Add new scheduler component for distributed ML workload orchestration: - Hub-based coordination for multi-worker clusters - Pacing controller for rate limiting job submissions - Priority queue with preemption support - Port allocator for dynamic service discovery - Protocol handlers for worker-scheduler communication - Service manager with OS-specific implementations - Connection management and state persistence - Template system for service deployment Includes comprehensive test suite: - Unit tests for all core components - Integration tests for distributed scenarios - Benchmark tests for performance validation - Mock fixtures for isolated testing Refs: scheduler-architecture.md |
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