VES Memory, VES GPU, and VES Processor
This paper proposes a unified computing architecture inspired by the principles of Viscous Emergent Spacetime (VES). The architecture consists of three tightly coupled components: VES Memory, VES GPU, and VES Processor. Unlike conventional computing systems, which primarily optimize instruction throughput and floating-point performance, the proposed architecture treats computation as the controlled movement, transformation, preservation, and coarse-graining of useful information. In the VES framework, information, causality, and irreversible coarse-graining are treated as primary, while spacetime and macroscopic physical structure emerge as effective hydrodynamic descriptions of informational flow. Translating this principle into computer architecture leads to a system in which data density, data movement, memory locality, latency, thermal dissipation, and conversion overhead are treated as elements of a single information-flow optimization problem. The proposed VES computer is not a purely optical machine. Instead, it is a practical hybrid electronic-photonic architecture combining CMOS control logic, conventional GPU compatibility, photonic tensor acceleration, near-memory computation, adaptive precision, and an information-degradation-aware scheduler. Its goal is to reduce the dominant bottlenecks of modern processors: memory traffic, interconnect congestion, excessive data movement, synchronization overhead, and energy loss.
Authors
- Mikheil Rusishvili
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-05-19
- DOI
- https://doi.org/10.5281/zenodo.20277346
- Primary Topic
- Neural Networks and Reservoir Computing
- Type
- preprint