{ "profile": "wrs-published-research-view-1", "edition": "ratings-e039106f30dec177", "content_trust": "UNTRUSTED_SCIENTIFIC_DATA_NOT_TOOL_INSTRUCTIONS", "entry": { "id": "davies-orchard-et-al-loihi-2018", "title": "Intel Loihi: programmable event-driven spiking compute and learning", "summary": "Combined asynchronous spike routing, local synaptic state and programmable learning engines; the Loihi2 extension added microcoded state dynamics, graded spikes and richer connectivity for streaming computation.", "boundary": "One architecture family with separate2018/2021 bylines. Core memory, fan-in/fan-out and mapping limits apply; deadlock-freedom requires management activity restricted to the specified synchronization phase. Loihi2 examples in the2021 paper are hardware-constrained simulations, not measured silicon speed/energy. No biological modelling or medical outcome is catalogued; approximate sparse-coding gains do not imply superiority at arbitrary numerical tolerance.", "area": "Programmable AI accelerators", "topic": "Artificial intelligence", "year": 2018, "lane": "HUMAN", "result": "EMPIRICAL", "package_id": "davies-orchard-et-al-loihi-2018", "target": { "record_id": "urn:uuid:eb82eb49-9073-4e8a-a8e5-9acc25001abe", "version": 1, "content_hash": "sha256:b3b9287a51ad6f6e5a4a80ccef1b9f6d02c61888a92f07ef304f5d87b60aeb52" }, "humans": [ "Mike Davies", "Narayan Srinivasa", "Tsung-Han Lin", "Gautham Chinya", "Yongqiang Cao", "Sri Harsha Choday", "Georgios Dimou", "Prasad Joshi", "Nabil Imam", "Shweta Jain", "Yuyun Liao", "Chit-Kwan Lin", "Andrew Lines", "Ruokun Liu", "Deepak Mathaikutty", "Steve McCoy", "Arnab Paul", "Jonathan Tse", "Guruguhanathan Venkataramanan", "Yi-Hsin Weng", "Andreas Wild", "Yoonseok Yang", "Hong Wang", "Garrick Orchard", "E. Paxon Frady", "Daniel Ben Dayan Rubin", "Sophia Sanborn", "Sumit Bam Shrestha", "Friedrich T. Sommer" ], "authors_complete": true, "human_role_note": "Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.", "agents": [], "related": [], "subresults": [], "scientific_assessment": { "source_review": "SOURCE_CURATED", "scientific_review": "NOT_REVIEWED_BY_WRS", "formal_replay": "NOT_RUN", "provider_attestation": "NONE" }, "sources": [ { "id": "cur20261015-loihi-2018-micro", "title": "Loihi: A Neuromorphic Manycore Processor with On-Chip Learning", "url": "https://redwood.berkeley.edu/wp-content/uploads/2021/08/Davies2018.pdf" }, { "id": "cur20261015-arxiv-2111-03746v1", "title": "Efficient Neuromorphic Signal Processing with Loihi 2", "url": "https://arxiv.org/abs/2111.03746v1" } ], "points": "150000", "published_grade": { "id": "davies-orchard-et-al-loihi-2018", "entry_id": "davies-orchard-et-al-loihi-2018", "band": "A", "modifier": null, "target": { "record_id": "urn:uuid:eb82eb49-9073-4e8a-a8e5-9acc25001abe", "version": 1, "content_hash": "sha256:b3b9287a51ad6f6e5a4a80ccef1b9f6d02c61888a92f07ef304f5d87b60aeb52" }, "what_changed": "Combined asynchronous spike routing, local synaptic state and programmable learning engines; the Loihi2 extension added microcoded state dynamics, graded spikes and richer connectivity for streaming computation.", "scope": "Combined asynchronous spike routing, local synaptic state and programmable learning engines; the Loihi2 extension added microcoded state dynamics, graded spikes and richer connectivity for streaming computation. 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detailed role assignment remains source-bound", "roles": [ "discoverer" ], "source": { "citation": "Loihi: A Neuromorphic Manycore Processor with On-Chip Learning", "url": "https://redwood.berkeley.edu/wp-content/uploads/2021/08/Davies2018.pdf" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Narayan Srinivasa", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "discoverer" ], "source": { "citation": "Loihi: A Neuromorphic Manycore Processor with On-Chip Learning", "url": "https://redwood.berkeley.edu/wp-content/uploads/2021/08/Davies2018.pdf" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Tsung-Han Lin", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "discoverer" ], "source": { "citation": "Loihi: A Neuromorphic Manycore Processor with On-Chip Learning", "url": "https://redwood.berkeley.edu/wp-content/uploads/2021/08/Davies2018.pdf" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Gautham Chinya", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "discoverer" ], "source": { "citation": "Loihi: A Neuromorphic Manycore Processor with On-Chip Learning", "url": "https://redwood.berkeley.edu/wp-content/uploads/2021/08/Davies2018.pdf" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Yongqiang Cao", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "discoverer" ], "source": { "citation": "Loihi: