# Mycelium GPU for Developers

*The Energy Behind Intelligence*

## Overview

Mycelium GPU provides unified access to distributed GPU acceleration across the ThreeFold Grid. It transforms fragmented GPU resources into a single sovereign fabric for running AI, ML, and rendering workloads.

## Core Concept

Mycelium GPU unifies distributed acceleration into a single sovereign fabric — turning fragmented hardware into one adaptive intelligence layer. Run AI, ML, and rendering workloads anywhere, from edge to core, with deterministic performance and transparent cost.

### Key Principles
- **No Silos**: All GPU resources accessible through single interface
- **No Intermediaries**: Direct access to GPU resources
- **Raw, Verifiable Power**: Every GPU cycle cryptographically verified
- **Orchestrated Through Code**: GPU resources managed through APIs and smart contracts

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## Use Cases

### AI/ML Training
Run GPU-accelerated workloads for deep learning and data science on demand.

**Features:**
- **GPU Acceleration**: High-performance computing for machine learning
- **Scalable Compute**: Scale training across multiple GPU resources
- **Cost Optimization**: Pay only for actual GPU usage

### Rendering & Visualization
Run high-performance graphics processing workloads.

**Applications:**
- **3D Rendering**: Distributed rendering for film, games, and architecture
- **Scientific Visualization**: Complex data visualization and analysis
- **Virtual Reality**: Real-time VR/AR processing
- **Digital Twins**: Real-time simulation and modeling

### General GPU Computing
High-performance computing for various computational workloads.

**Applications:**
- **Scientific Simulations**: Physics, chemistry, climate modeling
- **Financial Modeling**: Risk analysis and algorithmic trading
- **Cryptocurrency**: Mining and blockchain processing
- **Protein Folding**: Drug discovery and molecular modeling

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## Integration with Mycelium Cloud

Mycelium GPU works seamlessly with Mycelium Cloud infrastructure:

- **Unified Networking**: GPU nodes accessible via Mycelium network
- **Shared Security**: Zero-trust security model applies to GPU operations
- **Storage Integration**: Access quantum-safe storage from GPU workloads
- **Kubernetes Support**: GPU workloads can be deployed as Kubernetes resources

### Deployment Example
```yaml
# GPU workload specification for Kubernetes
apiVersion: apps/v1
kind: Deployment
metadata:
  name: gpu-workload
spec:
  replicas: 1
  selector:
    matchLabels:
      app: gpu-compute
  template:
    metadata:
      labels:
        app: gpu-compute
    spec:
      containers:
      - name: gpu-compute
        image: tensorflow/tensorflow:latest-gpu
        resources:
          limits:
            nvidia.com/gpu: 1
        env:
        - name: MYCELIUM_GPU_REGION
          value: "auto"
```

---

## Getting Started

### Access GPU Resources
1. **Account Setup**: Create Mycelium account with GPU access
2. **Resource Request**: Use Mycelium GPU APIs to request GPU resources
3. **Workload Deployment**: Deploy your AI/ML or compute workload
4. **Monitor Usage**: Track GPU utilization and costs through dashboard

### Basic Workflow
```
Application → Mycelium GPU API → GPU Resource Allocation → Workload Execution
```

### Key Benefits
- **Deterministic Performance**: Predictable GPU allocation and performance
- **Global Distribution**: Access GPU resources worldwide
- **Transparent Costs**: Clear pricing without hidden fees
- **Sovereign Control**: Full control over GPU workloads and data

---

## Technical Architecture

### Distributed GPU Mesh
Mycelium GPU creates a peer-to-peer network of GPU resources accessible through the Mycelium Network.

**Components:**
- **GPU Nodes**: Physical GPU hardware distributed globally
- **Mycelium Network**: Encrypted peer-to-peer communication layer
- **Orchestration Layer**: API and smart contract-based resource management
- **Monitoring**: Real-time GPU utilization and health monitoring

### Performance Characteristics
- **Edge-to-Core Deployment**: Run workloads from edge devices to data centers
- **Adaptive Intelligence Layer**: Optimizes GPU resource allocation
- **Deterministic Performance**: Guaranteed resource availability and performance
- **Transparent Cost**: All GPU usage tracked and billed transparently

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## Key Differentiators

### Unified Fabric
Transforms fragmented GPU resources into a single, unified acceleration fabric accessible through standard APIs.

### Sovereign Control
Complete control over GPU workloads with no vendor lock-in or geographical restrictions.

### Code-Driven Orchestration
GPU resources managed through APIs and smart contracts, enabling automated and verifiable resource allocation.

### Deterministic Performance
Guaranteed GPU allocation with consistent performance characteristics across all workloads.

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## Cost Efficiency

Mycelium GPU provides cost-effective access to GPU resources through:

- **Transparent Pricing**: No hidden fees or surprise charges
- **Pay-per-Usage**: Pay only for actual GPU consumption
- **Global Optimization**: Access GPUs where they're most cost-effective
- **No Vendor Lock-in**: Avoid premium pricing from single providers

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*Mycelium GPU - Unifying distributed acceleration into a sovereign fabric.*