Merge branch 'staggered' into 'master'

Make create_staggered_kernel work with OpenMP

See merge request pycodegen/pystencils!123

pystencils/kernelcreation.py

@@ -24,6 +24,7 @@ def create_kernel(assignments,
                   cpu_openmp=False,
                   cpu_vectorize_info=None,
                   cpu_blocking=None,
+                  omp_single_loop=True,
                   gpu_indexing='block',
                   gpu_indexing_params=MappingProxyType({}),
                   use_textures_for_interpolation=True,
@@ -47,6 +48,7 @@ def create_kernel(assignments,
         skip_independence_check: don't check that loop iterations are independent. This is needed e.g. for
                                  periodicity kernel, that access the field outside the iteration bounds. Use with care!
         cpu_openmp: True or number of threads for OpenMP parallelization, False for no OpenMP
+        omp_single_loop: if OpenMP is active: whether multiple outer loops are permitted
         cpu_vectorize_info: a dictionary with keys, 'vector_instruction_set', 'assume_aligned' and 'nontemporal'
                             for documentation of these parameters see vectorize function. Example:
                             '{'instruction_set': 'avx512', 'assume_aligned': True, 'nontemporal':True}'
@@ -99,7 +101,7 @@ def create_kernel(assignments,
         if cpu_blocking:
             omp_collapse = loop_blocking(ast, cpu_blocking)
         if cpu_openmp:
-            add_openmp(ast, num_threads=cpu_openmp, collapse=omp_collapse)
+            add_openmp(ast, num_threads=cpu_openmp, collapse=omp_collapse, assume_single_outer_loop=omp_single_loop)
         if cpu_vectorize_info:
             if cpu_vectorize_info is True:
                 vectorize(ast)
@@ -237,7 +239,7 @@ def create_staggered_kernel(assignments, target='cpu', gpu_exclusive_conditions=
     Returns:
         AST, see `create_kernel`
     """
-    assert 'iteration_slice' not in kwargs and 'ghost_layers' not in kwargs
+    assert 'iteration_slice' not in kwargs and 'ghost_layers' not in kwargs and 'omp_single_loop' not in kwargs
 
     if isinstance(assignments, AssignmentCollection):
         subexpressions = assignments.subexpressions + [a for a in assignments.main_assignments
@@ -325,7 +327,7 @@ def create_staggered_kernel(assignments, target='cpu', gpu_exclusive_conditions=
 
         if target == 'cpu':
             from pystencils.cpu import create_kernel as create_kernel_cpu
-            ast = create_kernel_cpu(final_assignments, ghost_layers=ghost_layers, **kwargs)
+            ast = create_kernel_cpu(final_assignments, ghost_layers=ghost_layers, omp_single_loop=False, **kwargs)
         else:
             ast = create_kernel(final_assignments, ghost_layers=ghost_layers, target=target, **kwargs)
         return ast
@@ -341,6 +343,6 @@ def create_staggered_kernel(assignments, target='cpu', gpu_exclusive_conditions=
     remove_start_conditional = any([gl[0] == 0 for gl in ghost_layers])
     prepend_optimizations = [lambda ast: remove_conditionals_in_staggered_kernel(ast, remove_start_conditional),
                              move_constants_before_loop]
-    ast = create_kernel(final_assignments, ghost_layers=ghost_layers, target=target,
+    ast = create_kernel(final_assignments, ghost_layers=ghost_layers, target=target, omp_single_loop=False,
                         cpu_prepend_optimizations=prepend_optimizations, **kwargs)
     return ast

pystencils_tests/test_staggered_kernel.py

@@ -5,7 +5,7 @@ import pystencils as ps
 
 
 class TestStaggeredDiffusion:
-    def _run(self, num_neighbors, target='cpu'):
+    def _run(self, num_neighbors, target='cpu', openmp=False):
         L = (40, 40)
         D = 0.066
         dt = 1
@@ -33,8 +33,8 @@ class TestStaggeredDiffusion:
             flux += [ps.Assignment(j.staggered_access("SW"), xy_staggered),
                      ps.Assignment(j.staggered_access("NW"), xY_staggered)]
 
-        staggered_kernel = ps.create_staggered_kernel(flux, target=dh.default_target).compile()
-        div_kernel = ps.create_kernel(update, target=dh.default_target).compile()
+        staggered_kernel = ps.create_staggered_kernel(flux, target=dh.default_target, cpu_openmp=openmp).compile()
+        div_kernel = ps.create_kernel(update, target=dh.default_target, cpu_openmp=openmp).compile()
 
         def time_loop(steps):
             sync = dh.synchronization_function([c.name])
@@ -74,6 +74,9 @@ class TestStaggeredDiffusion:
         import pystencils.opencl.autoinit
         self._run(4, 'opencl')
 
+    def test_diffusion_openmp(self):
+        self._run(4, openmp=True)
+
 
 def test_staggered_subexpressions():
     dh = ps.create_data_handling((10, 10), periodicity=True, default_target='cpu')