When I try to run the example "Waveform Segmentation Using Deep Learning" Matlab stops the execution at very beginning with:
Error using trainNetwork (line 170)Unexpected error calling cuDNN: CUDNN_STATUS_EXECUTION_FAILED.
or sometimes with:
Failed to initialize GPU BLAS library.
preceded by multiple copies of theis warning:
Warning: An unexpected error occurred during CUDA execution. The CUDA error was:CUDA_ERROR_LAUNCH_FAILED
when I try to reset the GPU, I get the error:
Error using parallel.gpu.CUDADevice/resetAn unexpected error occurred during CUDA execution. The CUDA error was:all CUDA-capable devices are busy or unavailable
and have to exit/restart Matlab. I already set TdrLevel to 0, the GPU is not connected to any screen (although I cannot set it to TCC mode as it is not supported).
I also tried
try nnet.internal.cnngpu.reluForward(1);catch MEend
I use Matlab 2019b Update 1, the gpuDevice output is:
Name: 'GeForce RTX 2080 SUPER' Index: 1 ComputeCapability: '7.5' SupportsDouble: 1 DriverVersion: 10.1000 ToolkitVersion: 10.1000 MaxThreadsPerBlock: 1024 MaxShmemPerBlock: 49152 MaxThreadBlockSize: [1024 1024 64] MaxGridSize: [2.1475e+09 65535 65535] SIMDWidth: 32 TotalMemory: 8.5899e+09 AvailableMemory: 6.8422e+09 MultiprocessorCount: 48 ClockRateKHz: 1845000 ComputeMode: 'Default' GPUOverlapsTransfers: 1 KernelExecutionTimeout: 0 CanMapHostMemory: 1 DeviceSupported: 1 DeviceSelected: 1
My old GPU still works without problems but is just very slow
Name: 'GeForce GTX 650 Ti' Index: 2 ComputeCapability: '3.0' SupportsDouble: 1 DriverVersion: 10.1000 ToolkitVersion: 10.1000 MaxThreadsPerBlock: 1024 MaxShmemPerBlock: 49152 MaxThreadBlockSize: [1024 1024 64] MaxGridSize: [2.1475e+09 65535 65535] SIMDWidth: 32 TotalMemory: 2.1475e+09 AvailableMemory: 1.6932e+09 MultiprocessorCount: 4 ClockRateKHz: 1032500 ComputeMode: 'Default' GPUOverlapsTransfers: 1 KernelExecutionTimeout: 0 CanMapHostMemory: 1 DeviceSupported: 1 DeviceSelected: 1
Is the way to get the 2080 to work?
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