdxnRepjOhD1z4a9YX4dNrrHISCg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:29:14.344897Z","signed_message":"canonical_sha256_bytes"},"source_id":"2405.07266","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4e9683804a1df1f37d0679b696beb66ad151a83137c4f7eda118702fa0101c20","sha256:4e37173d9c06cdd44819c087adcde356e010fd37cf5682337d1869854e44cfee"],"state_sha256":"217c8cf569ee000304a18bd052968cca8143b3945d202ec1d55f646bd481b4a4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EWHRdl7dmTxEMjHuSnt9c+i1StEk5fBtbrH+o5PAbCDFCYJCtK/KrctZQP/J4llaqDUrJUpNq7nFWSt/6zsAAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-14T08:48:55.549557Z","bundle_sha256":"486127f34bfa806815616b258a16e92158c4c0ad7d36de0379c8e128245bc246"}}