EMM tensorflow gpu_error ai_generated true

InternalError: Blas GEMM launch failed : a]=[32,128], b=[128,64] [Op:MatMul]

ID: tensorflow/aborted-blas-gemm-launch

Also available as: JSON · Markdown
80%Fix Rate
85%Confidence
3Evidence
2023-01-01First Seen

Version Compatibility

VersionStatusIntroducedDeprecatedNotes
2 active — — —

Root Cause

GPU BLAS kernel failed to launch. Caused by GPU memory exhaustion, CUDA version mismatch, or another process holding the GPU.

generic

Workarounds

  1. 88% success Enable GPU memory growth to avoid pre-allocating all VRAM 
    tf.config.experimental.set_memory_growth(gpu, True)  # prevents TF from claiming all VRAM

    Sources: https://www.tensorflow.org/guide/gpu

  2. 85% success Check for other processes using the GPU and kill them 
    nvidia-smi  # check for processes; kill -9 <pid>  # free GPU memory
  3. 82% success Ensure cuBLAS version matches CUDA toolkit 
    ldconfig -p | grep cublas  # verify libcublas matches your CUDA version

Dead Ends

Common approaches that don't work:

  1. Set CUDA_VISIBLE_DEVICES to empty to run on CPU 70% fail

    Avoids GPU entirely. The real fix is resolving the GPU resource conflict.

  2. Reboot the machine to clear GPU state 65% fail

    Only helps if a zombie process holds the GPU. Identify and kill the process instead.