A Neuromorphic Manycore Processor with On-Chip Learning", "url": "https://redwood.berkeley.edu/wp-content/uploads/2021/08/Davies2018.pdf" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Sri Harsha Choday", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "discoverer" ], "source": { "citation": "Loihi: A Neuromorphic Manycore Processor with On-Chip Learning", "url": "https://redwood.berkeley.edu/wp-content/uploads/2021/08/Davies2018.pdf" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Georgios Dimou", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "discoverer" ], "source": { "citation": "Loihi: A Neuromorphic Manycore Processor with On-Chip Learning", "url": "https://redwood.berkeley.edu/wp-content/uploads/2021/08/Davies2018.pdf" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Prasad Joshi", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "discoverer" ], "source": { "citation": "Loihi: A Neuromorphic Manycore Processor with On-Chip Learning", "url": "https://redwood.berkeley.edu/wp-content/uploads/2021/08/Davies2018.pdf" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Nabil Imam", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "discoverer" ], "source": { "citation": "Loihi: A Neuromorphic Manycore Processor with On-Chip Learning", "url": "https://redwood.berkeley.edu/wp-content/uploads/2021/08/Davies2018.pdf" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Shweta Jain", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "discoverer" ], "source": { "citation": "Loihi: A Neuromorphic Manycore Processor with On-Chip Learning", "url": "https://redwood.berkeley.edu/wp-content/uploads/2021/08/Davies2018.pdf" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Yuyun Liao", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "discoverer" ], "source": { "citation": "Loihi: A Neuromorphic Manycore Processor with On-Chip Learning", "url": "https://redwood.berkeley.edu/wp-content/uploads/2021/08/Davies2018.pdf" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Chit-Kwan Lin", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "discoverer" ], "source": { "citation": "Loihi: A Neuromorphic Manycore Processor with On-Chip Learning", "url": "https://redwood.berkeley.edu/wp-content/uploads/2021/08/Davies2018.pdf" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Andrew Lines", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "discoverer" ], "source": { "citation": "Loihi: A Neuromorphic Manycore Processor with On-Chip Learning", "url": "https://redwood.berkeley.edu/wp-content/uploads/2021/08/Davies2018.pdf" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Ruokun Liu", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "discoverer" ], "source": { "citation": "Loihi: A Neuromorphic Manycore Processor with On-Chip Learning", "url": "https://redwood.berkeley.edu/wp-content/uploads/2021/08/Davies2018.pdf" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Deepak Mathaikutty", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "discoverer" ], "source": { "citation": "Loihi: A Neuromorphic Manycore Processor with On-Chip Learning", "url": "https://redwood.berkeley.edu/wp-content/uploads/2021/08/Davies2018.pdf" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Steve McCoy", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "discoverer" ], "source": { "citation": "Loihi: A Neuromorphic Manycore Processor with On-Chip Learning", "url": "https://redwood.berkeley.edu/wp-content/uploads/2021/08/Davies2018.pdf" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Arnab Paul", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "discoverer" ], "source": { "citation": "Loihi: A Neuromorphic Manycore Processor with On-Chip Learning", "url": "https://redwood.berkeley.edu/wp-content/uploads/2021/08/Davies2018.pdf" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Jonathan Tse", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "discoverer" ], "source": { "citation": "Loihi: A Neuromorphic Manycore Processor with On-Chip Learning", "url": "https://redwood.berkeley.edu/wp-content/uploads/2021/08/Davies2018.pdf" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Guruguhanathan Venkataramanan", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "discoverer" ], "source": { "citation": "Loihi: A Neuromorphic Manycore Processor with On-Chip Learning", "url": "https://redwood.berkeley.edu/wp-content/uploads/2021/08/Davies2018.pdf" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Yi-Hsin Weng", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "discoverer" ], "source": { "citation": "Loihi: A Neuromorphic Manycore Processor with On-Chip Learning", "url": "https://redwood.berkeley.edu/wp-content/uploads/2021/08/Davies2018.pdf" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Andreas