def _setup_scalar_ptr(handle, a, dtype):
a, a_ptr = _get_scalar_ptr(a, dtype)
mode = cublas.getPointerMode(handle)
if isinstance(a, cupy.ndarray):
cublas.setPointerMode(handle, cublas.CUBLAS_POINTER_MODE_DEVICE)
else:
cublas.setPointerMode(handle, cublas.CUBLAS_POINTER_MODE_HOST)
return a, a_ptr, mode
def _setup_scalar_ptr(handle, a, dtype):
mode = cublas.getPointerMode(handle)
if isinstance(a, cupy.ndarray):
if a.dtype != dtype:
a = cupy.array(a, dtype=dtype)
a_ptr = a.data.ptr
cublas.setPointerMode(handle, cublas.CUBLAS_POINTER_MODE_DEVICE)
else:
if not (isinstance(a, numpy.ndarray) and a.dtype == dtype):
a = numpy.array(a, dtype=dtype)
a_ptr = a.ctypes.data
cublas.setPointerMode(handle, cublas.CUBLAS_POINTER_MODE_HOST)
return a_ptr, mode
def sbmv(k, alpha, a, x, beta, y, lower=False):
"""Computes y = alpha*A @ x + beta * y
"""
dtype = a.dtype.char
if dtype == 'f':
func = cublas.ssbmv
elif dtype == 'd':
func = cublas.dsbmv
else:
raise TypeError('Complex dtypes not supported')
assert a.ndim == 2
assert x.ndim == y.ndim == 1
assert a.dtype == x.dtype == y.dtype
m, n = a.shape
assert x.shape[0] == n
assert y.shape[0] == n
if not a._f_contiguous:
a = a.copy(order='F')
alpha, alpha_ptr = _get_scalar_ptr(alpha, a.dtype)
beta, beta_ptr = _get_scalar_ptr(beta, a.dtype)
handle = device.get_cublas_handle()
orig_mode = cublas.getPointerMode(handle)
if isinstance(alpha, cupy.ndarray) or isinstance(beta, cupy.ndarray):
if not isinstance(alpha, cupy.ndarray):
alpha = cupy.array(alpha)
alpha_ptr = alpha.data.ptr
if not isinstance(beta, cupy.ndarray):
beta = cupy.array(beta)
beta_ptr = beta.data.ptr
cublas.setPointerMode(handle, cublas.CUBLAS_POINTER_MODE_DEVICE)
else:
cublas.setPointerMode(handle, cublas.CUBLAS_POINTER_MODE_HOST)
if lower:
uplo = cublas.CUBLAS_FILL_MODE_LOWER
else:
uplo = cublas.CUBLAS_FILL_MODE_UPPER
handle = device.get_cublas_handle()
try:
func(handle, uplo, n, k,
alpha_ptr, a.data.ptr, m, x.data.ptr, 1,
beta_ptr, y.data.ptr, 1)
finally:
cublas.setPointerMode(handle, orig_mode)
return y
def __init__(self, A, V, alpha, beta, update_impl='fast'):
assert A.ndim == V.ndim == 2
assert alpha.ndim == beta.ndim == 1
assert A.dtype == V.dtype == alpha.dtype
assert A.dtype.char.lower() == beta.dtype.char
assert A.shape[0] == A.shape[1] == V.shape[1]
assert V.shape[0] == alpha.shape[0] == beta.shape[0]
self.A = A
self.V = V
self.alpha = alpha
self.beta = beta
self.n = V.shape[1]
self.ncv = V.shape[0]
self.update_impl = update_impl
if self.update_impl != 'fast':
return
self.cublas_handle = device.get_cublas_handle()
self.cublas_pointer_mode = _cublas.getPointerMode(self.cublas_handle)
if A.dtype.char == 'f':
self.dotc = _cublas.sdot
self.nrm2 = _cublas.snrm2
self.gemm = _cublas.sgemm
elif A.dtype.char == 'd':
self.dotc = _cublas.ddot
