from libKMCUDA import kmeans_cuda
from time import time
X = np.random.rand(10, 12000).astype(dtype=np.float32)
start = time()
centers_, labels_ = kmeans_cuda(X, 10)
print(time() - start)
0.19472670555114746
It never finishes with 13'000 ÷ 60'000 features.
It throws an error right away with 70'000+ features:
from libKMCUDA import kmeans_cuda
from time import time
X = np.random.rand(10, 70000).astype(dtype=np.float32)
start = time()
centers_, labels_ = kmeans_cuda(X, 10)
print(time() - start)
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-1-8e783410a8e6> in <module>
10
11 start = time()
---> 12 centers_, labels_ = kmeans_cuda(X, 10)
13 print(time() - start)
ValueError: "samples": more than 70000 features is not supported
So my question is:
Is there a limit on horizontal dimension kmcuda can manage or I'm missing something?
I'm running Ubuntu 18.04, conda python 3.7 environment, CUDA 10.2, libKMCuda 6.2.3 installed via pip
kmcuda
runs well until 12'000 features:It never finishes with 13'000 ÷ 60'000 features.
It throws an error right away with 70'000+ features:
So my question is:
I'm running Ubuntu 18.04, conda python 3.7 environment, CUDA 10.2, libKMCuda 6.2.3 installed via pip