MATLAB: GpuArray memory requirement estimation

gpuarray gpudevice memory

Dear All,
I was running a script employing parallel processing and a gpuArray structure. I get the following error on two PCs with different Nvidia cards
Error using gpuArray.eye An unexpected error occurred during CUDA execution. The CUDA error was: out of memory
Ressetting the gpuDevice(1) on either box does not help.
Questions: 1. How can I estimate what memory is required by any gpuArray (I know the available GPU memory with gpuDevice() command, but not that requested)
2. Besides a true relative memory deficit (task vs available), what other causes could lead to this error?
For example, I work on a PC 64 bit windows 8.1, matlab R2014a
GPU: gpuDevice()
ans =
CUDADevice with properties:
                      Name: 'GeForce GTX 645'
                     Index: 1
         ComputeCapability: '3.0'
            SupportsDouble: 1
             DriverVersion: 5.5000
            ToolkitVersion: 5.5000
        MaxThreadsPerBlock: 1024
          MaxShmemPerBlock: 49152
        MaxThreadBlockSize: [1024 1024 64]
               MaxGridSize: [2.1475e+09 65535 65535]
                 SIMDWidth: 32
               TotalMemory: 1.0737e+09
                FreeMemory: 207220736
       MultiprocessorCount: 3
              ClockRateKHz: 823500
               ComputeMode: 'Default'
      GPUOverlapsTransfers: 1
    KernelExecutionTimeout: 1
          CanMapHostMemory: 1
           DeviceSupported: 1
            DeviceSelected: 1
Thank you,
Octavian

Best Answer

Hi. It sounds like you're using the same card for both graphics and computation - this will put quite severe limitations on the amount of memory you have available.
1. The simplest way is to gather() your gpuArray to the CPU and call whos. This will tell you the amount of space it takes up in bytes (short of a small amount of header information). The equation is pretty simple, it's just numel(X) * 8 for double-precision arrays (the standard). Or multiply by 16 if the array is complex.
2. There are no other ways to get an Out of Memory error when calling gpuArray.eye(). Other functions will sometimes run out of memory because they need to create intermediate arrays as part of the computation; this error will still only be thrown when trying to allocate more memory than is available.
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