Modal reduced GPU inference replica spin-up from ~2000 seconds to ~50 seconds using four layered infrastructure techniques.
Key Takeaways
Four techniques stack: cloud LP-managed GPU buffers, lazy content-addressed FUSE filesystem, CPU-side checkpoint/restore, and CUDA context checkpoint/restore.
GPU buffer pool is managed by a linear program (Google GLOP) fed live cloud prices and observed supply, keeping idle machines off the hot path.
Lazy container image loading via a content-addressed multi-tier cache eliminates sequential layer pulls; files are served on-demand rather than pre-loaded.
CUDA checkpoint/restore skips full GPU-side initialization by snapshotting and restoring CUDA contexts directly into GPU memory on resume.
Real-world GPU hardware failure rates are high enough that active health checks on boot plus weekly deep diagnostics (dcgmi diag) are required to keep the buffer reliable.
