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Add an opt‑in “fast path” configuration preset tuned for typical RTX GPUs that reuses the existing configuration system but applies performance‑oriented defaults such as autocast, recommended batch sizes, and CUDA/cuDNN flags. This should complement and build on top of the work tracked in #5 (Adaptive OS-based support for RTX series).
Why
Many users will have “standard” RTX setups where a curated set of defaults can provide an immediate speed boost.
Centralizing these choices in a named profile makes it easier to test, reproduce, and iterate on performance improvements.
Keeping this as a preset ensures existing conservative defaults remain available.
What to do
Define a named profile (e.g., rtx-fast) in the existing config system.
For that profile, specify:
Autocast / mixed precision defaults appropriate for RTX.
Add an opt‑in “fast path” configuration preset tuned for typical RTX GPUs that reuses the existing configuration system but applies performance‑oriented defaults such as autocast, recommended batch sizes, and CUDA/cuDNN flags. This should complement and build on top of the work tracked in #5 (Adaptive OS-based support for RTX series).
Why
What to do
rtx-fast) in the existing config system.--profile rtx-fast), reusing the central config object from Centralize config via Pydantic/dataclass and env overrides #2.Acceptance criteria