Dear pyCuda mailing list readers,
I am aware that this question is rather directly CUDA related, but as I use
pycuda, I just wanted to try if someone had similar problems already.
The error I get :
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/peter/PhD/img_fac/pycuda/complementarity/complementarity.py",
line 240, in getPocketASAProfile
A=getSurfaceGPU(pocket, r, nbPtPerUnitSphere, pocket_ref, ligand,
xyz_name="pocket.xyz")
File "/home/peter/PhD/img_fac/pycuda/complementarity/complementarity.py",
line 132, in getSurfaceGPU
m=cu.getSurfacePts(test_points, reference.xyz,
reference["vdw"]+probe+correct, atom_idx, ligref.xyz, mol.xyz)
File "cudm.py", line 239, in getSurfacePts
npy.uint16(lig_ref.shape[0]), block=(bX,bY,1), grid=(gX,gY))
File
"/usr/local/lib64/python2.6/site-packages/pycuda-0.93-py2.6-linux-x86_64.egg/pycuda/driver.py",
line 138, in function_call
Context.synchronize()
pycuda._driver.LaunchError: cuCtxSynchronize failed: launch failed
>>> >>>
terminate called after throwing an instance of 'cuda::error'
what(): cuMemFree failed: launch failed
What I am doing :
I am calculating if a point on a surface of a sphere (atom) is exposed or
occluded by other atoms. I am doing this using a 3d array of coordinates.
The length of the coordinate vector can be different thus I have written a
function that gives me "possible but not optimal" values for the grid size,
and block size to use to run the calculation on the GPU in 1D. Thus, I only
use the X dimension for blocks and grids here.
Following an output of blocksize.X, blocksize.y, gridSize.x, gridSize.y
that I calculate (and subsequent calculation runs successfully on the GPU)
:
(4, 1, 4363, 1)
(499, 1, 40, 1)
(499, 1, 40, 1)
(458, 1, 50, 1)
(458, 1, 50, 1)
(380, 1, 68, 1)
(380, 1, 68, 1)
(297, 1, 97, 1)
(297, 1, 97, 1)
(3, 1, 10607, 1)
(3, 1, 10607, 1)
(3, 1, 11731, 1)
(3, 1, 11731, 1)
(63, 1, 619, 1)
(63, 1, 619, 1)
(33, 1, 1297, 1)
(33, 1, 1297, 1)
(3, 1, 15559, 1)
(3, 1, 15559, 1)
(411, 1, 123, 1)
(411, 1, 123, 1)
(21, 1, 2609, 1)
(21, 1, 2609, 1)
(487, 1, 122, 1)
(487, 1, 122, 1)
(475, 1, 135, 1)
(475, 1, 135, 1)
(26, 1, 2647, 1)
(26, 1, 2647, 1)
(2, 1, 36781, 1)
(2, 1, 36781, 1)
(74, 1, 1063, 1)
(74, 1, 1063, 1)
(473, 1, 178, 1)
(473, 1, 178, 1)
(493, 1, 182, 1)
(493, 1, 182, 1)
(1, 1, 95287, 1) <-- interesting here, because 95287 is bigger than the
maximum x dimension of a grid (65536)
(7, 1, 1, 1) <-- thus I substract 3, or 7 or whatever uneven number
from the data, and run the same thing again...we end up with something
possbile)
(7, 1, 1, 1)
(397, 1, 240, 1) <- - here it crashes with the error shown above...this is
the major bunch of the previous data. My card 9800GTX+ supports up to 512
threads/block.
Someone has an idea how I can track down the problem.
Furthermore after this operation when I close the python interpreter,
pycuda is not able to unalloc the memory on the device.
Ah yes, my cuda call looks like this :
isASAPoint(drv.Out(mask), drv.In(x1),drv.In(x2),
drv.In(y1),drv.In(y2),drv.In(z1),drv.In(z2),
drv.In(radii), npy.uint16(molxyz.shape[0]),
drv.In(excluded_idx),drv.In(pocket),drv.In(lig_ref),
npy.uint16(lig_ref.shape[0]), block=(bX,bY,1),
grid=(gX,gY))
So I use the drv in and out functions from pycuda.
Thanks in advance.
--
Peter Schmidtke
----------------------
PhD Student at the Molecular Modeling and Bioinformatics Group
Dep. Physical Chemistry
Faculty of Pharmacy
University of Barcelona
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