MemoryError: clCreateImage failed: mem object allocation failure

[Kerkil]

I have a "complex-valued" array read from a Matlab data file .mat:

datas = scipy.io.loadmat('/Users/recondev/Projects/RMA/Data/RMA_to_iPython_interpolator_only.mat')
dataIn = datas['vec_in'].astype(np.complex64).view(cl.array.vec.float2).T

dataIn.dtype returns complex64

I am trying to create an 1d image object from the dataIn array using pyopencl.image_from_array, but I receive the following errors:

---------------------------------------------------------------------------
MemoryError                               Traceback (most recent call last)
<ipython-input-69-07fda49d952e> in <module>()
----> 1 dataInImg = pyopencl.image_from_array(ctx, dataInCont)

/Users/recondev/.virtualenvs/ipythonenv/lib/python2.7/site-packages/pyopencl/__init__.pyc in image_from_array(ctx, ary, num_channels, mode, norm_int)
   1178             ImageFormat(img_format, channel_type),
   1179             shape=shape[::-1], pitches=strides[::-1][1:],
-> 1180             hostbuf=ary)
   1181 
   1182 # }}}

/Users/recondev/.virtualenvs/ipythonenv/lib/python2.7/site-packages/pyopencl/__init__.pyc in image_init(self, context, flags, format, shape, pitches, hostbuf, is_array, buffer)
    676             desc.buffer = buffer
    677 
--> 678             image_old_init(self, context, flags, format, desc, hostbuf)
    679         else:
    680             # legacy init for CL 1.1 and older

MemoryError: clCreateImage failed: mem object allocation failure

By reducing the array to a much smaller size (the original array contains 1728_256_13 complex64 values, and the reduced array contains only 1728 complex64 values), I was able to remove the errors.

What I am troubling getting my head around is that when I create an image from float32 (as compared to complex64) array, I am able to create an image containing much larger sized array. I am able to create an image containing 1728_256_13 float32 values (23003136 bytes). However, I keep failing to create an image containing 1728*256 complex64 values (2097152 bytes).

I wonder if this is an expected behavior and what is the reason behind it.

[Kerkil]

I was able to resolve the issue by changing the following

dataInCont = dataInCont.reshape((np.size(dataInCont),1))
dataInCont = np.ascontiguousarray(dataIn)

to (I basically switched the order of the two lines)

dataInCont = np.ascontiguousarray(dataIn)
dataInCont = dataInCont.reshape((np.size(dataInCont),1))

The dataInCont was the input to pyopencl.image_from_array(context, dataInCont).

The mistake I made is that I break the contiguousness of the memory by reshaping the array.