def ker_ind_inc():
return ast.FunDecl(
'void', 'ker_ind_inc', [
ast.Decl('int', 'B', qualifiers=['unsigned'], pointers=['', '']),
ast.Decl('int', 'A', qualifiers=['unsigned'], pointers=[''])
],
ast.Block([ast.Incr(ast.Symbol('B', (0, 0)), ast.Symbol('A', (0, )))]))
def ker_write2d():
return ast.FunDecl(
'void', 'ker_write2d',
[ast.Decl('int', 'V', qualifiers=['unsigned'], pointers=[''])],
ast.Block([
ast.Assign(ast.Symbol('V', (0, )), 1),
ast.Assign(ast.Symbol('V', (1, )), 2)
]))
def get_restriction_kernel(fiat_element, unique_indices, dim=1, no_weights=False):
weights = restriction_weights(fiat_element)[unique_indices].T
ncdof = weights.shape[0]
nfdof = weights.shape[1]
arglist = [ast.Decl("double", ast.Symbol("coarse", (ncdof*dim, ))),
ast.Decl("double *restrict *restrict ", ast.Symbol("fine", ()),
qualifiers=["const"])]
if not no_weights:
arglist.append(ast.Decl("double *restrict *restrict", ast.Symbol("count_weights", ()),
qualifiers=["const"]))
all_ones = np.allclose(weights, 1.0)
if all_ones:
w = []
else:
w_sym = ast.Symbol("weights", (ncdof, nfdof))
init = ast.ArrayInit(format_array_literal(weights))
w = [ast.Decl("double", w_sym, init,
qualifiers=["const"])]
i = ast.Symbol("i", ())
j = ast.Symbol("j", ())
k = ast.Symbol("k", ())
fine = ast.Symbol("fine", (j, k))
if no_weights:
if all_ones:
assign = fine
else:
assign = ast.Prod(fine, ast.Symbol("weights", (i, j)))
else:
if all_ones:
assign = ast.Prod(fine, ast.Symbol("count_weights", (j, 0)))
else:
assign = ast.Prod(fine,
ast.Prod(ast.Symbol("weights", (i, j)),
ast.Symbol("count_weights", (j, 0))))
assignment = ast.Incr(ast.Symbol("coarse", (ast.Sum(k, ast.Prod(i, ast.c_sym(dim))),)),
assign)
k_loop = ast.For(ast.Decl("int", k, ast.c_sym(0)),
ast.Less(k, ast.c_sym(dim)),
ast.Incr(k, ast.c_sym(1)),
ast.Block([assignment], open_scope=True))
j_loop = ast.For(ast.Decl("int", j, ast.c_sym(0)),
ast.Less(j, ast.c_sym(nfdof)),
ast.Incr(j, ast.c_sym(1)),
ast.Block([k_loop], open_scope=True))
i_loop = ast.For(ast.Decl("int", i, ast.c_sym(0)),
ast.Less(i, ast.c_sym(ncdof)),
ast.Incr(i, ast.c_sym(1)),
ast.Block([j_loop], open_scope=True))
k = ast.FunDecl("void", "restriction", arglist, ast.Block(w + [i_loop]),
pred=["static", "inline"])
return op2.Kernel(k, "restriction", opts=parameters["coffee"])
def get_count_kernel(arity):
arglist = [ast.Decl("double", ast.Symbol("weight", (arity, )))]
i = ast.Symbol("i", ())
assignment = ast.Incr(ast.Symbol("weight", (i, )), ast.c_sym(1.0))
loop = ast.For(ast.Decl("int", i, ast.c_sym(0)),
ast.Less(i, ast.c_sym(arity)),
ast.Incr(i, ast.c_sym(1)),
ast.Block([assignment], open_scope=True))
k = ast.FunDecl("void", "count_weights", arglist,
ast.Block([loop]),
pred=["static", "inline"])
return op2.Kernel(k, "count_weights", opts=parameters["coffee"])
def construct_ast(self, name, args, statements):
"""Constructs the full kernel AST of a given SLATE expression. The :class:`Transformer`
is used to perform the conversion from standard C into the Eigen C++ template library
syntax.
:arg name: a string denoting the name of the macro kernel.
:arg args: a list of arguments for the macro_kernel.
:arg statements: a `coffee.base.Block` of instructions, which contains declarations
of temporaries, function calls to all subkernels and any auxilliary
information needed to evaulate the SLATE expression.
E.g. facet integral loops and action loops.
Returns: the full kernel AST to be converted into a PyOP2 kernel, as well as any
orientation information.
"""
# all kernel body statements must be wrapped up as a coffee.base.Block
assert isinstance(statements, ast.Block)
macro_kernel = ast.FunDecl("void",
name,
args,
statements,
pred=["static", "inline"])
kernel_list = []
transformer = Transformer()
oriented = False
# Assume self.kernel_exprs is populated at this point
for kernel_items in self.kernel_exprs.values():
for ks in kernel_items:
oriented = oriented or ks.kinfo.oriented
# TODO: Extend multiple domains support
assert ks.kinfo.subdomain_id == "otherwise"
kast = transformer.visit(ks.kinfo.kernel._ast)
kernel_list.append(kast)
kernel_list.append(macro_kernel)
return ast.Node(kernel_list), oriented
def ast_matmul(self, F_a, implementation='optimized'):
"""Generate an AST for a PyOP2 kernel performing a matrix-vector multiplication."""
