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Tom Harke
pystencils
Commits
c819048d
Commit
c819048d
authored
Nov 28, 2019
by
Michael Kuron
Browse files
enable optimizations in create_staggered_kernel_2
parent
244d02d0
Changes
1
Hide whitespace changes
Inline
Side-by-side
pystencils/kernelcreation.py
View file @
c819048d
...
...
@@ -25,7 +25,8 @@ def create_kernel(assignments,
cpu_blocking
=
None
,
gpu_indexing
=
'block'
,
gpu_indexing_params
=
MappingProxyType
({}),
use_textures_for_interpolation
=
True
):
use_textures_for_interpolation
=
True
,
cpu_prepend_optimizations
=
[]):
"""
Creates abstract syntax tree (AST) of kernel, using a list of update equations.
...
...
@@ -49,6 +50,7 @@ def create_kernel(assignments,
gpu_indexing: either 'block' or 'line' , or custom indexing class, see `AbstractIndexing`
gpu_indexing_params: dict with indexing parameters (constructor parameters of indexing class)
e.g. for 'block' one can specify '{'block_size': (20, 20, 10) }'
cpu_prepend_optimizations: list of extra optimizations to perform first on the AST
Returns:
abstract syntax tree (AST) object, that can either be printed as source code with `show_code` or
...
...
@@ -86,6 +88,8 @@ def create_kernel(assignments,
ast
=
create_kernel
(
assignments
,
type_info
=
data_type
,
split_groups
=
split_groups
,
iteration_slice
=
iteration_slice
,
ghost_layers
=
ghost_layers
,
skip_independence_check
=
skip_independence_check
)
for
optimization
in
cpu_prepend_optimizations
:
optimization
(
ast
)
omp_collapse
=
None
if
cpu_blocking
:
omp_collapse
=
loop_blocking
(
ast
,
cpu_blocking
)
...
...
@@ -301,7 +305,7 @@ def create_staggered_kernel_1(staggered_field, expressions, subexpressions=(), t
return
ast
def
create_staggered_kernel_2
(
assignments
,
**
kwargs
):
def
create_staggered_kernel_2
(
assignments
,
gpu_exclusive_conditions
=
False
,
**
kwargs
):
"""Kernel that updates a staggered field.
.. image:: /img/staggered_grid.svg
...
...
@@ -310,12 +314,16 @@ def create_staggered_kernel_2(assignments, **kwargs):
Further index coordinates can be used to store vectors/tensors at each point.
Args:
assignments: a sequence of assignments or AssignmentCollection with one item for each staggered grid point.
assignments: a sequence of assignments or
an
AssignmentCollection with one item for each staggered grid point.
When storing vectors/tensors, the number of items expected is multiplied with the number of
components.
kwargs: passed directly to create_kernel
gpu_exclusive_conditions: whether to use nested conditionals instead of multiple conditionals
kwargs: passed directly to create_kernel, iteration_slice and ghost_layers parameters are not allowed
Returns:
AST, see `create_kernel`
"""
assert
'ghost_layers'
not
in
kwargs
assert
'iteration_slice'
not
in
kwargs
and
'ghost_layers'
not
in
kwargs
subexpressions
=
()
if
isinstance
(
assignments
,
AssignmentCollection
):
...
...
@@ -367,11 +375,16 @@ def create_staggered_kernel_2(assignments, **kwargs):
conditions
.
append
(
counters
[
i
]
>
0
)
return
sp
.
And
(
*
conditions
)
if
gpu_exclusive_conditions
:
raise
NotImplementedError
(
'gpu_exclusive_conditions is not implemented yet'
)
for
d
,
direction
in
zip
(
range
(
points
),
staggered_field
.
staggered_stencil
):
sp_assignments
=
[
SympyAssignment
(
assignments
[
d
].
lhs
,
assignments
[
d
].
rhs
)]
+
\
[
SympyAssignment
(
s
.
lhs
,
s
.
rhs
)
for
s
in
subexpressions
]
last_conditional
=
Conditional
(
condition
(
direction
),
Block
(
sp_assignments
))
final_assignments
.
append
(
last_conditional
)
ast
=
create_kernel
(
final_assignments
,
ghost_layers
=
ghost_layers
,
**
kwargs
)
prepend_optimizations
=
[
remove_conditionals_in_staggered_kernel
,
move_constants_before_loop
]
ast
=
create_kernel
(
final_assignments
,
ghost_layers
=
ghost_layers
,
cpu_prepend_optimizations
=
prepend_optimizations
,
**
kwargs
)
return
ast
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