synor/docs/PLAN/PHASE11-Synor-Compute-L2.md

Phase 11: Synor Compute L2 - Full-Stack Compute Platform

Mission: Build a decentralized compute platform capable of AI/ML training, inference, OS hosting, and general-purpose high-performance computing.

---

Executive Summary

Synor Compute L2 extends beyond the current WASM-only Synor VM to provide:

• GPU Compute: AI/ML training and inference with CUDA/ROCm support
• Container Orchestration: Docker-compatible workloads with Kubernetes-style scheduling
• Persistent VMs: Long-running virtual machines for OS hosting
• Serverless Functions: Short-lived compute for API backends and event processing
• Edge Compute: Low-latency compute at network edge nodes

---

Architecture Overview

┌─────────────────────────────────────────────────────────────────────────────┐
│                         SYNOR COMPUTE L2                                     │
├─────────────────────────────────────────────────────────────────────────────┤
│                                                                              │
│  ┌─────────────────────────────────────────────────────────────────────────┐ │
│  │                      APPLICATION LAYER                                   │ │
│  ├──────────────┬──────────────┬──────────────┬──────────────┬────────────┤ │
│  │   AI/ML      │  Serverless  │  Containers  │  Persistent  │   Edge     │ │
│  │   Training   │  Functions   │  (Docker)    │  VMs (Linux) │  Compute   │ │
│  └──────────────┴──────────────┴──────────────┴──────────────┴────────────┘ │
│                                                                              │
│  ┌─────────────────────────────────────────────────────────────────────────┐ │
│  │                      ORCHESTRATION LAYER                                 │ │
│  ├──────────────┬──────────────┬──────────────┬──────────────┬────────────┤ │
│  │   Job        │  Resource    │  Network     │  Storage     │   Health   │ │
│  │   Scheduler  │  Manager     │  Fabric      │  Orchestrator│   Monitor  │ │
│  └──────────────┴──────────────┴──────────────┴──────────────┴────────────┘ │
│                                                                              │
│  ┌─────────────────────────────────────────────────────────────────────────┐ │
│  │                      COMPUTE RUNTIME LAYER                               │ │
│  ├──────────────┬──────────────┬──────────────┬──────────────┬────────────┤ │
│  │   GPU        │  Container   │  MicroVM     │  WASM        │   Native   │ │
│  │   Runtime    │  Runtime     │  Runtime     │  Runtime     │   Runtime  │ │
│  │   (CUDA/ROCm)│  (containerd)│  (Firecracker)│  (Wasmtime) │   (gVisor) │ │
│  └──────────────┴──────────────┴──────────────┴──────────────┴────────────┘ │
│                                                                              │
│  ┌─────────────────────────────────────────────────────────────────────────┐ │
│  │                      INFRASTRUCTURE LAYER                                │ │
│  ├──────────────┬──────────────┬──────────────┬──────────────┬────────────┤ │
│  │   Node       │  Network     │  Distributed │  Consensus   │   Billing  │ │
│  │   Registry   │  Overlay     │  Storage     │  (PoS+PoW)   │   Metering │ │
│  └──────────────┴──────────────┴──────────────┴──────────────┴────────────┘ │
│                                                                              │
│  ┌─────────────────────────────────────────────────────────────────────────┐ │
│  │              SYNOR L1 BLOCKCHAIN (GHOSTDAG + DAG-RIDER)                  │ │
│  └─────────────────────────────────────────────────────────────────────────┘ │
│                                                                              │
└─────────────────────────────────────────────────────────────────────────────┘

---

Milestone 1: GPU Compute Foundation (AI/ML Training & Inference)

1.1 GPU Node Registration

// synor-compute/src/gpu/node.rs

/// GPU node capabilities
pub struct GpuNode {
    /// Unique node ID
    pub node_id: NodeId,
    /// GPU specifications
    pub gpus: Vec<GpuSpec>,
    /// Total VRAM available (bytes)
    pub total_vram: u64,
    /// Available VRAM (bytes)
    pub available_vram: u64,
    /// CUDA compute capability (e.g., 8.6 for RTX 3090)
    pub cuda_capability: Option<(u8, u8)>,
    /// ROCm version (for AMD)
    pub rocm_version: Option<String>,
    /// Network bandwidth (Gbps)
    pub bandwidth_gbps: u32,
    /// Geographic region
    pub region: Region,
    /// Stake amount (for PoS validation)
    pub stake: u64,
}

pub struct GpuSpec {
    pub model: String,           // "NVIDIA RTX 4090"
    pub vram_gb: u32,            // 24
    pub tensor_cores: u32,       // 512
    pub cuda_cores: u32,         // 16384
    pub memory_bandwidth: u32,   // 1008 GB/s
    pub fp32_tflops: f32,        // 82.6
    pub fp16_tflops: f32,        // 165.2
    pub int8_tops: f32,          // 330.4
}