self.nrm2 = _cublas.dnrm2
self.gemm = _cublas.dgemm
elif A.dtype.char == 'F':
self.dotc = _cublas.cdotc
self.nrm2 = _cublas.scnrm2
self.gemm = _cublas.cgemm
elif A.dtype.char == 'D':
self.dotc = _cublas.zdotc
self.nrm2 = _cublas.dznrm2
self.gemm = _cublas.zgemm
else:
raise TypeError('invalid dtype ({})'.format(A.dtype))
if csr.isspmatrix_csr(A) and cusparse.check_availability('spmv'):
self.cusparse_handle = device.get_cusparse_handle()
self.spmv_op_a = _cusparse.CUSPARSE_OPERATION_NON_TRANSPOSE
self.spmv_alpha = numpy.array(1.0, A.dtype)
self.spmv_beta = numpy.array(0.0, A.dtype)
self.spmv_cuda_dtype = cusparse._dtype_to_DataType(A.dtype)
self.spmv_alg = _cusparse.CUSPARSE_MV_ALG_DEFAULT
else:
self.cusparse_handle = None
self.v = cupy.empty((self.n, ), dtype=A.dtype)
self.u = cupy.empty((self.n, ), dtype=A.dtype)
self.uu = cupy.empty((self.ncv, ), dtype=A.dtype)
def _setup_result_ptr(handle, out, dtype):
mode = cublas.getPointerMode(handle)
if out is None or isinstance(out, cupy.ndarray):
if out is None or out.dtype != dtype:
result = cupy.empty([], dtype=dtype)
else:
result = out
result_ptr = result.data.ptr
cublas.setPointerMode(handle, cublas.CUBLAS_POINTER_MODE_DEVICE)
elif isinstance(out, numpy.ndarray):
if out.dtype != dtype:
result = numpy.empty([], dtype=dtype)
else:
result = out
result_ptr = result.ctypes.data
cublas.setPointerMode(handle, cublas.CUBLAS_POINTER_MODE_HOST)
else:
raise TypeError('out must be either cupy or numpy ndarray')
return result_ptr, result, mode
def _lanczos_fast(A, n, ncv):
cublas_handle = device.get_cublas_handle()
cublas_pointer_mode = _cublas.getPointerMode(cublas_handle)
if A.dtype.char == 'f':
dotc = _cublas.sdot
nrm2 = _cublas.snrm2
gemm = _cublas.sgemm
elif A.dtype.char == 'd':
dotc = _cublas.ddot
nrm2 = _cublas.dnrm2
gemm = _cublas.dgemm
elif A.dtype.char == 'F':
dotc = _cublas.cdotc
nrm2 = _cublas.scnrm2
gemm = _cublas.cgemm
elif A.dtype.char == 'D':
dotc = _cublas.zdotc
nrm2 = _cublas.dznrm2
gemm = _cublas.zgemm
else:
raise TypeError('invalid dtype ({})'.format(A.dtype))
cusparse_handle = None
if csr.isspmatrix_csr(A) and cusparse.check_availability('spmv'):
cusparse_handle = device.get_cusparse_handle()
spmv_op_a = _cusparse.CUSPARSE_OPERATION_NON_TRANSPOSE
spmv_alpha = numpy.array(1.0, A.dtype)
spmv_beta = numpy.array(0.0, A.dtype)
spmv_cuda_dtype = _dtype.to_cuda_dtype(A.dtype)
spmv_alg = _cusparse.CUSPARSE_MV_ALG_DEFAULT
v = cupy.empty((n, ), dtype=A.dtype)
uu = cupy.empty((ncv, ), dtype=A.dtype)
one = numpy.array(1.0, dtype=A.dtype)
zero = numpy.array(0.0, dtype=A.dtype)
mone = numpy.array(-1.0, dtype=A.dtype)
outer_A = A
def aux(A, V, u, alpha, beta, i_start, i_end):
assert A is outer_A
beta_eps = inversion_eps(A.dtype)
# Get ready for spmv if enabled
if cusparse_handle is not None:
