SamerMakni/cuda-selector
A simple tool to select the optimal CUDA device based custom criteria.
This tool helps developers and machine learning engineers manage compute resources efficiently by automatically selecting the best available CUDA (or MPS) device. You provide criteria like desired memory, power, temperature, or utilization, and it outputs the identifier for the optimal device(s) to run your computational tasks. This is ideal for anyone running data processing, simulation, or AI/ML workloads on systems with multiple GPUs.
No commits in the last 6 months. Available on PyPI.
Use this if you need to programmatically choose the best GPU for your tasks based on its current performance metrics, ensuring your applications run optimally without manual device selection.
Not ideal if you only have one GPU or if your applications do not require dynamic GPU selection based on real-time metrics.
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Language
Python
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Last pushed
Mar 10, 2025
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