1.2 AI/ML Job Specification

// synor-compute/src/ai/job.rs

/// AI/ML training job specification
pub struct TrainingJob {
    /// Job ID
    pub job_id: JobId,
    /// Owner address
    pub owner: Address,
    /// Framework (PyTorch, TensorFlow, JAX)
    pub framework: MlFramework,
    /// Model specification
    pub model: ModelSpec,
    /// Dataset reference (Synor Storage CID)
    pub dataset_cid: Cid,
    /// Training configuration
    pub config: TrainingConfig,
    /// Resource requirements
    pub resources: GpuResources,
    /// Maximum budget (SYNOR tokens)
    pub max_budget: u64,
    /// Checkpoint interval (steps)
    pub checkpoint_interval: u64,
}

pub struct GpuResources {
    pub min_gpus: u32,
    pub max_gpus: u32,
    pub min_vram_per_gpu: u64,
    pub cuda_capability_min: Option<(u8, u8)>,
    pub distributed: bool,        // Multi-node training
    pub priority: JobPriority,
}

pub enum MlFramework {
    PyTorch { version: String },
    TensorFlow { version: String },
    JAX { version: String },
    ONNX,
    Custom { image: String },
}

pub struct TrainingConfig {
    pub epochs: u32,
    pub batch_size: u32,
    pub learning_rate: f32,
    pub optimizer: String,
    pub mixed_precision: bool,
    pub gradient_accumulation: u32,
    pub distributed_strategy: DistributedStrategy,
}

pub enum DistributedStrategy {
    DataParallel,
    ModelParallel,
    PipelineParallel,
    ZeRO { stage: u8 },  // DeepSpeed ZeRO stages 1-3
    FSDP,                // Fully Sharded Data Parallel
}

1.3 Inference Service

// synor-compute/src/ai/inference.rs

/// Inference endpoint specification
pub struct InferenceEndpoint {
    /// Endpoint ID
    pub endpoint_id: EndpointId,
    /// Model reference (Synor Storage CID)
    pub model_cid: Cid,
    /// Model format
    pub format: ModelFormat,
    /// Scaling configuration
    pub scaling: AutoscaleConfig,
    /// GPU requirements per replica
    pub gpu_per_replica: GpuResources,
    /// Request timeout
    pub timeout_ms: u32,
    /// Max batch size for batching inference
    pub max_batch_size: u32,
    /// Batching timeout
    pub batch_timeout_ms: u32,
}

pub enum ModelFormat {
    PyTorch,
    ONNX,
    TensorRT,
    Triton,
    vLLM,          // For LLM serving
    TGI,           // Text Generation Inference
    Custom,
}

pub struct AutoscaleConfig {
    pub min_replicas: u32,
    pub max_replicas: u32,
    pub target_gpu_utilization: f32,
    pub scale_up_threshold: f32,
    pub scale_down_threshold: f32,
    pub cooldown_seconds: u32,
}

1.4 Pricing Model for GPU Compute

Resource	Unit	Price (SYNOR/unit)
GPU (RTX 4090 equivalent)	hour	0.50
GPU (A100 80GB equivalent)	hour	2.00
GPU (H100 equivalent)	hour	4.00
VRAM	GB/hour	0.01
Network egress	GB	0.05
Storage (hot, NVMe)	GB/month	0.10
Inference requests	1M tokens	0.10

---

Milestone 2: Container Orchestration (Docker/Kubernetes-Compatible)

2.1 Container Runtime

// synor-compute/src/container/runtime.rs

/// Container specification (OCI-compatible)
pub struct ContainerSpec {
    /// Image reference
    pub image: ImageRef,
    /// Resource limits
    pub resources: ContainerResources,
    /// Environment variables
    pub env: HashMap<String, String>,
    /// Volume mounts
    pub volumes: Vec<VolumeMount>,
    /// Network configuration
    pub network: NetworkConfig,
    /// Security context
    pub security: SecurityContext,
    /// Health check
    pub health_check: Option<HealthCheck>,
}

pub struct ContainerResources {
    pub cpu_cores: f32,          // 0.5, 1.0, 2.0, etc.
    pub memory_mb: u64,
    pub gpu: Option<GpuAllocation>,
    pub ephemeral_storage_gb: u32,
    pub network_bandwidth_mbps: u32,
}

pub struct GpuAllocation {
    pub count: u32,
    pub vram_mb: u64,
    pub shared: bool,  // Allow GPU sharing via MPS/MIG
}

2.2 Service Mesh & Networking

// synor-compute/src/network/mesh.rs

/// Service definition for container orchestration
pub struct Service {
    pub service_id: ServiceId,
    pub name: String,
    pub containers: Vec<ContainerSpec>,
    pub replicas: ReplicaConfig,
    pub load_balancer: LoadBalancerConfig,
    pub service_mesh: ServiceMeshConfig,
}

pub struct ServiceMeshConfig {
    pub mtls_enabled: bool,
    pub traffic_policy: TrafficPolicy,
    pub circuit_breaker: CircuitBreakerConfig,
    pub retry_policy: RetryPolicy,
    pub rate_limit: Option<RateLimitConfig>,
}

pub struct LoadBalancerConfig {
    pub algorithm: LoadBalancerAlgorithm,
    pub health_check: HealthCheck,
    pub sticky_sessions: bool,
    pub ssl_termination: SslTermination,
}

pub enum LoadBalancerAlgorithm {
    RoundRobin,
    LeastConnections,
    WeightedRoundRobin { weights: Vec<u32> },
    IPHash,
    Random,
}

2.3 Container Pricing

Resource	Unit	Price (SYNOR/unit)
CPU	core/hour	0.02
Memory	GB/hour	0.005
Ephemeral storage	GB/hour	0.001
Network ingress	GB	FREE
Network egress	GB	0.05
Load balancer	hour	0.01
Static IP	month	2.00

---

Milestone 3: Persistent Virtual Machines (OS Hosting)

3.1 MicroVM Architecture (Firecracker-based)

// synor-compute/src/vm/microvm.rs

/// Virtual machine specification
pub struct VmSpec {
    /// VM ID
    pub vm_id: VmId,
    /// Owner address
    pub owner: Address,
    /// VM size
    pub size: VmSize,
    /// Boot image
    pub image: VmImage,
    /// Persistent volumes
    pub volumes: Vec<PersistentVolume>,
    /// Network configuration
    pub network: VmNetworkConfig,
    /// SSH keys for access
    pub ssh_keys: Vec<SshPublicKey>,
    /// Cloud-init user data
    pub user_data: Option<String>,
}

pub struct VmSize {
    pub vcpus: u32,
    pub memory_gb: u32,
    pub gpu: Option<GpuPassthrough>,
    pub network_bandwidth_gbps: u32,
}

pub struct GpuPassthrough {
    pub count: u32,
    pub model: GpuModel,
    pub vram_gb: u32,
}

pub enum VmImage {
    /// Pre-built images
    Marketplace { image_id: String, version: String },
    /// Custom image from Synor Storage
    Custom { cid: Cid, format: ImageFormat },
    /// Standard OS images
    Ubuntu { version: String },
    Debian { version: String },
    AlmaLinux { version: String },
    Windows { version: String, license: WindowsLicense },
}

pub struct PersistentVolume {
    pub volume_id: VolumeId,
    pub size_gb: u32,
    pub volume_type: VolumeType,
    pub mount_path: String,
    pub encrypted: bool,
}

pub enum VolumeType {
    /// High-performance NVMe SSD
    NvmeSsd { iops: u32, throughput_mbps: u32 },
    /// Standard SSD
    Ssd,
    /// HDD for archival
    Hdd,
    /// Distributed storage (Synor Storage L2)
    Distributed { replication: u8 },
}

3.2 VM Lifecycle Management

// synor-compute/src/vm/lifecycle.rs

pub enum VmState {
    Pending,
    Provisioning,
    Running,
    Stopping,
    Stopped,
    Hibernating,
    Hibernated,
    Migrating,
    Failed,
    Terminated,
}

pub struct VmManager {
    /// Active VMs
    vms: HashMap<VmId, VmInstance>,
    /// Node assignments
    node_assignments: HashMap<VmId, NodeId>,
    /// Live migration coordinator
    migration_coordinator: MigrationCoordinator,
}

impl VmManager {
    /// Start a new VM
    pub async fn create(&self, spec: VmSpec) -> Result<VmId, VmError>;

