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PyCUDA を使用してスパース cuSOLVER ルーチンcusolverSpDcsrlsvqr() (>= CUDA 7.0) をインターフェイスしようとしていますが、いくつかの問題に直面しています: 密な cuSolver ルーチンが scikits-cuda でラップされているのと同じ方法でメソッドをラップしようとしました ( https:/ /github.com/lebedov/scikits.cuda/blob/master/scikits/cuda/cusolver.py )。

ただし、cusolverSpDcsrlsvqr() 関数を呼び出すと、セグメンテーション違反でコードがクラッシュします。cuda-gdb ( cuda-gdb --args python -m pycuda.debug test.py; run;bt) を使用してデバッグすると、次のスタック トレースが生成されます。

#0 0x00007fffd9e3b71a in cusolverSpXcsrissymHost () from /usr/local/cuda/lib64/libcusolver.so #1 0x00007fffd9df5237 in hsolverXcsrqr_zeroPivot () from /usr/local/cuda/lib64/libcusolver.so
#2 0x00007fffd9e0c764 in hsolverXcsrqr_analysis_coletree () from /usr /local/cuda/lib64/libcusolver.so
#3 0x00007fffd9f160a0 in cusolverXcsrqr_analysis () from /usr/local/cuda/lib64/libcusolver.so
#4 0x00007fffd9f28d78 in cusolverSpScsrlsvqr () from /usr/local/cuda/lib64/libcusolver.so

私は cusolverSp S csrlsvqr() を呼び出しておらず、ホスト関数 (cusolverSpXcsrissym Host ) を呼び出す必要もないと思うので、これは奇妙です。

これは私が話しているコードです - あなたの助けに感謝します:

# ### Interface cuSOLVER PyCUDA


import pycuda.gpuarray as gpuarray
import pycuda.driver as cuda
import pycuda.autoinit
import numpy as np
import scipy.sparse as sp
import ctypes


# #### wrap the cuSOLVER cusolverSpDcsrlsvqr() using ctypes

# cuSparse
_libcusparse = ctypes.cdll.LoadLibrary('libcusparse.so')

class cusparseMatDescr_t(ctypes.Structure):
    _fields_ = [
        ('MatrixType', ctypes.c_int),
        ('FillMode', ctypes.c_int),
        ('DiagType', ctypes.c_int),
        ('IndexBase', ctypes.c_int)
        ]
_libcusparse.cusparseCreate.restype = int
_libcusparse.cusparseCreate.argtypes = [ctypes.c_void_p]

_libcusparse.cusparseDestroy.restype = int
_libcusparse.cusparseDestroy.argtypes = [ctypes.c_void_p]

_libcusparse.cusparseCreateMatDescr.restype = int
_libcusparse.cusparseCreateMatDescr.argtypes = [ctypes.c_void_p]


# cuSOLVER
_libcusolver = ctypes.cdll.LoadLibrary('libcusolver.so')



_libcusolver.cusolverSpCreate.restype = int
_libcusolver.cusolverSpCreate.argtypes = [ctypes.c_void_p]

_libcusolver.cusolverSpDestroy.restype = int
_libcusolver.cusolverSpDestroy.argtypes = [ctypes.c_void_p]



_libcusolver.cusolverSpDcsrlsvqr.restype = int
_libcusolver.cusolverSpDcsrlsvqr.argtypes= [ctypes.c_void_p,
                                            ctypes.c_int,
                                            ctypes.c_int,
                                            cusparseMatDescr_t,
                                            ctypes.c_void_p,
                                            ctypes.c_void_p,
                                            ctypes.c_void_p,
                                            ctypes.c_void_p,
                                            ctypes.c_double,
                                            ctypes.c_int,
                                            ctypes.c_void_p,
                                            ctypes.c_void_p]


#### Prepare the matrix and parameters, copy to Device via gpuarray

# coo to csr
val = np.arange(1,5,dtype=np.float64)
col = np.arange(0,4,dtype=np.int32)
row = np.arange(0,4,dtype=np.int32)
A = sp.coo_matrix((val,(row,col))).todense()
Acsr = sp.csr_matrix(A)
b = np.ones(4)
x = np.empty(4)
print('A:' + str(A))
print('b: ' + str(b))


dcsrVal = gpuarray.to_gpu(Acsr.data)
dcsrColInd = gpuarray.to_gpu(Acsr.indices)
dcsrIndPtr = gpuarray.to_gpu(Acsr.indptr)
dx = gpuarray.to_gpu(x)
db = gpuarray.to_gpu(b)
m = ctypes.c_int(4)
nnz = ctypes.c_int(4)
descrA = cusparseMatDescr_t()
reorder = ctypes.c_int(0)
tol = ctypes.c_double(1e-10)
singularity = ctypes.c_int(99)


#create cusparse handle
_cusp_handle = ctypes.c_void_p()
status = _libcusparse.cusparseCreate(ctypes.byref(_cusp_handle))
print('status: ' + str(status))
cusp_handle = _cusp_handle.value

#create MatDescriptor
status = _libcusparse.cusparseCreateMatDescr(ctypes.byref(descrA))
print('status: ' + str(status))

#create cusolver handle
_cuso_handle = ctypes.c_void_p()
status = _libcusolver.cusolverSpCreate(ctypes.byref(_cuso_handle))
print('status: ' + str(status))
cuso_handle = _cuso_handle.value



print('cusp handle: ' + str(cusp_handle))
print('cuso handle: ' + str(cuso_handle))


### Call solver
_libcusolver.cusolverSpDcsrlsvqr(cuso_handle,
                                 m,
                                 nnz,
                                 descrA,
                                 int(dcsrVal.gpudata),
                                 int(dcsrIndPtr.gpudata),
                                 int(dcsrColInd.gpudata),
                                 int(db.gpudata),
                                 tol,
                                 reorder,
                                 int(dx.gpudata),
                                 ctypes.byref(singularity))

# destroy handles
status = _libcusolver.cusolverSpDestroy(cuso_handle)
print('status: ' + str(status))
status = _libcusparse.cusparseDestroy(cusp_handle)
print('status: ' + str(status))
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1 に答える 1

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ラッパーをに設定descrAしctypes.c_void_p()て置き換えるcusparseMatDescr_tと、問題が解決するはずです。cusolverSpDcsrlsvqrctypes.c_void_p

于 2015-05-29T17:03:26.457 に答える