{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:QUXAEPQ6KJGVYNNTANLP52WV6U","short_pith_number":"pith:QUXAEPQ6","schema_version":"1.0","canonical_sha256":"852e023e1e524d5c35b30356feead5f52c8ba4c74a286615b8d65607147d63eb","source":{"kind":"arxiv","id":"2404.16208","version":1},"attestation_state":"computed","paper":{"title":"GPU-RANC: A CUDA Accelerated Simulation Framework for Neuromorphic Architectures","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.ET","authors_text":"Ali Akoglu, Ilkin Aliyev, Joshua Mack, Maisha Hafiz, Michael Inouye, Miguel C. Gonzalez, Sahil Hassan","submitted_at":"2024-04-24T21:08:21Z","abstract_excerpt":"Open-source simulation tools play a crucial role for neuromorphic application engineers and hardware architects to investigate performance bottlenecks and explore design optimizations before committing to silicon. Reconfigurable Architecture for Neuromorphic Computing (RANC) is one such tool that offers ability to execute pre-trained Spiking Neural Network (SNN) models within a unified ecosystem through both software-based simulation and FPGA-based emulation. RANC has been utilized by the community with its flexible and highly parameterized design to study implementation bottlenecks, tune arch"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2404.16208","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.ET","submitted_at":"2024-04-24T21:08:21Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"16b13c7a65c095c3c9e319df227156cd7469568aabab5d656f9f8ea3a99c0e1f","abstract_canon_sha256":"ed463b44a7692d620cf908dd79161524f90c97fe1407063aeb65379cf9b618e7"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:12:02.781726Z","signature_b64":"4S1MP+6YFP/k7r3/ci7kR1sLqD9PjYii0r4flI4E4RBI0Q5d4ICab5kcvoc+2P5AZDeicyaXynyTHSXR+MS7Cw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"852e023e1e524d5c35b30356feead5f52c8ba4c74a286615b8d65607147d63eb","last_reissued_at":"2026-07-05T08:12:02.781262Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:12:02.781262Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"GPU-RANC: A CUDA Accelerated Simulation Framework for Neuromorphic Architectures","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.ET","authors_text":"Ali Akoglu, Ilkin Aliyev, Joshua Mack, Maisha Hafiz, Michael Inouye, Miguel C. Gonzalez, Sahil Hassan","submitted_at":"2024-04-24T21:08:21Z","abstract_excerpt":"Open-source simulation tools play a crucial role for neuromorphic application engineers and hardware architects to investigate performance bottlenecks and explore design optimizations before committing to silicon. Reconfigurable Architecture for Neuromorphic Computing (RANC) is one such tool that offers ability to execute pre-trained Spiking Neural Network (SNN) models within a unified ecosystem through both software-based simulation and FPGA-based emulation. RANC has been utilized by the community with its flexible and highly parameterized design to study implementation bottlenecks, tune arch"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.16208","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/2404.16208/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2404.16208","created_at":"2026-07-05T08:12:02.781326+00:00"},{"alias_kind":"arxiv_version","alias_value":"2404.16208v1","created_at":"2026-07-05T08:12:02.781326+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.16208","created_at":"2026-07-05T08:12:02.781326+00:00"},{"alias_kind":"pith_short_12","alias_value":"QUXAEPQ6KJGV","created_at":"2026-07-05T08:12:02.781326+00:00"},{"alias_kind":"pith_short_16","alias_value":"QUXAEPQ6KJGVYNNT","created_at":"2026-07-05T08:12:02.781326+00:00"},{"alias_kind":"pith_short_8","alias_value":"QUXAEPQ6","created_at":"2026-07-05T08:12:02.781326+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/QUXAEPQ6KJGVYNNTANLP52WV6U","json":"https://pith.science/pith/QUXAEPQ6KJGVYNNTANLP52WV6U.json","graph_json":"https://pith.science/api/pith-number/QUXAEPQ6KJGVYNNTANLP52WV6U/graph.json","events_json":"https://pith.science/api/pith-number/QUXAEPQ6KJGVYNNTANLP52WV6U/events.json","paper":"https://pith.science/paper/QUXAEPQ6"},"agent_actions":{"view_html":"https://pith.science/pith/QUXAEPQ6KJGVYNNTANLP52WV6U","download_json":"https://pith.science/pith/QUXAEPQ6KJGVYNNTANLP52WV6U.json","view_paper":"https://pith.science/paper/QUXAEPQ6","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2404.16208&json=true","fetch_graph":"https://pith.science/api/pith-number/QUXAEPQ6KJGVYNNTANLP52WV6U/graph.json","fetch_events":"https://pith.science/api/pith-number/QUXAEPQ6KJGVYNNTANLP52WV6U/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/QUXAEPQ6KJGVYNNTANLP52WV6U/action/timestamp_anchor","attest_storage":"https://pith.science/pith/QUXAEPQ6KJGVYNNTANLP52WV6U/action/storage_attestation","attest_author":"https://pith.science/pith/QUXAEPQ6KJGVYNNTANLP52WV6U/action/author_attestation","sign_citation":"https://pith.science/pith/QUXAEPQ6KJGVYNNTANLP52WV6U/action/citation_signature","submit_replication":"https://pith.science/pith/QUXAEPQ6KJGVYNNTANLP52WV6U/action/replication_record"}},"created_at":"2026-07-05T08:12:02.781326+00:00","updated_at":"2026-07-05T08:12:02.781326+00:00"}