Refactor distributed eval mapper

pytential/symbolic/execution.py

@@ -381,36 +381,37 @@ def exec_assign(self, actx: PyOpenCLArrayContext, insn, bound_expr, evaluate):
     def exec_compute_potential_insn(
             self, actx: PyOpenCLArrayContext, insn, bound_expr, evaluate):
         from pytential.qbx.distributed import DistributedQBXLayerPotentialSource
-        return_timing_data = self.timing_data is not None
 
-        is_distributed_fmm = None
+        mpi_rank = self.comm.Get_rank()
         use_target_specific_qbx = None
         fmm_backend = None
         qbx_order = None
         fmm_level_to_order = None
         expansion_factory = None
 
-        if self.comm.Get_rank() == 0:
-            source = bound_expr.places.get_geometry(insn.source.geometry)
-            is_distributed_fmm = isinstance(
-                source, DistributedQBXLayerPotentialSource)
-            if is_distributed_fmm:
-                use_target_specific_qbx = source._use_target_specific_qbx
-                fmm_backend = source.fmm_backend
-                qbx_order = source.qbx_order
-                fmm_level_to_order = source.fmm_level_to_order
-                expansion_factory = source.expansion_factory
-
-        is_distributed_fmm = self.comm.bcast(is_distributed_fmm, root=0)
-        if is_distributed_fmm:
-            use_target_specific_qbx = self.comm.bcast(
-                use_target_specific_qbx, root=0)
-            fmm_backend = self.comm.bcast(fmm_backend, root=0)
-            qbx_order = self.comm.bcast(qbx_order, root=0)
-            fmm_level_to_order = self.comm.bcast(fmm_level_to_order, root=0)
-            expansion_factory = self.comm.bcast(expansion_factory, root=0)
-
-        if is_distributed_fmm and self.comm.Get_rank() != 0:
+        if mpi_rank == 0:
+            source: DistributedQBXLayerPotentialSource = \
+                bound_expr.places.get_geometry(insn.source.geometry)
+            if not isinstance(source, DistributedQBXLayerPotentialSource):
+                raise TypeError("Distributed execution mapper can only process"
+                                "distributed layer potential source")
+
+            use_target_specific_qbx = source._use_target_specific_qbx
+            fmm_backend = source.fmm_backend
+            qbx_order = source.qbx_order
+            fmm_level_to_order = source.fmm_level_to_order
+            expansion_factory = source.expansion_factory
+
+        use_target_specific_qbx = self.comm.bcast(
+            use_target_specific_qbx, root=0)
+        fmm_backend = self.comm.bcast(fmm_backend, root=0)
+        qbx_order = self.comm.bcast(qbx_order, root=0)
+        fmm_level_to_order = self.comm.bcast(fmm_level_to_order, root=0)
+        expansion_factory = self.comm.bcast(expansion_factory, root=0)
+
+        assert isinstance(fmm_backend, str)
+
+        if mpi_rank != 0:
             source = DistributedQBXLayerPotentialSource(
                 self.comm,
                 actx.context,
@@ -420,18 +421,18 @@ def exec_compute_potential_insn(
                 fmm_backend=fmm_backend,
                 expansion_factory=expansion_factory)
 
-        if self.comm.Get_rank() == 0 or is_distributed_fmm:
-            result, timing_data = (
-                    source.exec_compute_potential_insn(
-                        actx, insn, bound_expr, evaluate, return_timing_data))
+        return_timing_data = self.timing_data is not None
+        result, timing_data = (
+                source.exec_compute_potential_insn(
+                    actx, insn, bound_expr, evaluate, return_timing_data))
 
-            if return_timing_data:
-                # The compiler ensures this.
-                assert insn not in self.timing_data
+        if return_timing_data:
+            # The compiler ensures this.
+            assert insn not in self.timing_data
 
-                self.timing_data[insn] = timing_data
+            self.timing_data[insn] = timing_data
 
-            return result
+        return result
 
     def __call__(self, expr, *args, **kwargs):
         if self.comm.Get_rank() == 0: