SynktiPhase 2

P2P Orchestration for Volatile Compute Infrastructure

Phase 1 Complete | Phase 2 In Progress

80%
Cost Reduction
~10k
Lines of Rust
41
Tests Passing
P2P
Architecture
(no central coordinator)
📦 GitHub Repository 🌐 Website 📝 Technical Blog

~10,000 lines of Rust | 41 tests | P2P orchestration | AGPL-3.0

Phase 2: Production Orchestrator (In Progress)

Evolved from centralized control plane to P2P autonomous protocol. Each node is self-aware, self-monitoring, and self-healing—the natural foundation for DePIN.

7,537 Lines of Rust

EC2 spot management, S3 integration, SSM remote execution, IMDSv2 preemption detection, ELB routing, P2P peer discovery, stateless failover, RAII auto-cleanup

Architectural Evolution

Centralized Control Plane → P2P Autonomous Protocol. No central coordinator means no capture point—permissionless by design.

Technical Deep-Dives

Stateless Failover → Infrastructure as a Library → Banker's Algorithm for Distributed Systems →

Demo Coming Soon: Distributed system demo will be uploaded once current AWS integration is complete.

Phase 1: Simulation Engine (Complete)

The research prototype achieves up to 80% cost reduction for GPU workloads on volatile spot instances through provably optimal migration and intelligent checkpoint recovery. 2,204 lines of Rust, 41 tests passing.

Key Findings (200 tasks, 72-hour simulation)

  • Optimal Kuhn-Munkres migration provides 7-46% cost reduction vs naive first-fit (policy-dependent)
  • Greedy-Optimal policy achieves 79.9% cost savings vs on-demand baseline
  • Checkpoint recovery successfully handles preemption events
  • 45% fewer preemptions with optimal migration (Greedy policy)

Interactive Visualizations

Explore the benchmark results through interactive Plotly charts. Hover for details, zoom, and pan.

📊 Benchmark Comparison

Cost comparison across all policies. Shows the 200-task, 72-hour simulation results with optimal vs naive migration strategies.

View Benchmark →

🎯 Naive vs Optimal

Direct comparison demonstrating the superiority of Kuhn-Munkres optimal migration over naive first-fit assignment.

View Comparison →

📈 Spot Price Behavior

Realistic spot instance market simulation using Ornstein-Uhlenbeck stochastic process. Shows price volatility and preemption risk.

View Market Simulation →

Try It Yourself

Run the simulation on your own machine. Requires Rust 1.91+ (no GPU needed - pure CPU simulation).

# Clone the repository git clone https://github.com/bobby-math/synkti cd synkti/crates # Run 200-task, 72-hour simulation cargo run --release -p synkti-simulation-engine -- --duration 72 --tasks 200 # Run all tests (32 passing) cargo test -p synkti-simulation-engine # Generate visualizations cargo run --example visualize_benchmark_comparison cargo run --example visualize_naive_vs_optimal cargo run --example visualize_spot_behavior

Technical Highlights

🧮 Kuhn-Munkres Migration

Provably optimal task-to-instance assignment using Hungarian algorithm. 443 lines, 11 tests.

⏱️ Checkpoint Recovery

Intelligent exploitation of AWS's 120-second grace period. Full/Partial/Restart decision logic. 382 lines, 9 tests.

🔄 Domain-Agnostic Design

Clean separation between orchestration logic and workload type via pluggable scheduling policies.

Benchmark Configuration

Workload: 200 inference tasks (Llama-2-70B equivalent)

Duration: 72 hours continuous simulation

Spot Price: $0.30/hr (30% of on-demand)

On-Demand Price: $1.00/hr (baseline)

Preemption Rate: 5% per hour (realistic AWS rate)

Network Bandwidth: 10 Gbps (typical AWS instance)