gputools - OpenCL accelerated volume processing in Python
This package aims to provide GPU accelerated implementations of common volume processing algorithms to the python ecosystem, such as
- convolutions
- denoising
- synthetic noise
- ffts (simple wrapper around reikna)
- affine transforms
via OpenCL and the excellent pyopencl bindings.
Some examples of processing tasks and their respective runtime (tests/benchmark/benchmark.py
):
Task | Image Size/type | CPU[1] | GPU[2] | GPU (w/o transfer)[3] |
---|---|---|---|---|
Mean filter 7x7x7 | (128, 1024, 1024) uint8 | 2627 ms | 99 ms | 24 ms |
Median filter 3x3x3 | (128, 1024, 1024) uint8 | 59750 ms | 346 ms | 252 ms |
Gaussian filter 5x5x5 | (128, 1024, 1024) float32 | 9594 ms | 416 ms | 101 ms |
Zoom/Scale 2x2x2 | (128, 1024, 1024) uint8 | 61829 ms | 466 ms | - |
NLM denoising | (64, 256, 256) float32 | 52736 ms | 742 ms | - |
FFT (pow2) | (128, 1024, 1024) complex64 | 13831 ms | 615 ms | 69 ms |
[1] Xeon(R) CPU E5-2630 v4 using numpy/scipy functions
[2] NVidia Titan X using gputools
[3] as [2] but without CPU->GPU->CPU transfer
Requirements
- python 2.7 / 3.5+
- a working OpenCL environment (check with clinfo).
Installation
pip install gputools
Or the developmental version:
pip install git+https://github.com/maweigert/gputools@develop
Check if basic stuff is working:
python -m gputools
Troubleshooting
If you experience installation issues in Windows, this might be due to pyopencl
not
being properly installed.
- Download the correct pyopencl wheel for your platform
- Install it via
pip install pyopenclโ2020.2.2+cl21โcp38โcp38โwin_amd64.whl
Usage
Docs are still to be done ;)
Most of the methods work on both numpy arrays or GPU memory objects (gputools.OCLArrays/OCLImage). The latter saving the memory transfer (which e.g. for simple convolutions accounts for the main run time)
Convolutions
- 2D-3D convolutions
- separable convolutions
- fft based convolution
- spatially varying convolutions
import gputools
d = np.zeros((128,128), np.float32)
d[64,64] = 1.
h = np.ones((17,17))
res = gputools.convolve(d,h)
d = np.zeros((128,128,128), np.float32)
d[64,64,64] = 1.
hx,hy,hz = np.ones(7),np.ones(9),np.ones(11)
res = gputools.convolve_sep3(d,hx,hy,hz)
Denoising
bilateral filter, non local means
...
d = np.zeros((128,128,128, np.float32))
d[50:78,50:78,50:78:2] = 4.
d = d+np.random.normal(0,1,d.shape)
res_nlm = gputools.denoise.nlm3(d,2.,2,3)
res_bilat = gputools.denoise.bilateral3(d,3,4.)
Perlin noise
fast 2d and 3d perlin noise calculations
gputools.perlin3(size = (256,256,256), scale = (10.,10.,10.))
Transforms
scaling, translate, rotate, affine...
gputools.transforms.scale(d,.2)
gputools.transforms.rotate(d,axis = (64,64,64),angle = .3)
gputools.transforms.shift(d,(10,20,30))
...
fft
wraps around reikna
gputools.fft(d)
gputools.fft(d, inverse = True)
Configuration
Some configuration data (e.g. the default OpenCL platform and devic) can be changed in the config file "~/.gputools" (create it if necessary)
#~/.gputools
id_platform = 0
id_device = 1
See
gputools.config.defaults
for available keys and their defaults.
Alternatively, the used OpenCL Device can be set via the environment variables gputools_id_device
, gputools_id_platform
, and gputools_use_gpu
(variables present in the config file will take precendence, however).
Troubleshooting
pyopencl: _cffi.so ImportError
If you see a
ImportError: _cffi.so: undefined symbol: clSVMFree
after importing gputools, this is most likely a problem of pyopencl being installed with an incorrent OpenCL version. Check the OpenCL version for your GPU with clinfo (e.g. 1.2):
clinfo | grep Version
and install pyopencl manually while enforcing your opencl version:
# uninstall pyopencl
pip uninstall pyopencl cffi
# get pyopencl source
git clone https://github.com/pyopencl/pyopencl.git
cd pyopencl
python configure.py
# add in siteconf.py the line
# CL_PRETEND_VERSION = "1.2"
echo 'CL_PRETEND_VERSION = "1.2"' >> siteconf.py
pip install .
where e.g. "1.2" is your version of OpenCL.