diff --git a/python/dune/perftool/options.py b/python/dune/perftool/options.py
index 25fd514582a9873eb26cf59f50897b1dbe59cdc9..c0f4900b8fff2f77b7cbefd593214cfc8d3af87d 100644
--- a/python/dune/perftool/options.py
+++ b/python/dune/perftool/options.py
@@ -94,6 +94,7 @@ class PerftoolFormOptionsArray(ImmutableRecord):
vectorization_target = PerftoolOption(_type=float, helpstr="The cost function target for the 'target' cost model. Only needed to verify the cost model itself, do not use light-heartedly!!!")
simplify = PerftoolOption(default=False, helpstr="Whether to simplify expressions using sympy")
generate_jacobians = PerftoolOption(default=True, helpstr="Whether jacobian_* methods should be generated. This is set to false automatically, when numerical_jacobian is set to true.")
+ generate_jacobian_apply = PerftoolOption(default=False, helpstr="Wether jacobian_allpy_* methods should be generated.")
generate_residuals = PerftoolOption(default=True, helpstr="Whether alpha_* methods should be generated.")
unroll_dimension_loops = PerftoolOption(default=False, helpstr="whether loops over the geometric dimension should be unrolled")
precompute_quadrature_info = PerftoolOption(default=True, helpstr="compute quadrature points and weights in the constructor of the local operator")
@@ -172,7 +173,7 @@ def process_form_options(opt, form):
opt = opt.copy(unroll_dimension_loops=True)
if opt.numerical_jacobian:
- opt = opt.copy(generate_jacobians=False)
+ opt = opt.copy(generate_jacobians=False, generate_jacobian_apply=False)
if opt.form is None:
opt = opt.copy(form=form)
@@ -189,6 +190,10 @@ def process_form_options(opt, form):
generate_jacobians=False,
matrix_free=True,
)
+
+ if opt.matrix_free:
+ opt = opt.copy(generate_jacobian_apply=True)
+
return opt
diff --git a/python/dune/perftool/pdelab/driver/__init__.py b/python/dune/perftool/pdelab/driver/__init__.py
index 3877165c574ac8ef7b6d7197b56f97d071f38f42..591c022ddedd8656102f1594d5148714bd7561de 100644
--- a/python/dune/perftool/pdelab/driver/__init__.py
+++ b/python/dune/perftool/pdelab/driver/__init__.py
@@ -253,7 +253,7 @@ def generate_driver():
from dune.perftool.loopy.target import type_floatingpoint
pre_include("#define HP_TIMER_OPCOUNTER {}".format(type_floatingpoint()), filetag="driver")
evaluate_residual_timer()
- if get_form_option("matrix_free"):
+ if get_form_option("generate_jacobian_apply"):
apply_jacobian_timer()
elif is_stationary():
from dune.perftool.pdelab.driver.solve import dune_solve
diff --git a/python/dune/perftool/pdelab/driver/solve.py b/python/dune/perftool/pdelab/driver/solve.py
index cdf41b82ddd3a4f33e3beb0b8ef29cfab6d012e5..25747850ba9188f6141b6f848584daed3dd09921 100644
--- a/python/dune/perftool/pdelab/driver/solve.py
+++ b/python/dune/perftool/pdelab/driver/solve.py
@@ -52,8 +52,10 @@ def dune_solve():
snp = name_stationarynonlinearproblemsolver(go_type, go)
solve = "{}.apply();".format(snp)
- print_residual()
- print_matrix()
+ if get_form_option("generate_residuals"):
+ print_residual()
+ if get_form_option("generate_jacobians"):
+ print_matrix()
if get_option('instrumentation_level') >= 2:
from dune.perftool.pdelab.driver.timings import setup_timer, name_timing_stream, name_timing_identifier
diff --git a/python/dune/perftool/pdelab/localoperator.py b/python/dune/perftool/pdelab/localoperator.py
index 4daeb45a7627f7bda1d83c178e83a20a5362607c..1f808ef1c90f4b358b60d6f4744a2322a726e055 100644
--- a/python/dune/perftool/pdelab/localoperator.py
+++ b/python/dune/perftool/pdelab/localoperator.py
@@ -797,7 +797,7 @@ def generate_residual_kernels(form, original_form):
)
# In the case of matrix free operator evaluation we need jacobian apply methods
- if get_form_option("matrix_free"):
+ if get_form_option("generate_jacobian_apply"):
from dune.perftool.pdelab.driver import is_linear
