{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:ZM65BJ6K57LIXSDJRREG5KROPE","short_pith_number":"pith:ZM65BJ6K","canonical_record":{"source":{"id":"2506.03450","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.NE","submitted_at":"2025-06-03T23:21:25Z","cross_cats_sorted":[],"title_canon_sha256":"c7997fba0adb015510fd78633f4a011d01d89ca15cd90ca0ff13f8378672854f","abstract_canon_sha256":"d0bdf3c99f6a8f33434dc5eff0656eb838482441c1900ebf2a68899d5fdc2d08"},"schema_version":"1.0"},"canonical_sha256":"cb3dd0a7caefd68bc8698c486eaa2e7900339475816a7d9d00fa4c16c0ac77ce","source":{"kind":"arxiv","id":"2506.03450","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.03450","created_at":"2026-07-05T11:22:18Z"},{"alias_kind":"arxiv_version","alias_value":"2506.03450v2","created_at":"2026-07-05T11:22:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.03450","created_at":"2026-07-05T11:22:18Z"},{"alias_kind":"pith_short_12","alias_value":"ZM65BJ6K57LI","created_at":"2026-07-05T11:22:18Z"},{"alias_kind":"pith_short_16","alias_value":"ZM65BJ6K57LIXSDJ","created_at":"2026-07-05T11:22:18Z"},{"alias_kind":"pith_short_8","alias_value":"ZM65BJ6K","created_at":"2026-07-05T11:22:18Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:ZM65BJ6K57LIXSDJRREG5KROPE","target":"record","payload":{"canonical_record":{"source":{"id":"2506.03450","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.NE","submitted_at":"2025-06-03T23:21:25Z","cross_cats_sorted":[],"title_canon_sha256":"c7997fba0adb015510fd78633f4a011d01d89ca15cd90ca0ff13f8378672854f","abstract_canon_sha256":"d0bdf3c99f6a8f33434dc5eff0656eb838482441c1900ebf2a68899d5fdc2d08"},"schema_version":"1.0"},"canonical_sha256":"cb3dd0a7caefd68bc8698c486eaa2e7900339475816a7d9d00fa4c16c0ac77ce","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:22:18.817061Z","signature_b64":"hWhz66K7va/35FU/j2aUbyka93UJkTSlcjCRRhA5iD0RyBThUXmim4oQrjq1GRuPV1aEZEUNMQXHAtWKRYe2Cw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"cb3dd0a7caefd68bc8698c486eaa2e7900339475816a7d9d00fa4c16c0ac77ce","last_reissued_at":"2026-07-05T11:22:18.816508Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:22:18.816508Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2506.03450","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":"2026-07-05T11:22:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KQ+gcaSTrn3XPqRn3NPhGFlxkBsN9zrO0BXsSkuUlInliWvRgjR2QYwSUK8EVspFrczJuDanqpv9CBIGyPMlAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T01:33:22.547845Z"},"content_sha256":"b3c9f54c9e24255c04feb882e26e7b3d74e132c8dec5fa6775753e5c6045414b","schema_version":"1.0","event_id":"sha256:b3c9f54c9e24255c04feb882e26e7b3d74e132c8dec5fa6775753e5c6045414b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:ZM65BJ6K57LIXSDJRREG5KROPE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.NE","authors_text":"Alexandra F Dobrita, Amirreza Yousefzadeh, Gert-Jan van Schaik, Guangzhi Tang, Kanishkan Vadivel, Kevin Shidqi, Manolis Sifalakis, Mario Konijnenburg, Oliver Rhodes, Paul Detterer, Prithvish V Nembhani, YingFu Xu, Zaid Al-Ars","submitted_at":"2025-06-03T23:21:25Z","abstract_excerpt":"This paper introduces SENMap, a mapping and synthesis tool for scalable, energy-efficient neuromorphic computing architecture frameworks. SENECA is a flexible architectural design optimized for executing edge AI SNN/ANN inference applications efficiently. To speed up the silicon tape-out and chip design for SENECA, an accurate emulator, SENSIM, was designed. While SENSIM supports direct mapping of SNNs on neuromorphic architectures, as the SNN and ANNs grow in size, achieving optimal mapping for objectives like energy, throughput, area, and accuracy becomes challenging. This paper introduces S"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.03450","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/2506.03450/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":"2026-07-05T11:22:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"joE5LITST/rYenbJp7xZAjEl8FneQpJIF8Uln4l/j57iA4R322XRCFJSUqZZ3S7aJEbsYBhsCP4W13Oq7fyTAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T01:33:22.548348Z"},"content_sha256":"6b43ad79ab4d7834aa5e8f91f2376aa3ef11ae5fbe46add7b92f19316d3950e5","schema_version":"1.0","event_id":"sha256:6b43ad79ab4d7834aa5e8f91f2376aa3ef11ae5fbe46add7b92f19316d3950e5"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZM65BJ6K57LIXSDJRREG5KROPE/bundle.json","state_url":"https://pith.science/pith/ZM65BJ6K57