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18 changes: 14 additions & 4 deletions README.md
Original file line number Diff line number Diff line change
Expand Up @@ -15,27 +15,37 @@ Dual natureβ€”combining bare-metal virtualized hardware management (aSHARD VRAM
## πŸ—οΈ Architecture

```mermaid
---
title: Arbiter System Architecture
---
graph TD
subgraph CloudNative [Cloud Native Layer]
K8s[Kubernetes Cluster]
Workloads([AI Workloads])
K8s([Kubernetes Cluster])
end

subgraph Orchestration [Orchestration Layer]
Arbiter((Arbiter Core))
QS[Quantum Scheduler]
QS{{Quantum Scheduler}}
end

subgraph Infrastructure [Infrastructure Layer]
aSHARD{{aSHARD VRAM Pinning}}
BM[Bare Metal Hardware]
GPU[GPU Resources]
end

Workloads --> K8s
K8s <--> Arbiter
Arbiter <--> QS
Arbiter <--> BM
Arbiter <--> aSHARD
aSHARD <--> BM
BM --- GPU
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medium

Since aSHARD is specifically responsible for VRAM pinning, it should have a direct relationship/connection to the GPU (GPU Resources) node in the architecture diagram, rather than only connecting to BM (Bare Metal Hardware). This makes the diagram more semantically accurate regarding how VRAM pinning interacts with GPU resources.

Suggested change
Arbiter <--> aSHARD
aSHARD <--> BM
BM --- GPU
Arbiter <--> aSHARD
aSHARD <--> BM
aSHARD <--> GPU
BM --- GPU


style Arbiter fill:#f96,stroke-width:4px
style CloudNative stroke-dasharray: 5 5
style Orchestration stroke-dasharray: 5 5
style Infrastructure stroke-dasharray: 5 5
```

## πŸš€ Key Features
Expand All @@ -47,7 +57,7 @@ graph TD

## πŸ§ͺ Context

`arbiter` was created by **Igor Holt** (AI Architect) as part of the **Genesis Conductor Engine**. It serves as the resource orchestration layer for AI workloads, bridging low-level hardware management with cloud-native scheduling to ensure optimal utilization of specialized compute resources.
`arbiter` was created by **Igor Holt** (AI Architect) as part of the [**Genesis Conductor Engine**](https://genesisconductor.io "Genesis Conductor Engine - Official Website"). It serves as the resource orchestration layer for AI workloads, bridging low-level hardware management with cloud-native scheduling to ensure optimal utilization of specialized compute resources.

## βš–οΈ License

Expand Down