Source code for sumpy.p2e

from __future__ import division, absolute_import

__copyright__ = "Copyright (C) 2013 Andreas Kloeckner"

__license__ = """
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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The above copyright notice and this permission notice shall be included in
all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
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"""

import six
from six.moves import range

import numpy as np
import loopy as lp
from loopy.version import MOST_RECENT_LANGUAGE_VERSION

from sumpy.tools import KernelCacheWrapper

import logging
logger = logging.getLogger(__name__)


__doc__ = """

Particle-to-expansion
---------------------

.. autoclass:: P2EBase
.. autoclass:: P2EFromSingleBox
.. autoclass:: P2EFromCSR

"""


# {{{ P2E base class

[docs]class P2EBase(KernelCacheWrapper): def __init__(self, ctx, expansion, options=[], name=None, device=None): """ :arg expansion: a subclass of :class:`sympy.expansion.ExpansionBase` :arg strength_usage: A list of integers indicating which expression uses which source strength indicator. This implicitly specifies the number of strength arrays that need to be passed. Default: all kernels use the same strength. """ if device is None: device = ctx.devices[0] from sumpy.kernel import TargetDerivativeRemover expansion = expansion.with_kernel( TargetDerivativeRemover()(expansion.kernel)) self.ctx = ctx self.expansion = expansion self.options = options self.name = name or self.default_name self.device = device self.dim = expansion.dim def get_loopy_instructions(self): from sumpy.symbolic import make_sym_vector avec = make_sym_vector("a", self.dim) import sumpy.symbolic as sp rscale = sp.Symbol("rscale") from sumpy.assignment_collection import SymbolicAssignmentCollection sac = SymbolicAssignmentCollection() coeff_names = [ sac.assign_unique("coeff%d" % i, coeff_i) for i, coeff_i in enumerate( self.expansion.coefficients_from_source(avec, None, rscale))] sac.run_global_cse() from sumpy.codegen import to_loopy_insns return to_loopy_insns( six.iteritems(sac.assignments), vector_names=set(["a"]), pymbolic_expr_maps=[self.expansion.get_code_transformer()], retain_names=coeff_names, complex_dtype=np.complex128 # FIXME ) def get_cache_key(self): return (type(self).__name__, self.name, self.expansion)
# }}} # {{{ P2E from single box (P2M, likely)
[docs]class P2EFromSingleBox(P2EBase): default_name = "p2e_from_single_box" def get_kernel(self): ncoeffs = len(self.expansion) from sumpy.tools import gather_loopy_source_arguments loopy_knl = lp.make_kernel( [ "{[isrc_box]: 0<=isrc_box<nsrc_boxes}", "{[isrc,idim]: isrc_start<=isrc<isrc_end and 0<=idim<dim}", ], [""" for isrc_box <> src_ibox = source_boxes[isrc_box] <> isrc_start = box_source_starts[src_ibox] <> isrc_end = isrc_start+box_source_counts_nonchild[src_ibox] <> center[idim] = centers[idim, src_ibox] {id=fetch_center} for isrc <> a[idim] = center[idim] - sources[idim, isrc] {dup=idim} <> strength = strengths[isrc] """] + self.get_loopy_instructions() + [""" end """] + [""" tgt_expansions[src_ibox-tgt_base_ibox, {coeffidx}] = \ simul_reduce(sum, isrc, strength*coeff{coeffidx}) \ {{id_prefix=write_expn}} """.format(coeffidx=i) for i in range(ncoeffs)] + [""" end """], [ lp.GlobalArg("sources", None, shape=(self.dim, "nsources"), dim_tags="sep,c"), lp.GlobalArg("strengths", None, shape="nsources"), lp.GlobalArg("box_source_starts,box_source_counts_nonchild", None, shape=None), lp.GlobalArg("centers", None, shape="dim, aligned_nboxes"), lp.ValueArg("rscale", None), lp.GlobalArg("tgt_expansions", None, shape=("nboxes", ncoeffs), offset=lp.auto), lp.ValueArg("nboxes,aligned_nboxes,tgt_base_ibox", np.int32), lp.ValueArg("nsources", np.int32), "..." ] + gather_loopy_source_arguments([self.expansion]), name=self.name, assumptions="nsrc_boxes>=1", silenced_warnings="write_race(write_expn*)", default_offset=lp.auto, fixed_parameters=dict(dim=self.dim), lang_version=MOST_RECENT_LANGUAGE_VERSION) loopy_knl = self.expansion.prepare_loopy_kernel(loopy_knl) loopy_knl = lp.tag_inames(loopy_knl, "idim*:unr") return loopy_knl def get_optimized_kernel(self): # FIXME knl = self.get_kernel() knl = lp.split_iname(knl, "isrc_box", 16, outer_tag="g.0") return knl def __call__(self, queue, **kwargs): """ :arg expansions: :arg source_boxes: :arg box_source_starts: :arg box_source_counts_nonchild: :arg centers: :arg sources: :arg strengths: :arg rscale: """ centers = kwargs.pop("centers") # "1" may be passed for rscale, which won't have its type # meaningfully inferred. Make the type of rscale explicit. rscale = centers.dtype.type(kwargs.pop("rscale")) knl = self.get_cached_optimized_kernel() return knl(queue, centers=centers, rscale=rscale, **kwargs)
# }}} # {{{ P2E from CSR-like interaction list
[docs]class P2EFromCSR(P2EBase): default_name = "p2e_from_csr" def get_kernel(self): ncoeffs = len(self.expansion) from sumpy.tools import gather_loopy_source_arguments arguments = ( [ lp.GlobalArg("sources", None, shape=(self.dim, "nsources"), dim_tags="sep,c"), lp.GlobalArg("strengths", None, shape="nsources"), lp.GlobalArg("source_box_starts,source_box_lists", None, shape=None, offset=lp.auto), lp.GlobalArg("box_source_starts,box_source_counts_nonchild", None, shape=None), lp.GlobalArg("centers", None, shape="dim, naligned_boxes"), lp.GlobalArg("tgt_expansions", None, shape=("ntgt_level_boxes", ncoeffs), offset=lp.auto), lp.ValueArg("naligned_boxes,ntgt_level_boxes,tgt_base_ibox", np.int32), lp.ValueArg("nsources", np.int32), "..." ] + gather_loopy_source_arguments([self.expansion])) loopy_knl = lp.make_kernel( [ "{[itgt_box]: 0<=itgt_box<ntgt_boxes}", "{[isrc_box]: isrc_box_start<=isrc_box<isrc_box_stop}", "{[isrc]: isrc_start<=isrc<isrc_end}", "{[idim]: 0<=idim<dim}", ], [""" for itgt_box <> tgt_ibox = target_boxes[itgt_box] <> center[idim] = centers[idim, tgt_ibox] {id=fetch_center} <> isrc_box_start = source_box_starts[itgt_box] <> isrc_box_stop = source_box_starts[itgt_box+1] for isrc_box <> src_ibox = source_box_lists[isrc_box] <> isrc_start = box_source_starts[src_ibox] <> isrc_end = isrc_start+box_source_counts_nonchild[src_ibox] for isrc <> a[idim] = center[idim] - sources[idim, isrc] \ {dup=idim} <> strength = strengths[isrc] """] + self.get_loopy_instructions() + [""" end end """] + [""" tgt_expansions[tgt_ibox - tgt_base_ibox, {coeffidx}] = \ simul_reduce(sum, (isrc_box, isrc), strength*coeff{coeffidx}) \ {{id_prefix=write_expn}} """.format(coeffidx=i) for i in range(ncoeffs)] + [""" end """], arguments, name=self.name, assumptions="ntgt_boxes>=1", silenced_warnings="write_race(write_expn*)", default_offset=lp.auto, fixed_parameters=dict(dim=self.dim), lang_version=MOST_RECENT_LANGUAGE_VERSION) loopy_knl = self.expansion.prepare_loopy_kernel(loopy_knl) loopy_knl = lp.tag_inames(loopy_knl, "idim*:unr") return loopy_knl def get_optimized_kernel(self): # FIXME knl = self.get_kernel() knl = lp.split_iname(knl, "itgt_box", 16, outer_tag="g.0") return knl def __call__(self, queue, **kwargs): """ :arg expansions: :arg source_boxes: :arg box_source_starts: :arg box_source_counts_nonchild: :arg centers: :arg sources: :arg strengths: :arg rscale: """ knl = self.get_cached_optimized_kernel() centers = kwargs.pop("centers") # "1" may be passed for rscale, which won't have its type # meaningfully inferred. Make the type of rscale explicit. rscale = centers.dtype.type(kwargs.pop("rscale")) return knl(queue, centers=centers, rscale=rscale, **kwargs)
# }}} # vim: foldmethod=marker