Declaration of Invention: Reactive Cascade Accelerator (RCA) Vertical Architecture for Datacenter-Scale Artificial Intelligence Computation
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Zenodo
2026
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| _version_ | 1866901824516128768 |
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| author | Scurin, Pavel |
| author_facet | Scurin, Pavel |
| contents | <p>This declaration describes the Reactive Cascade Accelerator (RCA), a vertical compute architecture for datacenter-scale artificial intelligence systems. Unlike conventional flat GPU clusters that process raw prompts end-to-end on large models, RCA organizes computation as a cascade of progressively narrower levels from user edge to datacenter apex. Each level either resolves the request locally or transforms it into more compact, structured state before passing it upward. The governing principle is monotonic stream densification: broad token flows at lower stages are progressively condensed into narrow decision flows at higher stages. Resumable State (R-State) serves as the portable inter-cascade interface, enabling higher levels to resume from enriched state rather than reprocessing raw input. In datacenter-scale deployments, the architecture positions large language models as mid-tier reactors rather than terminal authorities, placing a specialized decision accelerator—potentially a quantum processing unit (QPU)—at the apex to handle maximally condensed streams. This defensive publication establishes prior art for the RCA architectural class to prevent monopolization of the disclosed concepts.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_20147443 |
| institution | Zenodo |
| language | |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Declaration of Invention: Reactive Cascade Accelerator (RCA) Vertical Architecture for Datacenter-Scale Artificial Intelligence Computation Scurin, Pavel Reactive Cascade Accelerator (RCA) vertical AI compute architecture datacenter-scale AI inference edge-to-cloud cascaded inference stream densification Resumable State (R-State) inter-cascade state transfer hierarchical AI accelerator architecture QPU as apex decision processor quantum processing unit for AI mid-tier LLM reactors heterogeneous inference pipeline vertical scaling versus horizontal scaling compressed computational state convergent inference streams defensive publication prior art <p>This declaration describes the Reactive Cascade Accelerator (RCA), a vertical compute architecture for datacenter-scale artificial intelligence systems. Unlike conventional flat GPU clusters that process raw prompts end-to-end on large models, RCA organizes computation as a cascade of progressively narrower levels from user edge to datacenter apex. Each level either resolves the request locally or transforms it into more compact, structured state before passing it upward. The governing principle is monotonic stream densification: broad token flows at lower stages are progressively condensed into narrow decision flows at higher stages. Resumable State (R-State) serves as the portable inter-cascade interface, enabling higher levels to resume from enriched state rather than reprocessing raw input. In datacenter-scale deployments, the architecture positions large language models as mid-tier reactors rather than terminal authorities, placing a specialized decision accelerator—potentially a quantum processing unit (QPU)—at the apex to handle maximally condensed streams. This defensive publication establishes prior art for the RCA architectural class to prevent monopolization of the disclosed concepts.</p> |
| title | Declaration of Invention: Reactive Cascade Accelerator (RCA) Vertical Architecture for Datacenter-Scale Artificial Intelligence Computation |
| topic | Reactive Cascade Accelerator (RCA) vertical AI compute architecture datacenter-scale AI inference edge-to-cloud cascaded inference stream densification Resumable State (R-State) inter-cascade state transfer hierarchical AI accelerator architecture QPU as apex decision processor quantum processing unit for AI mid-tier LLM reactors heterogeneous inference pipeline vertical scaling versus horizontal scaling compressed computational state convergent inference streams defensive publication prior art |
| url | https://doi.org/10.5281/zenodo.20147443 |