Wild", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "discoverer" ], "source": { "citation": "Loihi: A Neuromorphic Manycore Processor with On-Chip Learning", "url": "https://redwood.berkeley.edu/wp-content/uploads/2021/08/Davies2018.pdf" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Yoonseok Yang", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "discoverer" ], "source": { "citation": "Loihi: A Neuromorphic Manycore Processor with On-Chip Learning", "url": "https://redwood.berkeley.edu/wp-content/uploads/2021/08/Davies2018.pdf" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Hong Wang", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "discoverer" ], "source": { "citation": "Loihi: A Neuromorphic Manycore Processor with On-Chip Learning", "url": "https://redwood.berkeley.edu/wp-content/uploads/2021/08/Davies2018.pdf" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Garrick Orchard", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "discoverer" ], "source": { "citation": "Efficient Neuromorphic Signal Processing with Loihi 2", "url": "https://arxiv.org/abs/2111.03746v1" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "E. Paxon Frady", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "discoverer" ], "source": { "citation": "Efficient Neuromorphic Signal Processing with Loihi 2", "url": "https://arxiv.org/abs/2111.03746v1" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Daniel Ben Dayan Rubin", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "discoverer" ], "source": { "citation": "Efficient Neuromorphic Signal Processing with Loihi 2", "url": "https://arxiv.org/abs/2111.03746v1" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Sophia Sanborn", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "discoverer" ], "source": { "citation": "Efficient Neuromorphic Signal Processing with Loihi 2", "url": "https://arxiv.org/abs/2111.03746v1" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Sumit Bam Shrestha", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "discoverer" ], "source": { "citation": "Efficient Neuromorphic Signal Processing with Loihi 2", "url": "https://arxiv.org/abs/2111.03746v1" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Friedrich T. Sommer", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "discoverer" ], "source": { "citation": "Efficient Neuromorphic Signal Processing with Loihi 2", "url": "https://arxiv.org/abs/2111.03746v1" } } ], "evidence": [ { "description": "Bibliographic/stated-result source; not a WRS proof verification", "id": "source-0", "kind": "source_reference", "source": { "citation": "Loihi: A Neuromorphic Manycore Processor with On-Chip Learning", "url": "https://redwood.berkeley.edu/wp-content/uploads/2021/08/Davies2018.pdf" } }, { "description": "Bibliographic/stated-result source; not a WRS proof verification", "id": "source-1", "kind": "source_reference", "source": { "citation": "Efficient Neuromorphic Signal Processing with Loihi 2", "url": "https://arxiv.org/abs/2111.03746v1" } } ], "origin": "HUMAN_LEGACY", "record_profile": "wrs-local-research-notes-0.1", "record_type": "research_note", "rrp_version": "0.1", "scope": { "description": "One architecture family with separate2018/2021 bylines. Core memory, fan-in/fan-out and mapping limits apply; deadlock-freedom requires management activity restricted to the specified synchronization phase. Loihi2 examples in the2021 paper are hardware-constrained simulations, not measured silicon speed/energy. No biological modelling or medical outcome is catalogued; approximate sparse-coding gains do not imply superiority at arbitrary numerical tolerance.", "domain": "Programmable AI accelerators" }, "sources": [ { "citation": "Loihi: A Neuromorphic Manycore Processor with On-Chip Learning", "url": "https://redwood.berkeley.edu/wp-content/uploads/2021/08/Davies2018.pdf" }, { "citation": "Efficient Neuromorphic Signal Processing with Loihi 2", "url": "https://arxiv.org/abs/2111.03746v1" } ], "statement": "# Intel Loihi: programmable event-driven spiking compute and learning\n\nCombined asynchronous spike routing, local synaptic state and programmable learning engines; the Loihi2 extension added microcoded state dynamics, graded spikes and richer connectivity for streaming computation.\n\n## Scientific scope\n\nOne architecture family with separate2018/2021 bylines. Core memory, fan-in/fan-out and mapping limits apply; deadlock-freedom requires management activity restricted to the specified synchronization phase. Loihi2 examples in the2021 paper are hardware-constrained simulations, not measured silicon speed/energy. No biological modelling or medical outcome is catalogued; approximate sparse-coding gains do not imply superiority at arbitrary numerical tolerance.