Crowdsourcing GPU Power: Building a Distributed ML Compute Orchestrator

As ML training demands escalate, idle consumer hardware becomes a valuable resource pool. This post reveals the orchestration challenges that determine success—from race conditions in concurrent task allocation to GPU-first scoring algorithms—insights essential for any system managing heterogeneous compute resources at scale.