Intel XEON E-2314 2.80GHZ SKTLGA1200 8.00MB CACHE TRAY

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The answer to the question how much kB in 8 MB is usually 8000 kB, but depending on the vendor of the RAM, hard disk, the software producer or the CPU manufacturer for example, MB could also mean 1024 * 1024 B = 1024 2 bytes. Even a mixed use 1000 * 1024 B cannot completely ruled out. Unless indicated differently, go with 8 MB equal 8000 kB. RuntimeError: CUDA out of memory. Tried to allocate 34.00 MiB (GPU 0; 10.76 GiB total capacity; 1.56 GiB already allocated; 20.75 MiB free; 159.17 MiB cached)

CUDA out of memory. Tried to allocate 176.00 MiB (GPU 0; 3.00 GiB total capacity; 1.79 GiB already allocated; 41.55 MiB free; 1.92 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF

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CUDA out of memory. Tried to allocate 32.00 MiB (GPU 0; 3.00 GiB total capacity; 1.78 GiB already allocated; 21.55 MiB free; 1.94 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF RuntimeError: CUDA out of memory. Tried to allocate 28.00 MiB (GPU 0; 24.00 GiB total capacity; 2.78 GiB already allocated; 19.15 GiB free; 2.82 GiB reserved in total by PyTorch)” I disabled and enabled the graphic card before running the code - thus the VGA ram was 100% empty. Tested on my laptop so it has another GPU as well. Therefore, my GTX 1050 was literally using 0 MB of memory already

CUDA out of memory. Tried to allocate 32.00 MiB (GPU 0; 3.00 GiB total capacity; 1.83 GiB already allocated; 19.54 MiB free; 1.92 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF RuntimeError: CUDA out of memory. Tried to allocate 256.00 GiB (GPU 0; 14.76 GiB total capacity; 824.42 MiB already allocated; 11.68 GiB free; 1.80 GiB reserved in total by PyTorch) CUDA out of memory. Tried to allocate 32.00 MiB (GPU 0; 3.00 GiB total capacity; 1.83 GiB already allocated; 27.55 MiB free; 1.94 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF RuntimeError: CUDA out of memory. Tried to allocate 3.00 GiB (GPU 0; 8.00 GiB total capacity; 3.65 GiB already allocated; 1.18 GiB free; 4.30 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF A gigabyte is a unit of information or computer storage meaning approximately 1.07 billion bytes. This is the definition commonly used for computer memory and file sizes. Microsoft uses this definition to display hard drive sizes, as do most other operating systems and programs by default.I have installed CUDA-enabled Pytorch on Windows 10 computer however when I try speech-to-text decoding with CUDA enabled it fails due to ram error