Question

我正在尝试将scikit-cuda的包装器用于cuSOLVER函数，特别是我想执行cusolverDnSgesvd来计算实数矩阵上的全矩阵单精度SVD。

使用代码here和here作为参考，我设法做到了这一点：

import pycuda.autoinit
import pycuda.driver as drv
import pycuda.gpuarray as gpuarray
import numpy as np

from skcuda import cusolver


handle = cusolver.cusolverDnCreate()

m = 50
n = 25

a = np.asarray(np.random.random((m, n)))
a_gpu = gpuarray.to_gpu(a)

ldu = m
ldvt = n

s_gpu = gpuarray.empty(min(m, n), np.float32)
u_gpu = gpuarray.empty((ldu, m), np.float32)
vh_gpu = gpuarray.empty((n, n), np.float32)

work_size = cusolver.cusolverDnSgesvd_bufferSize(handle, m, n)

work = gpuarray.empty((m,n), np.float32)

u_gpu, s_gpu, vh_gpu = cusolver.cusolverDnSgesvd(
    handle=handle,
    jobu='A',
    jobvt='A',
    m=m,
    n=n,
    A=a,
    lda=m,
    S=s_gpu,
    U=u_gpu,
    ldu=ldu,
    VT=vh_gpu,
    ldvt=ldvt,
    Work=work,
    Lwork=work_size,
    rwork=None,
    devInfo=0
)

但代码不起作用，可能是因为我弄乱了类型。

Traceback (most recent call last):
  File "/home/vektor/PycharmProjects/yancut/test_svd.py", line 44, in <module>
    devInfo=0
  File "/home/vektor/anaconda3/lib/python3.4/site-packages/skcuda/cusolver.py", line 577, in cusolverDnSgesvd
    int(A), lda, int(S), int(U),
TypeError: only length-1 arrays can be converted to Python scalars

我应该如何提供所有参数，以便以正确的方式执行SVD？

UPDATE1： 在使用this问题作为参考后，我编辑了代码并收到了新错误。

import pycuda.autoinit
import pycuda.driver as drv
import pycuda.gpuarray as gpuarray
import numpy as np

import ctypes

from skcuda import cusolver

rows = 20
cols = 10

a = np.asarray(np.random.random((rows, cols)))
a_gpu = gpuarray.to_gpu(a.copy())
lda = rows

u_gpu = gpuarray.empty((rows, rows), np.float32)
v_gpu = gpuarray.empty((cols, cols), np.float32)
s_gpu = gpuarray.empty(cols, np.float32)
devInfo = gpuarray.zeros(1, np.int32)

handle = cusolver.cusolverDnCreate()

worksize = cusolver.cusolverDnSgesvd_bufferSize(handle, rows, cols)
print("SIZE", worksize)

Workspace = gpuarray.empty(worksize, np.float32)

svd_status = cusolver.cusolverDnSgesvd(
    handle=handle,
    jobu='A',
    jobvt='A',
    m=rows,
    n=cols,
    A=a_gpu.ptr,
    lda=rows,
    S=s_gpu.ptr,
    U=u_gpu.ptr,
    ldu=rows,
    VT=v_gpu.ptr,
    ldvt=cols,
    Work=Workspace.ptr,
    Lwork=worksize,
    rwork=Workspace.ptr,
    devInfo=devInfo.ptr
)
status = cusolver.cusolverDnDestroy(handle)

我收到了新错误

Traceback (most recent call last):
  File "/home/vektor/PycharmProjects/yancut/test_svd.py", line 53, in <module>
    devInfo=devInfo.ptr
  File "/home/vektor/anaconda3/lib/python3.4/site-packages/skcuda/cusolver.py", line 579, in cusolverDnSgesvd
    Lwork, int(rwork), int(devInfo))
ctypes.ArgumentError: argument 2: <class 'TypeError'>: wrong type

现在看来，我对devInfo

做错了

Answer 1

从documentation看起来每个矩阵（所以A，S，U，VT）都需要作为设备指针传递。因此对于PyCUDA gpuarrays，传递A.ptr而不是A。它应该工作。

使用scikit-cuda用cuSOLVER计算奇异值分解

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