    /// Stop a VM (preserves state)
    pub async fn stop(&self, vm_id: &VmId) -> Result<(), VmError>;

    /// Start a stopped VM
    pub async fn start(&self, vm_id: &VmId) -> Result<(), VmError>;

    /// Hibernate VM to storage (saves memory state)
    pub async fn hibernate(&self, vm_id: &VmId) -> Result<(), VmError>;

    /// Live migrate VM to another node
    pub async fn migrate(&self, vm_id: &VmId, target_node: NodeId) -> Result<(), VmError>;

    /// Resize VM (requires restart)
    pub async fn resize(&self, vm_id: &VmId, new_size: VmSize) -> Result<(), VmError>;

    /// Snapshot VM state
    pub async fn snapshot(&self, vm_id: &VmId) -> Result<SnapshotId, VmError>;

    /// Terminate and delete VM
    pub async fn terminate(&self, vm_id: &VmId) -> Result<(), VmError>;
}

3.3 VM Pricing

VM Type	vCPUs	Memory	Storage	GPU	Price (SYNOR/month)
micro	1	1 GB	20 GB SSD	-	5
small	2	4 GB	50 GB SSD	-	15
medium	4	8 GB	100 GB SSD	-	30
large	8	32 GB	200 GB SSD	-	80
xlarge	16	64 GB	500 GB NVMe	-	200
gpu-small	8	32 GB	200 GB NVMe	1x RTX 4090	400
gpu-medium	16	64 GB	500 GB NVMe	2x RTX 4090	750
gpu-large	32	128 GB	1 TB NVMe	4x A100 80GB	2500
gpu-xlarge	64	256 GB	2 TB NVMe	8x H100	8000

---

Milestone 4: Serverless Functions (FaaS)

4.1 Function Specification

// synor-compute/src/serverless/function.rs

/// Serverless function definition
pub struct Function {
    pub function_id: FunctionId,
    pub owner: Address,
    pub name: String,
    pub runtime: FunctionRuntime,
    pub handler: String,
    pub code: FunctionCode,
    pub resources: FunctionResources,
    pub triggers: Vec<FunctionTrigger>,
    pub environment: HashMap<String, String>,
    pub timeout_ms: u32,
    pub concurrency: ConcurrencyConfig,
}

pub enum FunctionRuntime {
    Node20,
    Node22,
    Python311,
    Python312,
    Rust,
    Go122,
    Java21,
    Dotnet8,
    Ruby33,
    Custom { image: String },
}

pub struct FunctionCode {
    /// Source code CID in Synor Storage
    pub cid: Cid,
    /// Entry point file
    pub entry_point: String,
    /// Dependencies (package.json, requirements.txt, etc.)
    pub dependencies: Option<Cid>,
}

pub struct FunctionResources {
    pub memory_mb: u32,       // 128, 256, 512, 1024, 2048, 4096, 8192
    pub cpu_allocation: f32,  // Proportional to memory
    pub ephemeral_storage_mb: u32,
    pub gpu: Option<GpuAllocation>,
}

pub enum FunctionTrigger {
    /// HTTP endpoint
    Http { path: String, methods: Vec<HttpMethod> },
    /// Scheduled execution (cron)
    Schedule { cron: String },
    /// Event from message queue
    Queue { queue_name: String },
    /// Storage events
    Storage { bucket: String, events: Vec<StorageEvent> },
    /// Blockchain events
    Blockchain { contract: Address, events: Vec<String> },
    /// Webhook
    Webhook { url: String },
}

4.2 Cold Start Optimization

// synor-compute/src/serverless/warmup.rs

/// Function warmup strategies
pub struct WarmupConfig {
    /// Minimum warm instances
    pub min_instances: u32,
    /// Provisioned concurrency
    pub provisioned_concurrency: u32,
    /// Warmup schedule
    pub warmup_schedule: Option<String>,
    /// Snapshot-based cold start (SnapStart)
    pub snapstart_enabled: bool,
}

pub struct ColdStartOptimizer {
    /// Pre-warmed function pools
    pools: HashMap<FunctionRuntime, WarmPool>,
    /// Snapshot cache
    snapshots: LruCache<FunctionId, FunctionSnapshot>,
    /// Prediction model for scaling
    predictor: ScalingPredictor,
}

impl ColdStartOptimizer {
    /// Get a warm instance or create one
    pub async fn get_instance(&self, function: &Function) -> Result<FunctionInstance, Error> {
        // Try snapshot restore first (< 100ms)
        if let Some(snapshot) = self.snapshots.get(&function.function_id) {
            return self.restore_from_snapshot(snapshot).await;
        }

