docs: add developer docs for gpu and cloud
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mik-tf
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docs/mycelium_gpu_for_devs.md
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docs/mycelium_gpu_for_devs.md
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# Mycelium GPU for Developers
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*The Energy Behind Intelligence*
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## Overview
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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.
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## Core Concept
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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.
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### Key Principles
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- **No Silos**: All GPU resources accessible through single interface
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- **No Intermediaries**: Direct access to GPU resources
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- **Raw, Verifiable Power**: Every GPU cycle cryptographically verified
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- **Orchestrated Through Code**: GPU resources managed through APIs and smart contracts
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---
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## Use Cases
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### AI/ML Training
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Run GPU-accelerated workloads for deep learning and data science on demand.
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**Features:**
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- **GPU Acceleration**: High-performance computing for machine learning
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- **Scalable Compute**: Scale training across multiple GPU resources
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- **Cost Optimization**: Pay only for actual GPU usage
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### Rendering & Visualization
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Run high-performance graphics processing workloads.
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**Applications:**
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- **3D Rendering**: Distributed rendering for film, games, and architecture
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- **Scientific Visualization**: Complex data visualization and analysis
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- **Virtual Reality**: Real-time VR/AR processing
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- **Digital Twins**: Real-time simulation and modeling
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### General GPU Computing
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High-performance computing for various computational workloads.
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**Applications:**
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- **Scientific Simulations**: Physics, chemistry, climate modeling
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- **Financial Modeling**: Risk analysis and algorithmic trading
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- **Cryptocurrency**: Mining and blockchain processing
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- **Protein Folding**: Drug discovery and molecular modeling
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---
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## Integration with Mycelium Cloud
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Mycelium GPU works seamlessly with Mycelium Cloud infrastructure:
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- **Unified Networking**: GPU nodes accessible via Mycelium network
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- **Shared Security**: Zero-trust security model applies to GPU operations
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- **Storage Integration**: Access quantum-safe storage from GPU workloads
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- **Kubernetes Support**: GPU workloads can be deployed as Kubernetes resources
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### Deployment Example
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```yaml
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# GPU workload specification for Kubernetes
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apiVersion: apps/v1
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kind: Deployment
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metadata:
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name: gpu-workload
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spec:
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replicas: 1
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selector:
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matchLabels:
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app: gpu-compute
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template:
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metadata:
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labels:
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app: gpu-compute
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spec:
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containers:
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- name: gpu-compute
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image: tensorflow/tensorflow:latest-gpu
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resources:
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limits:
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nvidia.com/gpu: 1
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env:
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- name: MYCELIUM_GPU_REGION
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value: "auto"
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```
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---
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## Getting Started
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### Access GPU Resources
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1. **Account Setup**: Create Mycelium account with GPU access
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2. **Resource Request**: Use Mycelium GPU APIs to request GPU resources
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3. **Workload Deployment**: Deploy your AI/ML or compute workload
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4. **Monitor Usage**: Track GPU utilization and costs through dashboard
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### Basic Workflow
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```
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Application → Mycelium GPU API → GPU Resource Allocation → Workload Execution
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```
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### Key Benefits
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- **Deterministic Performance**: Predictable GPU allocation and performance
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- **Global Distribution**: Access GPU resources worldwide
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- **Transparent Costs**: Clear pricing without hidden fees
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- **Sovereign Control**: Full control over GPU workloads and data
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---
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## Technical Architecture
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### Distributed GPU Mesh
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Mycelium GPU creates a peer-to-peer network of GPU resources accessible through the Mycelium Network.
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**Components:**
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- **GPU Nodes**: Physical GPU hardware distributed globally
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- **Mycelium Network**: Encrypted peer-to-peer communication layer
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- **Orchestration Layer**: API and smart contract-based resource management
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- **Monitoring**: Real-time GPU utilization and health monitoring
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### Performance Characteristics
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- **Edge-to-Core Deployment**: Run workloads from edge devices to data centers
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- **Adaptive Intelligence Layer**: Optimizes GPU resource allocation
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- **Deterministic Performance**: Guaranteed resource availability and performance
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- **Transparent Cost**: All GPU usage tracked and billed transparently
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---
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## Key Differentiators
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### Unified Fabric
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Transforms fragmented GPU resources into a single, unified acceleration fabric accessible through standard APIs.
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### Sovereign Control
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Complete control over GPU workloads with no vendor lock-in or geographical restrictions.
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### Code-Driven Orchestration
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GPU resources managed through APIs and smart contracts, enabling automated and verifiable resource allocation.
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### Deterministic Performance
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Guaranteed GPU allocation with consistent performance characteristics across all workloads.
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---
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## Cost Efficiency
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Mycelium GPU provides cost-effective access to GPU resources through:
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- **Transparent Pricing**: No hidden fees or surprise charges
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- **Pay-per-Usage**: Pay only for actual GPU consumption
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- **Global Optimization**: Access GPUs where they're most cost-effective
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- **No Vendor Lock-in**: Avoid premium pricing from single providers
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---
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*Mycelium GPU - Unifying distributed acceleration into a sovereign fabric.*
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