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detailed role assignment remains source-bound", "roles": [ "discoverer" ], "source": { "citation": "Think Fast: A Tensor Streaming Processor (TSP) for Accelerating Deep Learning Workloads", "url": "https://www.researchgate.net/publication/342914141_Think_Fast_A_Tensor_Streaming_Processor_TSP_for_Accelerating_Deep_Learning_Workloads" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Jim Sproch", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "discoverer" ], "source": { "citation": "Think Fast: A Tensor Streaming Processor (TSP) for Accelerating Deep Learning Workloads", "url": "https://www.researchgate.net/publication/342914141_Think_Fast_A_Tensor_Streaming_Processor_TSP_for_Accelerating_Deep_Learning_Workloads" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Adrian Macias", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "discoverer" ], "source": { "citation": "Think Fast: A Tensor Streaming Processor (TSP) for Accelerating Deep Learning Workloads", "url": "https://www.researchgate.net/publication/342914141_Think_Fast_A_Tensor_Streaming_Processor_TSP_for_Accelerating_Deep_Learning_Workloads" } }, { "attribution_basis": "SOURCE_CITED", "credit": "historical_scientific", "entity_kind": "historical_person", "name": "Brian Kurtz", "note": "Archive attribution; detailed role assignment remains source-bound", "roles": [ "discoverer" ], "source": { "citation": "Think Fast: A Tensor Streaming Processor (TSP) for Accelerating Deep Learning Workloads", "url": "https://www.researchgate.net/publication/342914141_Think_Fast_A_Tensor_Streaming_Processor_TSP_for_Accelerating_Deep_Learning_Workloads" } } ], "evidence": [ { "description": "Bibliographic/stated-result source; not a WRS proof verification", "id": "source-0", "kind": "source_reference", "source": { "citation": "Think Fast: A Tensor Streaming Processor (TSP) for Accelerating Deep Learning Workloads", "url": "https://www.researchgate.net/publication/342914141_Think_Fast_A_Tensor_Streaming_Processor_TSP_for_Accelerating_Deep_Learning_Workloads" } } ], "origin": "HUMAN_LEGACY", "record_profile": "wrs-local-research-notes-0.1", "record_type": "research_note", "rrp_version": "0.1", "scope": { "description": "Static scheduling/dataflow and tensor acceleration have predecessors. Determinism pertains to the compiled model, instruction/data schedule and stated hardware conditions, not arbitrary external services or all workloads. Original2020 ISCA implementation only; inaccessible2022 scale-out extension is not silently included. Source is an author-uploaded reproduction, not a new2022 publication or independently reproduced benchmark.", "domain": "Deterministically scheduled AI accelerators" }, "sources": [ { "citation": "Think Fast: A Tensor Streaming Processor (TSP) for Accelerating Deep Learning Workloads", "url": "https://www.researchgate.net/publication/342914141_Think_Fast_A_Tensor_Streaming_Processor_TSP_for_Accelerating_Deep_Learning_Workloads" } ], "statement": "# Groq TSP: compile-time scheduled tensor-streaming architecture\n\nBuilt a tensor-streaming processor around functional slices, producer-consumer streams and compiler-controlled cycle-level scheduling, explicitly managing computation and SRAM data movement.\n\n## Scientific scope\n\nStatic scheduling/dataflow and tensor acceleration have predecessors. Determinism pertains to the compiled model, instruction/data schedule and stated hardware conditions, not arbitrary external services or all workloads. Original2020 ISCA implementation only; inaccessible2022 scale-out extension is not silently included. Source is an author-uploaded reproduction, not a new2022 publication or independently reproduced benchmark.\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\nDennis Abts; Jonathan Ross; Jonathan Sparling; Mark Wong-VanHaren; Max Baker; Tom Hawkins; Andrew Bell; John Thompson; Temesghen Kahsai; Garrin Kimmell; Jennifer Hwang; Rebekah Leslie-Hurd; Michael Bye; E. R. Creswick; Matthew Boyd; Mahitha Venigalla; Evan Laforge; Jon Purdy; Purushotham Kamath; Dinesh Maheshwari; Michael Beidler; Geert Rosseel; Omar Ahmad; Gleb Gagarin; Richard Czekalski; Ashay Rane; Sahil Parmar; Jeff Werner; Jim Sproch; Adrian Macias; Brian Kurtz\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- [Think Fast: A Tensor Streaming Processor (TSP) for Accelerating Deep Learning Workloads](https://www.researchgate.net/publication/342914141_Think_Fast_A_Tensor_Streaming_Processor_TSP_for_Accelerating_Deep_Learning_Workloads)\n", "summary": "Built a tensor-streaming processor around functional slices, producer-consumer streams and compiler-controlled cycle-level scheduling, explicitly managing computation and SRAM data movement.", "title": "Groq TSP: compile-time scheduled tensor-streaming architecture" }, "record_id": "urn:uuid:b2dff19f-3c10-441b-a942-692a2c7bd2a0", "version": 1, "source_ref": { "record_id": "urn:uuid:b2dff19f-3c10-441b-a942-692a2c7bd2a0", "version": 1, "content_hash": "sha256:9bee5827293b04142de549d1041036a3b05624869e103009eb2b14bf608eb421" }, "export_view": "wrs-public-editorial-view-1", "public_view_hash": "sha256:c04659f3394490a6e073a6d98f426dd0f1ad7bda55502d868e7f02d80bd9d229" }, "target": { "record_id": "urn:uuid:b2dff19f-3c10-441b-a942-692a2c7bd2a0", "version": 1, "content_hash": "sha256:9bee5827293b04142de549d1041036a3b05624869e103009eb2b14bf608eb421" }, "published_grade": { "profile": "wrs-published-grade-1", "edition": "2026-10-28.1", "id": "abts-et-al-groq-tsp-2020", "entry_id": "abts-et-al-groq-tsp-2020", "revision": 1, "title": "Groq TSP: compile-time scheduled tensor-streaming architecture", "context": "Deterministically scheduled 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": "Built a tensor-streaming processor around functional slices, producer-consumer streams and compiler-controlled cycle-level scheduling, explicitly managing computation and SRAM data movement.", "scope": "Built a tensor-streaming processor around functional slices, producer-consumer streams and compiler-controlled cycle-level scheduling, explicitly managing computation and SRAM data movement. Static scheduling/dataflow and tensor acceleration have predecessors. Determinism pertains to the compiled model, instruction/data schedule and stated hardware conditions, not arbitrary external services or all workloads. Original2020 ISCA implementation only; inaccessible2022 scale-out extension is not silently included. Source is an author-uploaded reproduction, not a new2022 publication or independently reproduced benchmark.", "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. Static scheduling/dataflow and tensor acceleration have predecessors. Determinism pertains to the compiled model, instruction/data schedule and stated hardware conditions, not arbitrary external services or all workloads. Original2020 ISCA implementation only; inaccessible2022 scale-out extension is not silently included. Source is an author-uploaded reproduction, not a new2022 publication or independently reproduced benchmark.", "references": [ { "title": "Think Fast: A Tensor Streaming Processor (TSP) for Accelerating Deep Learning Workloads", "url": "https://www.researchgate.net/publication/342914141_Think_Fast_A_Tensor_Streaming_Processor_TSP_for_Accelerating_Deep_Learning_Workloads", "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. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. 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