AI GPU Infrastructure Reference Architecture (10 MW Pod)

This repository contains a physics-first, vendor-agnostic reference architecture for GPU-accelerated AI infrastructure.

It defines infrastructure as an engineering contract derived from workload physics:

Workload → Power → Heat → Fluid → Rejection → Operations

The architecture is expressed through:

• Engineering Basis of Design (BoD) — requirements and envelopes
• Appendices — derivations and commissioning evidence
• Reference Architecture — topology instantiation
• Witness closure — alignment with a representative AI workload

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Key Technical Sections

• Workload → Infrastructure projection
  appendices/20_Appendix_A_Workload_to_Boundary.md

• Thermal closure and digital twin basis
  appendices/21_Appendix_B_Thermal_and_Twin.md

• Commissioning and FMEA mapping
  appendices/24_Appendix_E_FMEA_and_Commissioning.md

• Witness workload closure (CausalCompute)
  appendices/25_Appendix_F_CausalCompute_Alignment.md

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Start Here

• Engineering Basis of Design
  → 10_BOD_Engineering_Basis_of_Design.md

• Reference Architecture
  → 30_Reference_Architecture_10MW_Pod.md

• Appendices
  → appendices/

• Full document (PDF)
  → AI_Native_Pod_Reference_Architecture_PoC.pdf

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Scope

This document defines:

• Power envelopes and transient limits
• Thermal closure and flow requirements
• Hydraulic sizing and fault domains
• Sustainability and KPI measurement boundaries
• Commissioning and verification methodology

This document does not define vendor selection or construction drawings.

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Purpose

This work demonstrates how GPU infrastructure can be derived from workload physics rather than vendor templates, enabling predictable scaling and operational safety.

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Author

Antreas Christofi
HPC Infrastructure Engineer
antreas@christofi.me