# The number of dofs on each element is /ndofs*cdim/
F_a_fs = F_a.function_space()
ndofs = F_a_fs.fiat_element.entity_dofs()
ndofs = sum(self.mesh.make_dofs_per_plex_entity(ndofs))
cdim = F_a_fs.dim
name = 'mat_vec_mul_kernel_%s' % F_a_fs.name
identifier = (ndofs, cdim, name, implementation)
if identifier in self.asts:
return self.asts[identifier]
from coffee import isa, options
if cdim and cdim % isa['dp_reg'] == 0:
simd_pragma = '#pragma simd reduction(+:sum)'
else:
simd_pragma = ''
# Craft the AST
if implementation == 'optimized' and cdim >= 4:
body = ast.Incr(
ast.Symbol('sum'),
ast.Prod(
ast.Symbol('A', ('i', ),
((ndofs * cdim, 'j*%d + k' % cdim), )),
ast.Symbol('B', ('j', 'k'))))
body = ast.c_for('k', cdim, body, simd_pragma).children[0]
body = [
ast.Decl('const int',
ast.Symbol('index'),
init=ast.Symbol('i%%%d' % cdim)),
ast.Decl('double', ast.Symbol('sum'), init=ast.Symbol('0.0')),
ast.c_for('j', ndofs, body).children[0],
ast.Assign(ast.Symbol('C', ('i/%d' % cdim, 'index')), 'sum')
]
body = ast.Block([ast.c_for('i', ndofs * cdim, body).children[0]])
funargs = [
ast.Decl('double* restrict', 'A'),
ast.Decl('double *restrict *restrict', 'B'),
ast.Decl('double *restrict *', 'C')
]
fundecl = ast.FunDecl('void', name, funargs, body,
['static', 'inline'])
else:
body = ast.Incr(
ast.Symbol('C', ('i/%d' % cdim, 'index')),
ast.Prod(
ast.Symbol('A', ('i', ),
((ndofs * cdim, 'j*%d + k' % cdim), )),
ast.Symbol('B', ('j', 'k'))))
body = ast.c_for('k', cdim, body).children[0]
body = [
ast.Decl('const int',
ast.Symbol('index'),
init=ast.Symbol('i%%%d' % cdim)),
ast.Assign(ast.Symbol('C', ('i/%d' % cdim, 'index' % cdim)),
'0.0'),
ast.c_for('j', ndofs, body).children[0]
]
body = ast.Block([ast.c_for('i', ndofs * cdim, body).children[0]])
funargs = [
ast.Decl('double* restrict', 'A'),
ast.Decl('double *restrict *restrict', 'B'),
ast.Decl('double *restrict *', 'C')
]
fundecl = ast.FunDecl('void', name, funargs, body,
['static', 'inline'])
# Track the AST for later fast retrieval
self.asts[identifier] = fundecl
return fundecl
def exterior_facet_boundary_node_map(self, method):
'''The :class:`pyop2.Map` from exterior facets to the nodes on
those facets. Note that this differs from
:meth:`exterior_facet_node_map` in that only surface nodes
are referenced, not all nodes in cells touching the surface.
:arg method: The method for determining boundary nodes. See
:class:`~.bcs.DirichletBC`.
'''
el = self.fiat_element
dim = self._mesh.facet_dimension()
if method == "topological":
boundary_dofs = el.entity_closure_dofs()[dim]
elif method == "geometric":
boundary_dofs = el.facet_support_dofs()
nodes_per_facet = \
len(boundary_dofs[0])
# HACK ALERT
# The facet set does not have a halo associated with it, since
# we only construct halos for DoF sets. Fortunately, this
# loop is direct and we already have all the correct
# information available locally. So We fake a set of the
# correct size and carry out a direct loop
facet_set = op2.Set(self._mesh.exterior_facets.set.total_size)
fs_dat = op2.Dat(facet_set**el.space_dimension(),
data=self.exterior_facet_node_map().values_with_halo)
facet_dat = op2.Dat(facet_set**nodes_per_facet, dtype=np.int32)
local_facet_nodes = np.array(
[dofs for e, dofs in boundary_dofs.iteritems()])
# Helper function to turn the inner index of an array into c
# array literals.
c_array = lambda xs: "{" + ", ".join(map(str, xs)) + "}"
body = ast.Block([
ast.Decl("int",
ast.Symbol("l_nodes",
(len(el.get_reference_element().topology[dim]),
nodes_per_facet)),
init=ast.ArrayInit(
c_array(map(c_array, local_facet_nodes))),
qualifiers=["const"]),
ast.For(
ast.Decl("int", "n", 0), ast.Less("n", nodes_per_facet),
ast.Incr("n", 1),
ast.Assign(
ast.Symbol("facet_nodes", ("n", )),
ast.Symbol("cell_nodes", ("l_nodes[facet[0]][n]", ))))
])
kernel = op2.Kernel(
ast.FunDecl("void", "create_bc_node_map", [
ast.Decl("int*", "cell_nodes"),
ast.Decl("int*", "facet_nodes"),
ast.Decl("unsigned int*", "facet")
], body), "create_bc_node_map")
local_facet_dat = op2.Dat(
facet_set**self._mesh.exterior_facets._rank,
self._mesh.exterior_facets.local_facet_dat.data_ro_with_halos,
dtype=np.uintc)
op2.par_loop(kernel, facet_set, fs_dat(op2.READ), facet_dat(op2.WRITE),
local_facet_dat(op2.READ))
if isinstance(self._mesh, mesh_t.ExtrudedMesh):
offset = self.offset[boundary_dofs[0]]
else:
offset = None
return op2.Map(facet_set,
self.node_set,
nodes_per_facet,
facet_dat.data_ro_with_halos,
name="exterior_facet_boundary_node",
offset=offset)