if is_linear(original_form):
# Numeical jacobian apply base class
@@ -840,35 +840,7 @@ def generate_jacobian_kernels(form, original_form):
jacform = offdiagonal_block_jacobian(jacform)
operator_kernels = {}
- with global_context(form_type="jacobian"):
- if get_form_option("generate_jacobians"):
- if get_form_option("sumfact"):
- was_sumfact = True
- if get_form_option("sumfact_regular_jacobians"):
- set_form_option("sumfact", False)
- for measure in set(i.integral_type() for i in jacform.integrals()):
- logger.info("generate_jacobian_kernels: measure {}".format(measure))
- with global_context(integral_type=measure):
- from dune.perftool.pdelab.signatures import assembler_routine_name
- with global_context(kernel=assembler_routine_name()):
- kernel = [k for k in get_backend(interface="generate_kernels_per_integral")(jacform.integrals_by_type(measure))]
- operator_kernels[(measure, 'jacobian')] = kernel
-
- # Generate dummy functions for those kernels, that vanished in the differentiation process
- # We *could* solve this problem by using lambda_* terms but we do not really want that, so
- # we use empty jacobian assembly methods instead
- alpha_measures = set(i.integral_type() for i in form.integrals())
- jacobian_measures = set(i.integral_type() for i in jacform.integrals())
- for it in alpha_measures - jacobian_measures:
- with global_context(integral_type=it):
- from dune.perftool.pdelab.signatures import assembly_routine_signature
- operator_kernels[(it, 'jacobian')] = [LoopyKernelMethod(assembly_routine_signature(), kernel=None)]
- if get_form_option("sumfact_regular_jacobians"):
- if was_sumfact:
- set_form_option("sumfact", True)
-
- # Jacobian apply methods for matrix-free computations
- if get_form_option("matrix_free"):
+ if get_form_option("generate_jacobian_apply"):
# The apply vector has reserved index 1 so we directly use Coefficient class from ufl
from ufl import Coefficient
apply_coefficient = Coefficient(form.coefficients()[0].ufl_element(), 1)
@@ -895,6 +867,33 @@ def generate_jacobian_kernels(form, original_form):
with global_context(integral_type=it):
from dune.perftool.pdelab.signatures import assembly_routine_signature
operator_kernels[(it, 'jacobian_apply')] = [LoopyKernelMethod(assembly_routine_signature(), kernel=None)]
+ if get_form_option("generate_jacobians"):
+ with global_context(form_type="jacobian"):
+ if get_form_option("generate_jacobians"):
+ if get_form_option("sumfact"):
+ was_sumfact = True
+ if get_form_option("sumfact_regular_jacobians"):
+ set_form_option("sumfact", False)
+ for measure in set(i.integral_type() for i in jacform.integrals()):
+ logger.info("generate_jacobian_kernels: measure {}".format(measure))
+ with global_context(integral_type=measure):
+ from dune.perftool.pdelab.signatures import assembler_routine_name
+ with global_context(kernel=assembler_routine_name()):
+ kernel = [k for k in get_backend(interface="generate_kernels_per_integral")(jacform.integrals_by_type(measure))]
+ operator_kernels[(measure, 'jacobian')] = kernel
+
+ # Generate dummy functions for those kernels, that vanished in the differentiation process
+ # We *could* solve this problem by using lambda_* terms but we do not really want that, so
+ # we use empty jacobian assembly methods instead
+ alpha_measures = set(i.integral_type() for i in form.integrals())
+ jacobian_measures = set(i.integral_type() for i in jacform.integrals())
+ for it in alpha_measures - jacobian_measures:
+ with global_context(integral_type=it):
+ from dune.perftool.pdelab.signatures import assembly_routine_signature
+ operator_kernels[(it, 'jacobian')] = [LoopyKernelMethod(assembly_routine_signature(), kernel=None)]
+ if get_form_option("sumfact_regular_jacobians"):
+ if was_sumfact:
+ set_form_option("sumfact", True)
return operator_kernels