LIXSDJRREG5KROPE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZM65BJ6K57LIXSDJRREG5KROPE/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":"2026-08-08T01:33:22Z","links":{"resolver":"https://pith.science/pith/ZM65BJ6K57LIXSDJRREG5KROPE","bundle":"https://pith.science/pith/ZM65BJ6K57LIXSDJRREG5KROPE/bundle.json","state":"https://pith.science/pith/ZM65BJ6K57LIXSDJRREG5KROPE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZM65BJ6K57LIXSDJRREG5KROPE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:ZM65BJ6K57LIXSDJRREG5KROPE","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":"d0bdf3c99f6a8f33434dc5eff0656eb838482441c1900ebf2a68899d5fdc2d08","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.NE","submitted_at":"2025-06-03T23:21:25Z","title_canon_sha256":"c7997fba0adb015510fd78633f4a011d01d89ca15cd90ca0ff13f8378672854f"},"schema_version":"1.0","source":{"id":"2506.03450","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.03450","created_at":"2026-07-05T11:22:18Z"},{"alias_kind":"arxiv_version","alias_value":"2506.03450v2","created_at":"2026-07-05T11:22:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.03450","created_at":"2026-07-05T11:22:18Z"},{"alias_kind":"pith_short_12","alias_value":"ZM65BJ6K57LI","created_at":"2026-07-05T11:22:18Z"},{"alias_kind":"pith_short_16","alias_value":"ZM65BJ6K57LIXSDJ","created_at":"2026-07-05T11:22:18Z"},{"alias_kind":"pith_short_8","alias_value":"ZM65BJ6K","created_at":"2026-07-05T11:22:18Z"}],"graph_snapshots":[{"event_id":"sha256:6b43ad79ab4d7834aa5e8f91f2376aa3ef11ae5fbe46add7b92f19316d3950e5","target":"graph","created_at":"2026-07-05T11:22:18Z","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/2506.03450/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper introduces SENMap, a mapping and synthesis tool for scalable, energy-efficient neuromorphic computing architecture frameworks. SENECA is a flexible architectural design optimized for executing edge AI SNN/ANN inference applications efficiently. To speed up the silicon tape-out and chip design for SENECA, an accurate emulator, SENSIM, was designed. While SENSIM supports direct mapping of SNNs on neuromorphic architectures, as the SNN and ANNs grow in size, achieving optimal mapping for objectives like energy, throughput, area, and accuracy becomes challenging. This paper introduces S","authors_text":"Alexandra F Dobrita, Amirreza Yousefzadeh, Gert-Jan van Schaik, Guangzhi Tang, Kanishkan Vadivel, Kevin Shidqi, Manolis Sifalakis, Mario Konijnenburg, Oliver Rhodes, Paul Detterer, Prithvish V Nembhani, YingFu Xu, Zaid Al-Ars","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.NE","submitted_at":"2025-06-03T23:21:25Z","title":"SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.03450","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:b3c9f54c9e24255c04feb882e26e7b3d74e132c8dec5fa6775753e5c6045414b","target":"record","created_at":"2026-07-05T11:22:18Z","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":"d0bdf3c99f6a8f33434dc5eff0656eb838482441c1900ebf2a68899d5fdc2d08","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.NE","submitted_at":"2025-06-03T23:21:25Z","title_canon_sha256":"c7997fba0adb015510fd78633f4a011d01d89ca15cd90ca0ff13f8378672854f"},"schema_version":"1.0","source":{"id":"2506.03450","kind":"arxiv","version":2}},"canonical_sha256":"cb3dd0a7caefd68bc8698c486eaa2e7900339475816a7d9d00fa4c16c0ac77ce","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"cb3dd0a7caefd68bc8698c486eaa2e7900339475816a7d9d00fa4c16c0ac77ce","first_computed_at":"2026-07-05T11:22:18.816508Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:22:18.816508Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"hWhz66K7va/35FU/j2aUbyka93UJkTSlcjCRRhA5iD0RyBThUXmim4oQrjq1GRuPV1aEZEUNMQXHAtWKRYe2Cw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:22:18.817061Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.03450","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b3c9f54c9e24255c04feb882e26e7b3d74e132c8dec5fa6775753e5c6045414b","sha256:6b43ad79ab4d7834aa5e8f91f2376aa3ef11ae5fbe46add7b92f19316d3950e5"],"state_sha256":"fd7f9fe1b3fd74d4eaccf0cce9a3def9d89636fc25ac133fc13fd0a6900d6685"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"75IlJ20ozyP7l74lp+XozVhKswPvhzD8RDPg80HssMTohVCvcFctK42N1wwv7jrolIczll9g4F0eoutvpExcAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T01:33:22.552114Z","bundle_sha256":"2333ac11f41d0660a3cfda214e6d926a09880a652da0b86193a0e6cb0b2cb5a4"}}