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August 28, 2016 20:51
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CUSOLVER getrf demo
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#!/usr/bin/env python | |
""" | |
CUSOLVER getrf demo. | |
""" | |
import numpy as np | |
import scipy.linalg | |
import scipy as sp | |
import pycuda.autoinit | |
import pycuda.gpuarray as gpuarray | |
import skcuda.cusolver as solver | |
h = solver.cusolverDnCreate() | |
x = np.asarray([[1.80, 2.88, 2.05, -0.89], | |
[5.25, -2.95, -0.95, -3.80], | |
[1.58, -2.69, -2.90, -1.04], | |
[-1.11, -0.66, -0.59, 0.80]]).astype(np.float32) | |
# Need to copy transposed matrix because T only returns a view: | |
m, n = x.shape | |
x_gpu = gpuarray.to_gpu(x.T.copy()) | |
# Set up work buffers: | |
Lwork = solver.cusolverDnSgetrf_bufferSize(h, m, n, x_gpu.gpudata, m) | |
workspace_gpu = gpuarray.zeros(Lwork, np.float32) | |
devipiv_gpu = gpuarray.zeros(min(m, n), np.int32) | |
devinfo_gpu = gpuarray.zeros(1, np.int32) | |
# Compute: | |
solver.cusolverDnSgetrf(h, m, n, x_gpu.gpudata, m, workspace_gpu.gpudata, devipiv_gpu.gpudata, devinfo_gpu.gpudata) | |
# Confirm that solution is correct by checking against result obtained with | |
# scipy; set dimensions of computed lower/upper triangular matrices to facilitate | |
# comparison if the original matrix was not square: | |
l_cuda = np.tril(x_gpu.get().T, -1) | |
u_cuda = np.triu(x_gpu.get().T) | |
if m < n: | |
l_cuda = l_cuda[:, :m] | |
else: | |
u_cuda = u_cuda[:n, :] | |
p, l, u = sp.linalg.lu(x) | |
# Only check values in lower triangle starting from first off-diagonal: | |
print 'lower triangular matrix is correct: ', \ | |
np.allclose(np.tril(l, -1), l_cuda) | |
print 'upper triangular matrix is correct: ', \ | |
np.allclose(np.triu(u), u_cuda) |
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