Include old csr solver

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jan 2016-07-04 19:30:36 -07:00
parent f24e75d4d1
commit d12ce6c957

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opencl_fdfd/csr.py Normal file
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import numpy
import pyopencl
import pyopencl.array
from pyopencl.elementwise import ElementwiseKernel
from pyopencl.reduction import ReductionKernel
import time
def type_to_C(float_type: numpy.float32 or numpy.float64) -> str:
"""
Returns a string corresponding to the C equivalent of a numpy type.
:param float_type: numpy type: float32, float64, complex64, complex128
:return: string containing the corresponding C type (eg. 'double')
"""
types = {
numpy.float32: 'float',
numpy.float64: 'double',
numpy.complex64: 'cfloat_t',
numpy.complex128: 'cdouble_t',
}
if float_type not in types:
raise Exception('Unsupported type')
return types[float_type]
def create_ops(context):
preamble = '''
#define PYOPENCL_DEFINE_CDOUBLE
#include <pyopencl-complex.h>
'''
ctype = type_to_C(numpy.complex128)
# -------------------------------------
spmv_source = '''
int start = m_row_ptr[i];
int stop = m_row_ptr[i+1];
cdouble_t dot = cdouble_new(0.0, 0.0);
int col_ind, d_ind;
for (int j=start; j<stop; j++) {
col_ind = m_col_ind[j];
d_ind = j;
dot = cdouble_add(dot, cdouble_mul(v_in[col_ind], m_data[d_ind]));
}
v_out[i] = dot;
'''
v_out_args = ctype + ' *v_out, int v_len_half'
m_args = 'int m_nnz, int *m_row_ptr, int *m_col_ind, ' + ctype + ' *m_data'
v_in_args = ctype + ' *v_in'
spmv_kernel = ElementwiseKernel(context, operation=spmv_source, preamble=preamble,
arguments=', '.join((v_out_args, m_args, v_in_args)))
def spmv(v_out, m, v_in, e):
return spmv_kernel(v_out, (v_out.size - 1)//2,
m.data.size, m.row_ptr, m.col_ind, m.data,
v_in, wait_for=e)
# -------------------------------------
update_xr_source = '''
x[i] = cdouble_add(x[i], cdouble_mul(alpha, p[i]));
r[i] = cdouble_sub(r[i], cdouble_mul(alpha, v[i]));
'''
xr_args = ', '.join([ctype + ' ' + f for f in ('*x', '*p', '*r', '*v', 'alpha')])
xr_kernel = ElementwiseKernel(context, operation=update_xr_source, preamble=preamble,
arguments=xr_args)
def xr_update(x, p, r, v, alpha, e):
return xr_kernel(x, p, r, v, alpha, wait_for=e)
# -------------------------------------
update_ri_source = '''
(double3)(r[i].real * r[i].real, \
r[i].real * r[i].imag, \
r[i].imag * r[i].imag)
'''
ri_dtype = pyopencl.array.vec.double3
ri_kernel = ReductionKernel(context, preamble=preamble,
dtype_out=ri_dtype,
neutral='(double3)(0.0, 0.0, 0.0)',
map_expr=update_ri_source,
reduce_expr='a+b',
arguments=ctype + ' *r')
def ri_update(r, e):
g = ri_kernel(r, wait_for=e).astype(ri_dtype).get()
rr, ri, ii = [g[q] for q in 'xyz']
rho = rr + 2j * ri - ii
err = rr + ii
return rho, err
# -------------------------------------
update_p_source = '''
p[i] = cdouble_add(r[i], cdouble_mul(beta, p[i]));
'''
p_args = ctype + ' *p, ' + ctype + ' *r, ' + ctype + ' beta'
p_kernel = ElementwiseKernel(context, preamble=preamble, operation=update_p_source,
arguments=p_args)
def p_update(p, r, beta, e):
return p_kernel(p, r, beta, wait_for=e)
ops = {
'spmv': spmv,
'p_update': p_update,
'ri_update': ri_update,
'xr_update': xr_update,
}
return ops
class CSRMatrix(object):
row_ptr = None # type: pyopencl.array.Array
col_ind = None # type: pyopencl.array.Array
data = None # type: pyopencl.array.Array
def __init__(self, queue, m):
self.row_ptr = pyopencl.array.to_device(queue, m.indptr)
self.col_ind = pyopencl.array.to_device(queue, m.indices)
self.data = pyopencl.array.to_device(queue, m.data.astype(numpy.complex128))
def cg(a, b, max_iters=10000, err_thresh=1e-6, context=None, queue=None, verbose=False):
start_time = time.perf_counter()
if context is None:
context = pyopencl.create_some_context(False)
if queue is None:
queue = pyopencl.CommandQueue(context)
ops = create_ops(context)
x = pyopencl.array.zeros(queue, dtype=numpy.complex128, shape=b.shape)
v = pyopencl.array.empty_like(x)
p = pyopencl.array.zeros_like(x)
r = pyopencl.array.to_device(queue, b)
alpha = 1.0 + 0j
rho = 1.0 + 0j
errs = []
m = CSRMatrix(queue, a)
e = ops['spmv'](v, m, x, [])
e = ops['xr_update'](x, p, r, v, 0.0, [e])
_, err2 = ops['ri_update'](r, [e])
b_norm = numpy.sqrt(err2)
print('b_norm check: ', b_norm)
start_time2 = time.perf_counter()
for k in range(max_iters):
if verbose:
print('[{:06d}] rho {:.4} alpha {:4.4}'.format(k, rho, alpha), end=' ')
rho_prev = rho
e = ops['xr_update'](x, p, r, v, alpha, [e])
rho, err2 = ops['ri_update'](r, [e])
errs += [numpy.sqrt(err2) / b_norm]
if verbose:
print('err', errs[-1])
if errs[-1] < err_thresh:
time_elapsed = time.perf_counter() - start_time
print('Success, {} iterations in {} sec: {} iterations/sec'.format(k,
time_elapsed, k/time_elapsed))
print('overhead', start_time2-start_time)
return x.get(), errs, True
e = ops['p_update'](p, r, rho/rho_prev, [])
e.wait()
ops['spmv'](v, m, p, [e]).wait()
alpha = rho / pyopencl.array.dot(p, v).get()
if k % 1000 == 0:
print(k)
return x.get(), errs, False