Commit c819048d authored by Michael Kuron's avatar Michael Kuron
Browse files

enable optimizations in create_staggered_kernel_2

parent 244d02d0
......@@ -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
Markdown is supported
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment