Queue single-node GPU experiments with a minimal, GPU-aware spooler

Queue single-node GPU experiments with a minimal, GPU-aware spooler targets a $1.2B = 3,000,000 developers/experimenters × $400 ACV total addressable market with medium saturation and a year-over-year growth rate of 15% YoY — growth inferred from increased ML tooling adoption and rise in local/edge experimentation (community signals + tooling reports).

Key trends driving demand: Local-first experimentation — more model development happens on personal or single-node machines, creating demand for lightweight tooling.; Tooling fatigue with heavyweight MLOps — teams prefer simple, focused tools for developer velocity rather than full cluster solutions.; Containerization and reproducible environments — users expect tooling to capture environment and dependencies, creating opportunity for small tools that bundle reproducibility..