# Note: I would like to reuse descriptors and working buffer
# on the next update, but I gave it up because it sometimes
# caused illegal memory access error.
spmv_desc_A = cusparse.SpMatDescriptor.create(A)
spmv_desc_v = cusparse.DnVecDescriptor.create(v)
spmv_desc_u = cusparse.DnVecDescriptor.create(u)
buff_size = _cusparse.spMV_bufferSize(
cusparse_handle, spmv_op_a, spmv_alpha.ctypes.data,
spmv_desc_A.desc, spmv_desc_v.desc, spmv_beta.ctypes.data,
spmv_desc_u.desc, spmv_cuda_dtype, spmv_alg)
spmv_buff = cupy.empty(buff_size, cupy.int8)
v[...] = V[i_start]
for i in range(i_start, i_end):
# Matrix-vector multiplication
if cusparse_handle is None:
u[...] = A @ v
else:
_cusparse.spMV(cusparse_handle, spmv_op_a,
spmv_alpha.ctypes.data, spmv_desc_A.desc,
spmv_desc_v.desc, spmv_beta.ctypes.data,
spmv_desc_u.desc, spmv_cuda_dtype, spmv_alg,
spmv_buff.data.ptr)
# Call dotc
_cublas.setPointerMode(cublas_handle,
_cublas.CUBLAS_POINTER_MODE_DEVICE)
try:
dotc(cublas_handle, n, v.data.ptr, 1, u.data.ptr, 1,
alpha.data.ptr + i * alpha.itemsize)
finally:
_cublas.setPointerMode(cublas_handle, cublas_pointer_mode)
# Orthogonalize
gemm(cublas_handle, _cublas.CUBLAS_OP_C, _cublas.CUBLAS_OP_N, 1,
i + 1, n, one.ctypes.data, u.data.ptr, n, V.data.ptr, n,
zero.ctypes.data, uu.data.ptr, 1)
gemm(cublas_handle, _cublas.CUBLAS_OP_N, _cublas.CUBLAS_OP_C, n, 1,
i + 1, mone.ctypes.data, V.data.ptr, n, uu.data.ptr, 1,
one.ctypes.data, u.data.ptr, n)
# Call nrm2
_cublas.setPointerMode(cublas_handle,
_cublas.CUBLAS_POINTER_MODE_DEVICE)
try:
nrm2(cublas_handle, n, u.data.ptr, 1,
beta.data.ptr + i * beta.itemsize)
finally:
_cublas.setPointerMode(cublas_handle, cublas_pointer_mode)
# Break here as the normalization below touches V[i+1]
if i >= i_end - 1:
break
if beta[i] < beta_eps:
V[i + 1:i_end, :] = 0
u[...] = 0
v[...] = 0
break
if i == i_start:
beta_eps *= beta[i] # scale eps to largest beta
# Normalize
_kernel_normalize(u, beta, i, n, v, V)
return aux
def syrk(trans, a, out=None, alpha=1.0, beta=0.0, lower=False):
"""Computes out := alpha*op1(a)*op2(a) + beta*out
op1(a) = a if trans is 'N', op2(a) = a.T if transa is 'N'
op1(a) = a.T if trans is 'T', op2(a) = a if transa is 'T'
lower specifies whether the upper or lower triangular
part of the array out is to be referenced
"""
assert a.ndim == 2
dtype = a.dtype.char
if dtype == 'f':
func = cublas.ssyrk
elif dtype == 'd':
func = cublas.dsyrk
elif dtype == 'F':
func = cublas.csyrk
elif dtype == 'D':
func = cublas.zsyrk
else:
raise TypeError('invalid dtype')
trans = _trans_to_cublas_op(trans)
if trans == cublas.CUBLAS_OP_N:
n, k = a.shape
else:
k, n = a.shape
if out is None:
out = cupy.zeros((n, n), dtype=dtype, order='F')
beta = 0.0
else:
assert out.ndim == 2
assert out.shape == (n, n)
assert out.dtype == dtype