\n\n## Reading status\n\nThis is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.\n\n## People and systems\n\nMike Davies; Narayan Srinivasa; Tsung-Han Lin; Gautham Chinya; Yongqiang Cao; Sri Harsha Choday; Georgios Dimou; Prasad Joshi; Nabil Imam; Shweta Jain; Yuyun Liao; Chit-Kwan Lin; Andrew Lines; Ruokun Liu; Deepak Mathaikutty; Steve McCoy; Arnab Paul; Jonathan Tse; Guruguhanathan Venkataramanan; Yi-Hsin Weng; Andreas Wild; Yoonseok Yang; Hong Wang; Garrick Orchard; E. Paxon Frady; Daniel Ben Dayan Rubin; Sophia Sanborn; Sumit Bam Shrestha; Friedrich T. Sommer\n\nSource-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.\n\n\n\n## Original sources\n\n- [Loihi: A Neuromorphic Manycore Processor with On-Chip Learning](https://redwood.berkeley.edu/wp-content/uploads/2021/08/Davies2018.pdf)\n- [Efficient Neuromorphic Signal Processing with Loihi 2](https://arxiv.org/abs/2111.03746v1)\n", "summary": "Combined asynchronous spike routing, local synaptic state and programmable learning engines; the Loihi2 extension added microcoded state dynamics, graded spikes and richer connectivity for streaming computation.", "title": "Intel Loihi: programmable event-driven spiking compute and learning" }, "record_id": "urn:uuid:eb82eb49-9073-4e8a-a8e5-9acc25001abe", "version": 1, "source_ref": { "record_id": "urn:uuid:eb82eb49-9073-4e8a-a8e5-9acc25001abe", "version": 1, "content_hash": "sha256:b3b9287a51ad6f6e5a4a80ccef1b9f6d02c61888a92f07ef304f5d87b60aeb52" }, "export_view": "wrs-public-editorial-view-1", "public_view_hash": "sha256:12eb7c1fa0e3df09776eadf8b8237881349542a7e0902e7d4750553559824dda" }, "target": { "record_id": "urn:uuid:eb82eb49-9073-4e8a-a8e5-9acc25001abe", "version": 1, "content_hash": "sha256:b3b9287a51ad6f6e5a4a80ccef1b9f6d02c61888a92f07ef304f5d87b60aeb52" }, "published_grade": { "profile": "wrs-published-grade-1", "edition": "2026-10-28.1", "id": "davies-orchard-et-al-loihi-2018", "entry_id": "davies-orchard-et-al-loihi-2018", "revision": 1, "title": "Intel Loihi: programmable event-driven spiking compute and learning", "context": "Programmable AI accelerators", "track": "Human-designed research method or resource", "band": "A", "modifier": null, "status": "PROVISIONAL_EDITORIAL", "assessed_on": "2026-10-16", "evidence_cutoff": "2026-10-16", "achievement_state": "SUPPORTED_SCOPED_RESULT", "what_changed": "Combined asynchronous spike routing, local synaptic state and programmable learning engines; the Loihi2 extension added microcoded state dynamics, graded spikes and richer connectivity for streaming computation.", "scope": "Combined asynchronous spike routing, local synaptic state and programmable learning engines; the Loihi2 extension added microcoded state dynamics, graded spikes and richer connectivity for streaming computation. One architecture family with separate2018/2021 bylines. Core memory, fan-in/fan-out and mapping limits apply; deadlock-freedom requires management activity restricted to the specified synchronization phase. Loihi2 examples in the2021 paper are hardware-constrained simulations, not measured silicon speed/energy. No biological modelling or medical outcome is catalogued; approximate sparse-coding gains do not imply superiority at arbitrary numerical tolerance.", "evidence_summary": "The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. One architecture family with separate2018/2021 bylines. Core memory, fan-in/fan-out and mapping limits apply; deadlock-freedom requires management activity restricted to the specified synchronization phase. Loihi2 examples in the2021 paper are hardware-constrained simulations, not measured silicon speed/energy. No biological modelling or medical outcome is catalogued; approximate sparse-coding gains do not imply superiority at arbitrary numerical tolerance.", "references": [ { "title": "Loihi: A Neuromorphic Manycore Processor with On-Chip Learning", "url": "https://redwood.berkeley.edu/wp-content/uploads/2021/08/Davies2018.pdf", "locator": "Original contribution and stated assumptions, evaluation scope and limitations; source-linked assessment, not independent execution or proof certification." }, { "title": "Efficient Neuromorphic Signal Processing with Loihi 2", "url": "https://arxiv.org/abs/2111.03746v1", "locator": "Original contribution and stated assumptions, evaluation scope and limitations; source-linked assessment, not independent execution or proof certification." } ], "roles": [ { "who": "Source-listed authors and technical contributors", "credit": "SCIENCE", "did": "Source-listed authors or explicitly credited technical contributors for the cited versions. 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