gpu-optimizer
bymathews-tom· 56 skills
GPU optimization for consumer NVIDIA GPUs (8-24GB VRAM) covering mixed precision, gradient checkpointing, XGBoost GPU, CuPy/cuDF migration, and torch.compile. Triggers on: "optimize GPU training", "speed up CUDA", "reduce OOM", "migrate NumPy to CuPy", "manage GPU memory", "benchmark PyTorch".
How to install gpu-optimizer?
mathews-tom/armory/gpu-optimizer
$npx -y skills add mathews-tom/armory --skill gpu-optimizerInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/mathews-tom/armory" --skill "mathews-tom/armory/gpu-optimizer"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/mathews-tom/armory" that are relevant to the current task. Run `npx skills add "https://github.com/mathews-tom/armory"` and select the relevant skills, then follow their instructions.
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