if lower:
uplo = cublas.CUBLAS_FILL_MODE_LOWER
else:
uplo = cublas.CUBLAS_FILL_MODE_UPPER
alpha, alpha_ptr = _get_scalar_ptr(alpha, a.dtype)
beta, beta_ptr = _get_scalar_ptr(beta, a.dtype)
handle = device.get_cublas_handle()
orig_mode = cublas.getPointerMode(handle)
if isinstance(alpha, cupy.ndarray) or isinstance(beta, cupy.ndarray):
if not isinstance(alpha, cupy.ndarray):
alpha = cupy.array(alpha)
alpha_ptr = alpha.data.ptr
if not isinstance(beta, cupy.ndarray):
beta = cupy.array(beta)
beta_ptr = beta.data.ptr
cublas.setPointerMode(handle, cublas.CUBLAS_POINTER_MODE_DEVICE)
else:
cublas.setPointerMode(handle, cublas.CUBLAS_POINTER_MODE_HOST)
lda, trans = _decide_ld_and_trans(a, trans)
ldo, _ = _decide_ld_and_trans(out, trans)
if out._c_contiguous:
if not a._c_contiguous:
a = a.copy(order='C')
trans = 1 - trans
lda = a.shape[1]
try:
func(handle, 1 - uplo, trans, n, k,
alpha_ptr, a.data.ptr, lda,
beta_ptr, out.data.ptr, ldo)
finally:
cublas.setPointerMode(handle, orig_mode)
else:
if not a._f_contiguous:
a = a.copy(order='F')
lda = a.shape[0]
trans = 1 - trans
c = out
if not out._f_contiguous:
c = out.copy(order='F')
try:
func(handle, uplo, trans, n, k,
alpha_ptr, a.data.ptr, lda,
beta_ptr, out.data.ptr, ldo)
finally:
cublas.setPointerMode(handle, orig_mode)
if not out._f_contiguous:
out[...] = c
return out
def geam(transa, transb, alpha, a, beta, b, out=None):
"""Computes alpha * op(a) + beta * op(b)
op(a) = a if transa is 'N', op(a) = a.T if transa is 'T',
op(a) = a.T.conj() if transa is 'H'.
op(b) = b if transb is 'N', op(b) = b.T if transb is 'T',
op(b) = b.T.conj() if transb is 'H'.
"""
assert a.ndim == b.ndim == 2
assert a.dtype == b.dtype
dtype = a.dtype.char
if dtype == 'f':
func = cublas.sgeam
elif dtype == 'd':
func = cublas.dgeam
elif dtype == 'F':
func = cublas.cgeam
elif dtype == 'D':
func = cublas.zgeam
else:
raise TypeError('invalid dtype')
transa = _trans_to_cublas_op(transa)
transb = _trans_to_cublas_op(transb)
if transa == cublas.CUBLAS_OP_N:
m, n = a.shape
else:
n, m = a.shape
if transb == cublas.CUBLAS_OP_N:
assert b.shape == (m, n)
else:
assert b.shape == (n, m)
if out is None:
out = cupy.empty((m, n), dtype=dtype, order='F')
else:
assert out.ndim == 2
assert out.shape == (m, n)
assert out.dtype == dtype
alpha, alpha_ptr = _get_scalar_ptr(alpha, a.dtype)
beta, beta_ptr = _get_scalar_ptr(beta, a.dtype)
handle = device.get_cublas_handle()
orig_mode = cublas.getPointerMode(handle)
if isinstance(alpha, cupy.ndarray) or isinstance(beta, cupy.ndarray):
if not isinstance(alpha, cupy.ndarray):
alpha = cupy.array(alpha)
alpha_ptr = alpha.data.ptr
if not isinstance(beta, cupy.ndarray):
beta = cupy.array(beta)
beta_ptr = beta.data.ptr
cublas.setPointerMode(handle, cublas.CUBLAS_POINTER_MODE_DEVICE)
else:
cublas.setPointerMode(handle, cublas.CUBLAS_POINTER_MODE_HOST)
lda, transa = _decide_ld_and_trans(a, transa)
ldb, transb = _decide_ld_and_trans(b, transb)
if not (lda is None or ldb is None):
if out._f_contiguous:
try:
func(handle, transa, transb, m, n, alpha_ptr, a.data.ptr,
lda, beta_ptr, b.data.ptr, ldb, out.data.ptr, m)
finally:
cublas.setPointerMode(handle, orig_mode)
return out
elif out._c_contiguous:
# Computes alpha * a.T + beta * b.T
try:
func(handle, 1-transa, 1-transb, n, m, alpha_ptr, a.data.ptr,
lda, beta_ptr, b.data.ptr, ldb, out.data.ptr, n)
finally:
cublas.setPointerMode(handle, orig_mode)
return out
a, lda = _change_order_if_necessary(a, lda)
b, ldb = _change_order_if_necessary(b, ldb)
c = out
if not out._f_contiguous:
c = out.copy(order='F')
try:
func(handle, transa, transb, m, n, alpha_ptr, a.data.ptr, lda,
beta_ptr, b.data.ptr, ldb, c.data.ptr, m)
finally:
cublas.setPointerMode(handle, orig_mode)
if not out._f_contiguous:
_core.elementwise_copy(c, out)
return out
def gemv(transa, alpha, a, x, beta, y):
"""Computes y = alpha * op(a) @ x + beta * y
op(a) = a if transa is 'N', op(a) = a.T if transa is 'T',
op(a) = a.T.conj() if transa is 'H'.
Note: ''y'' will be updated.
"""
dtype = a.dtype.char
if dtype == 'f':
func = cublas.sgemv
elif dtype == 'd':
func = cublas.dgemv
elif dtype == 'F':
func = cublas.cgemv
elif dtype == 'D':
func = cublas.zgemv
else:
raise TypeError('invalid dtype')
assert a.ndim == 2
assert x.ndim == y.ndim == 1
assert a.dtype == x.dtype == y.dtype
m, n = a.shape
transa = _trans_to_cublas_op(transa)
if transa == cublas.CUBLAS_OP_N:
xlen, ylen = n, m
else:
xlen, ylen = m, n
assert x.shape[0] == xlen
assert y.shape[0] == ylen
alpha, alpha_ptr = _get_scalar_ptr(alpha, a.dtype)
beta, beta_ptr = _get_scalar_ptr(beta, a.dtype)
handle = device.get_cublas_handle()
orig_mode = cublas.getPointerMode(handle)
if isinstance(alpha, cupy.ndarray) or isinstance(beta, cupy.ndarray):
if not isinstance(alpha, cupy.ndarray):
alpha = cupy.array(alpha)
alpha_ptr = alpha.data.ptr
if not isinstance(beta, cupy.ndarray):
beta = cupy.array(beta)
beta_ptr = beta.data.ptr
cublas.setPointerMode(handle, cublas.CUBLAS_POINTER_MODE_DEVICE)
else:
cublas.setPointerMode(handle, cublas.CUBLAS_POINTER_MODE_HOST)
try:
if a._f_contiguous:
func(handle, transa, m, n, alpha_ptr, a.data.ptr, m, x.data.ptr, 1,
beta_ptr, y.data.ptr, 1)
elif a._c_contiguous and transa != cublas.CUBLAS_OP_C:
if transa == cublas.CUBLAS_OP_N:
transa = cublas.CUBLAS_OP_T
else:
transa = cublas.CUBLAS_OP_N
func(handle, transa, n, m, alpha_ptr, a.data.ptr, n, x.data.ptr, 1,
beta_ptr, y.data.ptr, 1)
else:
a = a.copy(order='F')
func(handle, transa, m, n, alpha_ptr, a.data.ptr, m, x.data.ptr, 1,
beta_ptr, y.data.ptr, 1)
finally:
cublas.setPointerMode(handle, orig_mode)