        // Try warm pool (< 50ms)
        if let Some(instance) = self.pools.get(&function.runtime)?.get_warm() {
            return Ok(instance);
        }

        // Cold start (1-5s depending on runtime)
        self.cold_start(function).await
    }
}

4.3 Serverless Pricing

Resource	Unit	Price (SYNOR)
Invocations	1M requests	0.20
Duration	GB-second	0.00001
Provisioned concurrency	GB-hour	0.01
HTTP Gateway	1M requests	0.10
Event bridge	1M events	0.50

---

Milestone 5: Edge Compute

5.1 Edge Node Architecture

// synor-compute/src/edge/node.rs

/// Edge compute node
pub struct EdgeNode {
    pub node_id: NodeId,
    pub location: GeoLocation,
    pub capabilities: EdgeCapabilities,
    pub latency_zones: Vec<LatencyZone>,
    pub resources: EdgeResources,
}

pub struct EdgeCapabilities {
    pub wasm_runtime: bool,
    pub container_runtime: bool,
    pub gpu_inference: bool,
    pub video_transcoding: bool,
    pub cdn_cache: bool,
}

pub struct EdgeResources {
    pub cpu_cores: u32,
    pub memory_gb: u32,
    pub storage_gb: u32,
    pub gpu: Option<EdgeGpu>,
    pub bandwidth_gbps: u32,
}

/// Edge function for low-latency compute
pub struct EdgeFunction {
    pub function_id: FunctionId,
    pub code: WasmModule,
    pub memory_limit: u32,
    pub timeout_ms: u32,
    pub allowed_regions: Vec<Region>,
}

5.2 Edge Use Cases

// synor-compute/src/edge/usecases.rs

/// CDN with compute at edge
pub struct EdgeCdn {
    /// Origin servers
    origins: Vec<Origin>,
    /// Cache rules
    cache_rules: Vec<CacheRule>,
    /// Edge workers for request/response transformation
    workers: Vec<EdgeWorker>,
}

/// Real-time inference at edge
pub struct EdgeInference {
    /// Model optimized for edge (quantized, pruned)
    model_id: ModelId,
    /// Inference runtime (TensorRT, ONNX Runtime)
    runtime: EdgeInferenceRuntime,
    /// Max batch size
    max_batch: u32,
    /// Target latency
    target_latency_ms: u32,
}

/// Video processing at edge
pub struct EdgeVideoProcessor {
    /// Transcoding profiles
    profiles: Vec<TranscodingProfile>,
    /// Real-time streaming
    live_streaming: bool,
    /// Adaptive bitrate
    abr_enabled: bool,
}

5.3 Edge Pricing

Resource	Unit	Price (SYNOR)
Edge function invocations	1M	0.50
Edge function duration	GB-second	0.00002
Edge bandwidth	GB	0.08
Edge cache storage	GB/month	0.02
Video transcoding	minute	0.02

---

Milestone 6: Node Provider Economics

6.1 Provider Registration

// synor-compute/src/provider/registration.rs

/// Compute provider registration
pub struct ProviderRegistration {
    pub provider_id: ProviderId,
    pub owner: Address,
    /// Stake required to become provider
    pub stake: u64,
    /// Hardware specifications
    pub hardware: HardwareManifest,
    /// Network connectivity
    pub network: NetworkManifest,
    /// Geographic location
    pub location: GeoLocation,
    /// Availability SLA commitment
    pub sla: SlaCommitment,
}

pub struct HardwareManifest {
    pub cpus: Vec<CpuSpec>,
    pub memory_total_gb: u64,
    pub gpus: Vec<GpuSpec>,
    pub storage: Vec<StorageSpec>,
    pub verified: bool,  // Hardware attestation passed
}

pub struct SlaCommitment {
    pub uptime_percent: f32,      // 99.9, 99.99, etc.
    pub response_time_ms: u32,
    pub data_durability: f32,
    pub penalty_rate: f32,        // Penalty for SLA violation
}

6.2 Provider Revenue Model

Revenue Source	Provider Share	Protocol Share
Compute fees	85%	15%
Storage fees	80%	20%
Network fees	75%	25%
SLA bonuses	100%	0%
Staking rewards	100%	0%

