Simplify csr.cg and use operations from .ops
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@ -1,128 +1,12 @@
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import numpy
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from numpy.linalg import norm
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import pyopencl
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import pyopencl.array
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from pyopencl.elementwise import ElementwiseKernel
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from pyopencl.reduction import ReductionKernel
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import time
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def type_to_C(float_type: numpy.float32 or numpy.float64) -> str:
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"""
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Returns a string corresponding to the C equivalent of a numpy type.
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:param float_type: numpy type: float32, float64, complex64, complex128
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:return: string containing the corresponding C type (eg. 'double')
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"""
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types = {
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numpy.float32: 'float',
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numpy.float64: 'double',
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numpy.complex64: 'cfloat_t',
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numpy.complex128: 'cdouble_t',
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}
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if float_type not in types:
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raise Exception('Unsupported type')
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return types[float_type]
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def create_ops(context):
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preamble = '''
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#define PYOPENCL_DEFINE_CDOUBLE
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#include <pyopencl-complex.h>
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'''
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ctype = type_to_C(numpy.complex128)
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# -------------------------------------
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spmv_source = '''
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int start = m_row_ptr[i];
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int stop = m_row_ptr[i+1];
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cdouble_t dot = cdouble_new(0.0, 0.0);
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int col_ind, d_ind;
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for (int j=start; j<stop; j++) {
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col_ind = m_col_ind[j];
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d_ind = j;
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dot = cdouble_add(dot, cdouble_mul(v_in[col_ind], m_data[d_ind]));
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}
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v_out[i] = dot;
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'''
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v_out_args = ctype + ' *v_out'
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m_args = 'int *m_row_ptr, int *m_col_ind, ' + ctype + ' *m_data'
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v_in_args = ctype + ' *v_in'
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spmv_kernel = ElementwiseKernel(context, operation=spmv_source, preamble=preamble,
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arguments=', '.join((v_out_args, m_args, v_in_args)))
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def spmv(v_out, m, v_in, e):
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return spmv_kernel(v_out, m.row_ptr, m.col_ind, m.data, v_in, wait_for=e)
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# -------------------------------------
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update_xr_source = '''
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x[i] = cdouble_add(x[i], cdouble_mul(alpha, p[i]));
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r[i] = cdouble_sub(r[i], cdouble_mul(alpha, v[i]));
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'''
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xr_args = ', '.join([ctype + ' ' + f for f in ('*x', '*p', '*r', '*v', 'alpha')])
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xr_kernel = ElementwiseKernel(context, operation=update_xr_source, preamble=preamble,
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arguments=xr_args)
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def xr_update(x, p, r, v, alpha, e):
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return xr_kernel(x, p, r, v, alpha, wait_for=e)
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# -------------------------------------
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update_ri_source = '''
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(double3)(r[i].real * r[i].real, \
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r[i].real * r[i].imag, \
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r[i].imag * r[i].imag)
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'''
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ri_dtype = pyopencl.array.vec.double3
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ri_kernel = ReductionKernel(context, preamble=preamble,
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dtype_out=ri_dtype,
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neutral='(double3)(0.0, 0.0, 0.0)',
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map_expr=update_ri_source,
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reduce_expr='a + b',
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arguments=ctype + ' *r')
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def ri_update(r, e):
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g = ri_kernel(r, wait_for=e).astype(ri_dtype).get()
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rr, ri, ii = [g[q] for q in 'xyz']
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rho = rr + 2j * ri - ii
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err = rr + ii
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return rho, err
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# -------------------------------------
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update_p_source = '''
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p[i] = cdouble_add(r[i], cdouble_mul(beta, p[i]));
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'''
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p_args = ctype + ' *p, ' + ctype + ' *r, ' + ctype + ' beta'
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p_kernel = ElementwiseKernel(context, preamble=preamble, operation=update_p_source,
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arguments=p_args)
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def p_update(p, r, beta, e):
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return p_kernel(p, r, beta, wait_for=e)
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ops = {
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'spmv': spmv,
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'p_update': p_update,
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'ri_update': ri_update,
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'xr_update': xr_update,
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}
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return ops
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from . import ops
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class CSRMatrix(object):
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@ -145,32 +29,51 @@ def cg(a, b, max_iters=10000, err_thresh=1e-6, context=None, queue=None, verbose
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if queue is None:
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queue = pyopencl.CommandQueue(context)
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ops = create_ops(context)
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def load_field(v, dtype=numpy.complex128):
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return pyopencl.array.to_device(queue, v.astype(dtype))
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r = load_field(b)
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x = pyopencl.array.zeros_like(r)
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v = pyopencl.array.zeros_like(r)
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p = pyopencl.array.zeros_like(r)
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x = pyopencl.array.zeros(queue, dtype=numpy.complex128, shape=b.shape)
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v = pyopencl.array.zeros_like(x)
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p = pyopencl.array.zeros_like(x)
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r = pyopencl.array.to_device(queue, b)
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alpha = 1.0 + 0j
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rho = 1.0 + 0j
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errs = []
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m = CSRMatrix(queue, a)
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_, err2 = ops['ri_update'](r, [])
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'''
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Generate OpenCL kernels
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'''
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a_step = ops.create_a_csr(context)
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xr_step = ops.create_xr_step(context)
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rhoerr_step = ops.create_rhoerr_step(context)
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p_step = ops.create_p_step(context)
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dot = ops.create_dot(context)
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def a_step(E, H, p, events):
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return a_step_full(E, H, p, inv_dxes, oeps, invm, gpec, gpmc, Pl, Pr, events)
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'''
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Start the solve
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'''
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start_time2 = time.perf_counter()
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_, err2 = rhoerr_step(r, [])
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b_norm = numpy.sqrt(err2)
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print('b_norm check: ', b_norm)
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start_time2 = time.perf_counter()
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success = False
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for k in range(max_iters):
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if verbose:
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print('[{:06d}] rho {:.4} alpha {:4.4}'.format(k, rho, alpha), end=' ')
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rho_prev = rho
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e = ops['xr_update'](x, p, r, v, alpha, [])
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rho, err2 = ops['ri_update'](r, [e])
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e = xr_step(x, p, r, v, alpha, [])
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rho, err2 = rhoerr_step(r, e)
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errs += [numpy.sqrt(err2) / b_norm]
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if verbose:
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@ -179,13 +82,10 @@ def cg(a, b, max_iters=10000, err_thresh=1e-6, context=None, queue=None, verbose
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if errs[-1] < err_thresh:
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success = True
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break
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e = ops['p_update'](p, r, rho/rho_prev, [])
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ops['spmv'](v, m, p, [e]).wait()
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# v2 = a @ p.get()
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# print('norm', norm(v2 - v.get()))
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alpha = rho / pyopencl.array.dot(p, v).get()
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e = p_step(p, r, rho/rho_prev, [])
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e = a_step(v, m, p, e)
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alpha = rho / dot(p, v, e)
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if k % 1000 == 0:
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print(k)
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