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hcs edited this page Dec 10, 2024
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A list of issues you may encounter and ideas for a remedy.
- cudaErrorInsufficientDriver: Most likely caused by an Nvidia GPU driver that is too old for the CUDA version used by the indexer, see https://docs.nvidia.com/deploy/cuda-compatibility
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cudaErrorLaunchOutOfResources: Most likely caused by the fact, that there isn't enough GPU memory, for various possible reasons
- When building the library in debug mode, executables can get so large as to exhaust GPU resources. The library should be rebuilt in release mode if that is the case.
- Too many indexer objects are created in parallel. If that is the case, and you have several GPUs, maybe you'll be able to set set the INDEXER_GPU_DEVICE to different values for parallel program runs, or you might be able to set the default GPU device programmatically to different devices before creating indexer objects.
- The parameters for the number of maximum spots or input and output cell numbers might be too high. Consider setting them to lower values.