6.3 Slashing Conditions

Violation	Penalty
Downtime > committed SLA	1% stake per hour
Data loss	10% stake + compensation
Malicious behavior	100% stake
False hardware attestation	50% stake

---

Implementation Timeline

Phase 11.1: Foundation (Weeks 1-4)

• Node registration and hardware attestation
• Basic job scheduler
• WASM runtime integration (existing)
• Container runtime (containerd)
• Network overlay (WireGuard mesh)

Phase 11.2: GPU Compute (Weeks 5-8)

• GPU node registration
• NVIDIA driver integration
• CUDA runtime support
• Basic ML job execution
• Model storage integration

Phase 11.3: Container Orchestration (Weeks 9-12)

• OCI image support
• Service deployment
• Load balancing
• Auto-scaling
• Service mesh (mTLS)

Phase 11.4: Persistent VMs (Weeks 13-16)

• MicroVM runtime (Firecracker)
• VM lifecycle management
• Persistent storage
• Live migration
• Snapshot/restore

Phase 11.5: Serverless (Weeks 17-20)

• Function deployment
• Cold start optimization
• Event triggers
• API gateway
• Monitoring/logging

Phase 11.6: Edge Compute (Weeks 21-24)

• Edge node registration
• Edge function runtime
• CDN integration
• Edge inference
• Global anycast

---

Security Considerations

Isolation Levels

Workload Type	Isolation Technology	Security Level
WASM	Wasmtime sandbox	High
Serverless	gVisor + seccomp	High
Containers	gVisor or Kata	Medium-High
VMs	Firecracker MicroVM	High
GPU	NVIDIA MIG/MPS	Medium

Network Security

• All inter-node traffic encrypted (WireGuard)
• mTLS for service-to-service communication
• Network policies for workload isolation
• DDoS protection at edge

Data Security

• Encryption at rest (AES-256)
• Encryption in transit (TLS 1.3)
• Confidential computing support (AMD SEV, Intel SGX)
• Secure key management (HSM integration)

---

API Examples

Deploy AI Training Job

synor compute train create \
  --framework pytorch \
  --model-config ./model.yaml \
  --dataset synor://datasets/imagenet \
  --gpus 8 \
  --gpu-type h100 \
  --distributed ddp \
  --epochs 100 \
  --checkpoint-interval 1000 \
  --max-budget 1000

Deploy Inference Endpoint

synor compute inference deploy \
  --model synor://models/llama-70b \
  --format vllm \
  --min-replicas 2 \
  --max-replicas 10 \
  --gpu-per-replica 2 \
  --target-utilization 0.7

Create Persistent VM

synor compute vm create \
  --name my-dev-server \
  --image ubuntu:22.04 \
  --size gpu-small \
  --volume 100gb:nvme:/data \
  --ssh-key ~/.ssh/id_ed25519.pub \
  --region us-east

Deploy Container Service

synor compute service deploy \
  --name my-api \
  --image my-registry/my-api:latest \
  --replicas 3 \
  --cpu 2 \
  --memory 4gb \
  --port 8080 \
  --health-check /health \
  --autoscale 2-10

Deploy Serverless Function

synor compute function deploy \
  --name process-image \
  --runtime python312 \
  --handler main.handler \
  --code ./function \
  --memory 1024 \
  --timeout 30000 \
  --trigger http:/api/process

---

Comparison with Existing Synor VM

Feature	Current Synor VM	Synor Compute L2
Runtime	WASM only	WASM, Container, MicroVM
Timeout	30 seconds	Unlimited (VMs)
Memory	16 MB max	Up to 256 GB
GPU	❌	✅ Full CUDA/ROCm
Networking	❌	✅ Full TCP/UDP
File I/O	❌	✅ Persistent volumes
Threading	❌	✅ Multi-threaded
AI/ML	❌	✅ Training + Inference
OS Hosting	❌	✅ Full Linux/Windows

---

Next Steps

1. Milestone 1: Implement GPU node registration and attestation
2. Milestone 2: Build basic job scheduler with resource allocation
3. Milestone 3: Integrate containerd for container workloads
4. Milestone 4: Add Firecracker for MicroVM support
5. Milestone 5: Implement serverless function runtime
6. Milestone 6: Deploy edge nodes and CDN integration

This plan transforms Synor from a smart contract platform into a full-stack decentralized cloud provider capable of competing with AWS/GCP/Azure while maintaining decentralization and censorship resistance.