Performance Notes

Precision Modes

Snapshot storage supports: - storage_compression=False / "none": raw storage. - storage_compression="bf16": bfloat16-compressed storage.

CPU vs CUDA

• CPU path supports float32/float64 propagation and gradients.
• CUDA path is recommended for large ny x nx x nt workloads.

Batching

• Throughput scales with n_shots until memory bandwidth saturation.
• For gradient workloads, tune model_gradient_sampling_interval and storage_mode to control memory use.

Storage Impact

• storage_mode="device" is fastest but VRAM-heavy.
• storage_mode="cpu" / "disk" reduce VRAM pressure with transfer overhead.

Practical Optimization Checklist

1. Choose CUDA for medium/large models and batches.
2. Increase n_shots until throughput saturates, then stop.
3. Balance stencil order and grid spacing for target fidelity.
4. Use storage_mode=auto with byte limits on memory-constrained systems.
5. Profile representative workloads rather than synthetic tiny benchmarks.

Read This Before Enabling Advanced Modes

Before enabling advanced runtime options broadly:

1. Confirm correctness on a small case.
2. Read guides/limitations.md.
3. Run the checks in guides/verification.md.