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

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
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preprint

VES Memory, VES GPU, and VES Processor

Mikheil Rusishvili
Zenodo (CERN European Organization for Nuclear Research)
Neural Networks and Reservoir Computing
preprint

VES Memory, VES GPU, and VES Processor

Mikheil Rusishvili
preprint en

Abstract

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.

Zenodo (CERN European Organization for Nuclear Research)
Sustainable cities and communities
Neural Networks and Reservoir Computing
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